# Best Statistical Analysis Software *By [Bijou Barry](https://research.g2.com/insights/author/bijou-barry)* Statistical analysis software products are specialized programs designed to allow users to perform complex statistical analysis. These products typically provide tools for the organization, interpretation, and presentation of selected data sets. Statistical solutions typically package these data management capabilities with features specific to statistical analysis. Statistical analysis capabilities refer to capabilities that support analysis methodologies such as regression analysis, predictive analytics, and statistical modelling, among many others. The [bes statistical analysis software](https://learn.g2.com/best-statistical-analysis-software) is typically used by data scientists and mathematicians, but can provide industry-specific features. These may be features tailored to scientific research, cost modelling, or health science; other tools can perform specific statistical analysis across industry or use case. Some products overlap within both statistical analysis software and [predictive analytics software](https://www.g2.com/categories/predictive-analytics) or [business intelligence platforms](https://www.g2.com/categories/business-intelligence-platforms). However, most tools in those categories will not provide the same level of niche statistical analysis capabilities as statistical software. To qualify for inclusion in the Statistical Analysis category, a product must: - Package statistical analysis capabilities, equations, and models - Facilitate data importing, preparation and modelling - Perform complex statistical analysis ## Best Statistical Analysis Software At A Glance - **Leader:** [SAS Viya](https://www.g2.com/products/sas-sas-viya/reviews) - **Highest Performer:** [GraphPad Prism](https://www.g2.com/products/graphpad-prism/reviews) - **Easiest to Use:** [SAS Viya](https://www.g2.com/products/sas-sas-viya/reviews) - **Top Trending:** [SAS Viya](https://www.g2.com/products/sas-sas-viya/reviews) - **Best Free Software:** [IBM SPSS Statistics](https://www.g2.com/products/ibm-spss-statistics/reviews) ## Top-Rated Products (Ranked by G2 Score) ### 1. [SAS Viya](https://www.g2.com/products/sas-sas-viya/reviews) SAS Viya is a cloud-native data and AI platform that enables teams to build, deploy and scale explainable AI that drives trusted, confident decisions. It unites the entire data and AI life cycle and empowers teams to innovate quickly while balancing speed, automation and governance by design. Viya unifies data management, advanced analytics and decisioning in a single platform, so organizations can move from experimentation to production with confidence, delivering measurable business impact that is secure, explainable and scalable across any environment. Key capabilities required to deliver trusted decisions include: • End-to-end clarity across the data and AI life cycle, with built-in lineage, auditability and continuous monitoring to support defensible decisions. • Governance by design, enabling consistent oversight across data, models and decisions to reduce risk and accelerate adoption. • Explainable AI at scale, so insights and outcomes can be understood, validated and trusted by business and regulators alike. • Operationalized analytics, ensuring value continues beyond deployment through monitoring, retraining and life cycle management. • Flexible, cloud-native deployment, allowing organizations to start anywhere and scale everywhere while maintaining control. **Average Rating:** 4.3/5.0 **Total Reviews:** 696 **User Satisfaction Scores:** - **Quality Control:** 8.9/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 8.3/10 (Category avg: 8.8/10) - **Survival Analysis:** 8.9/10 (Category avg: 8.4/10) - **Data Sampling:** 8.9/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [SAS Institute Inc.](https://www.g2.com/sellers/sas-institute-inc-df6dde22-a5e5-4913-8b21-4fa0c6c5c7c2) - **Company Website:** https://www.sas.com/ - **Year Founded:** 1976 - **HQ Location:** Cary, NC - **Twitter:** @SASsoftware (60,957 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1491/ (18,238 employees on LinkedIn®) **Reviewer Demographics:** - **Who Uses This:** Student, Statistical Programmer - **Top Industries:** Pharmaceuticals, Computer Software - **Company Size:** 33% Enterprise, 32% Small-Business #### Pros & Cons **Pros:** - Ease of Use (316 reviews) - Features (218 reviews) - Analytics (196 reviews) - Data Analysis (166 reviews) - User Interface (147 reviews) **Cons:** - Learning Difficulty (151 reviews) - Learning Curve (144 reviews) - Complexity (143 reviews) - Difficult Learning (117 reviews) - Expensive (108 reviews) ### 2. [IBM SPSS Statistics](https://www.g2.com/products/ibm-spss-statistics/reviews) IBM SPSS Statistics is an end-to-end statistical solution that simplifies advanced statistical analysis across industries for users of any statistical expertise. It offers comprehensive resources, expert support, and proven reliability to transform complex data into impactful decisions IBM SPSS Statistics recent version 31 release comes up with powerful new features such as AI Output Assistant, UX and security enhancements and advanced algorithms. IBM SPSS Statistics • offers an easy to use drag and drop interface along with AI Output Assistant to interpret complex statistical output in easy language. • simplifies complex data analysis using advanced statistical techniques that performs data preparation and management, to analysis and reporting. • performs predictive analysis using advanced forecasting procedures to uncover patterns and predict future trends. • creates compelling visual representations to identify trends, derive accurate conclusions and deliver graphs and presentation-ready reports Explore how both individuals and organizations spanning across Industries can simply complex statistical test through an easy to use, accurate ,reliable and secure solution. Use Cases 1. Market Research - Statistical procedures highlighting how to do market research with IBM SPSS 2. Client Acquisition – Emphasizes on how can organizations can acquire more clients and understand consumer behavior 3. Forecasting – Analyze historical sales data, evaluate key trends, predict outcomes relevant to inventory planning 4. Healthcare - Enabling healthcare organizations to improve patient outcomes 5. Government - Empowering Government institutions to take smarter policy decisions 6. Supply Chain - Utilize Statistical Algorithms to make data-driven decisions across procurement, inventory, logistics, and demand planning. Visit here to see what's new in v31 - https://www.ibm.com/products/spss-statistics/whats-new **Average Rating:** 4.2/5.0 **Total Reviews:** 888 **User Satisfaction Scores:** - **Quality Control:** 8.5/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 8.0/10 (Category avg: 8.8/10) - **Survival Analysis:** 8.4/10 (Category avg: 8.4/10) - **Data Sampling:** 8.7/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [IBM](https://www.g2.com/sellers/ibm) - **Company Website:** https://www.ibm.com/us-en - **Year Founded:** 1911 - **HQ Location:** Armonk, NY - **Twitter:** @IBM (708,000 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1009/ (324,553 employees on LinkedIn®) **Reviewer Demographics:** - **Who Uses This:** Research Assistant, Assistant Professor - **Top Industries:** Higher Education, Research - **Company Size:** 43% Enterprise, 30% Mid-Market #### Pros & Cons **Pros:** - Ease of Use (33 reviews) - Statistical Analysis (19 reviews) - Data Management (15 reviews) - User Interface (13 reviews) - Analysis Capabilities (12 reviews) **Cons:** - Expensive (19 reviews) - Poor Visualization (12 reviews) - Learning Curve (11 reviews) - Outdated Interface (7 reviews) - Performance Issues (7 reviews) ### 3. [Minitab Statistical Software](https://www.g2.com/products/minitab-statistical-software/reviews) Minitab® Statistical Software is a comprehensive data analysis solution designed to assist users in making informed, data-driven decisions through visualizations, statistical analysis, and predictive analytics. This software caters to a diverse audience, enabling individuals and organizations—regardless of their statistical expertise or geographical location—to harness the power of data analysis with user-friendly tools. The software is particularly beneficial for businesses and institutions seeking to identify trends, solve complex problems, and extract valuable insights from their data. With nearly 50 years of experience in the field, Minitab has established itself as a trusted partner for organizations of all sizes, including many of the top Fortune 500 companies. Its suite of tools, which includes Minitab Engage®, Minitab Workspace™, Minitab Connect®, Quality Trainer®, and Salford Predictive Modeler®, is designed to streamline the process of data analysis and process improvement across various industries. Key features of Minitab® Statistical Software include a wide range of statistical tests, graphical representations, and predictive modeling capabilities. Users can easily create visualizations that help to clarify complex data sets, making it simpler to identify patterns and trends. The software also offers robust statistical analysis tools that allow users to perform hypothesis testing, regression analysis, and control charts, among other functions. These features empower users to make faster and more accurate decisions, ultimately driving business excellence. Minitab stands out in its category due to its unparalleled ease of use, which allows users with varying levels of statistical knowledge to engage with the software effectively. The intuitive interface and comprehensive support resources ensure that users can quickly learn how to leverage the software’s capabilities to address their specific needs. By providing access to powerful analytics tools, Minitab enables organizations to foster a culture of data-driven decision-making, leading to improved operational efficiency and enhanced strategic planning. In summary, Minitab® Statistical Software is an essential tool for organizations looking to enhance their data analysis capabilities. By offering a suite of powerful features designed for users of all backgrounds, Minitab not only simplifies the process of data analysis but also empowers organizations to unlock the full potential of their data for informed decision-making. **Average Rating:** 4.6/5.0 **Total Reviews:** 218 **User Satisfaction Scores:** - **Quality Control:** 8.2/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 8.6/10 (Category avg: 8.8/10) - **Survival Analysis:** 8.3/10 (Category avg: 8.4/10) - **Data Sampling:** 8.4/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [Minitab](https://www.g2.com/sellers/minitab-14ca02fe-fdeb-44c4-b0db-904058d0221b) - **Company Website:** https://www.minitab.com - **Year Founded:** 1972 - **HQ Location:** State College, Pennsylvania, United States - **Twitter:** @Minitab (5,022 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/39142/ (706 employees on LinkedIn®) **Reviewer Demographics:** - **Who Uses This:** Quality Manager - **Top Industries:** Automotive, Manufacturing - **Company Size:** 46% Enterprise, 32% Mid-Market #### Pros & Cons **Pros:** - Ease of Use (63 reviews) - Data Analysis (54 reviews) - Statistical Analysis (39 reviews) - Analysis (32 reviews) - Analysis Capabilities (30 reviews) **Cons:** - Expensive (23 reviews) - Learning Curve (22 reviews) - Not User-Friendly (14 reviews) - Complexity (13 reviews) - Limited Features (11 reviews) ### 4. [Base SAS](https://www.g2.com/products/base-sas/reviews) Base SAS is a comprehensive software suite that provides a flexible and extensible fourth-generation programming language (4GL) designed for data access, transformation, analysis, and reporting. It serves as the foundation of the SAS System, enabling users to manage and analyze data efficiently across various platforms. With its intuitive syntax and extensive library of prewritten procedures, Base SAS simplifies complex data tasks, making it an essential tool for data professionals. Key Features and Functionality: - Intuitive 4GL Programming Language: Offers an easy-to-learn syntax with hundreds of language elements and functions, supporting tasks from data extraction and cleansing to reporting and information delivery. - Rich Library of Integrated Procedures: Provides prewritten procedures for data manipulation, management, information storage, retrieval, and report writing, enhancing productivity by reducing the need for extensive coding. - Powerful Data Analysis Tools: Capable of performing a wide range of analyses, from simple descriptive statistics to advanced data correlation and distribution analysis. - Cross-Platform Support: Runs on all major computing platforms, allowing seamless integration into any computing environment and ensuring code portability across different systems. - Web-Based Interface: Includes SAS Studio, a web-based developer interface that enables access to data files, libraries, and existing programs from any device with a web browser, facilitating coding and data management tasks. Primary Value and Solutions Provided: Base SAS significantly reduces programming and maintenance time by offering an intuitive programming language and a comprehensive set of tools for data management and analysis. It enables organizations to integrate data across diverse environments, ensuring a unified view of information. The software simplifies the creation and distribution of visually appealing reports in various formats, including Microsoft Excel, PowerPoint, PDF, and HTML, catering to the preferred platforms of decision-makers. By providing a robust and scalable solution, Base SAS addresses the challenges of complex data manipulation and reporting, empowering users to derive meaningful insights and make informed decisions. **Average Rating:** 4.4/5.0 **Total Reviews:** 123 **User Satisfaction Scores:** - **Quality Control:** 9.4/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 8.6/10 (Category avg: 8.8/10) - **Survival Analysis:** 9.1/10 (Category avg: 8.4/10) - **Data Sampling:** 9.2/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [SAS Institute Inc.](https://www.g2.com/sellers/sas-institute-inc-df6dde22-a5e5-4913-8b21-4fa0c6c5c7c2) - **Year Founded:** 1976 - **HQ Location:** Cary, NC - **Twitter:** @SASsoftware (60,957 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1491/ (18,238 employees on LinkedIn®) - **Phone:** 1-800-727-0025 **Reviewer Demographics:** - **Top Industries:** Pharmaceuticals, Hospital & Health Care - **Company Size:** 49% Enterprise, 28% Small-Business #### Pros & Cons **Pros:** - Ease of Use (16 reviews) - Coding Simplification (12 reviews) - Learning (8 reviews) - Data Management (7 reviews) - Performance Efficiency (6 reviews) **Cons:** - Complexity (5 reviews) - Poor Visualization (5 reviews) - Slow Performance (5 reviews) - Learning Difficulty (4 reviews) - Not User-Friendly (3 reviews) ### 5. [Posit](https://www.g2.com/products/posit-posit/reviews) Posit, formerly RStudio, is dedicated to advancing open-source software for data science, scientific research, and technical communication. Trusted by millions of users, including 25% of the Fortune Global 100, Posit empowers organizations to drive innovation and informed decision-making. We focus on making data science more open, intuitive, accessible, and collaborative, offering tools that enable powerful insights and smarter, data-driven decisions. We build popular open-source tools like the RStudio IDE and Shiny, as well as enterprise-level tools for professional data science teams, including Posit Team, Posit Connect, Posit Workbench, and Posit Package Manager. **Average Rating:** 4.5/5.0 **Total Reviews:** 563 **User Satisfaction Scores:** - **Quality Control:** 8.7/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 8.6/10 (Category avg: 8.8/10) - **Survival Analysis:** 8.9/10 (Category avg: 8.4/10) - **Data Sampling:** 9.2/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [Posit](https://www.g2.com/sellers/posit) - **Year Founded:** 2009 - **HQ Location:** Boston, MA - **Twitter:** @posit_pbc (121,263 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1978648/ (448 employees on LinkedIn®) **Reviewer Demographics:** - **Who Uses This:** Research Assistant, Graduate Research Assistant - **Top Industries:** Higher Education, Information Technology and Services - **Company Size:** 49% Enterprise, 27% Mid-Market #### Pros & Cons **Pros:** - Ease of Use (13 reviews) - Features (9 reviews) - Open Source (7 reviews) - Customer Support (5 reviews) - Easy Integrations (5 reviews) **Cons:** - Slow Performance (7 reviews) - Learning Curve (4 reviews) - Performance Issues (4 reviews) - Steep Learning Curve (4 reviews) - Lagging Performance (3 reviews) ### 6. [Orange](https://www.g2.com/products/orange/reviews) Orange is an open-source software suite designed for data visualization, machine learning, and data mining. Developed by the Bioinformatics Laboratory at the University of Ljubljana, it offers a user-friendly, component-based visual programming interface that enables users to construct complex data analysis workflows without the need for coding. This makes Orange accessible to both beginners and experienced data scientists, facilitating efficient and interactive data exploration. Key Features and Functionality: - Visual Programming Interface: Users can create analytical workflows by placing and connecting widgets on a canvas, streamlining the data analysis process. - Extensive Widget Library: Orange provides over 100 widgets for tasks such as data input, preprocessing, visualization, modeling, and evaluation, allowing for comprehensive data analysis. - Interactive Data Visualization: The software supports various visualization techniques, including scatter plots, heatmaps, dendrograms, and box plots, enabling dynamic and real-time data exploration. - Machine Learning Capabilities: Orange includes tools for classification, regression, clustering, and other machine learning techniques, supporting both supervised and unsupervised learning. - Extensibility through Add-ons: Specialized add-ons are available for tasks like text mining, bioinformatics, image analytics, and time series analysis, enhancing the software's functionality. - Python Integration: Advanced users can extend Orange's capabilities or write custom scripts within the platform, combining visual programming with the flexibility of Python scripting. Primary Value and User Solutions: Orange democratizes data analysis by providing an intuitive, code-free environment for constructing and visualizing data workflows. Its modular design allows users to focus on data exploration and interpretation rather than programming, making it particularly valuable for educators, researchers, and professionals seeking to perform complex analyses efficiently. By lowering the barrier to entry in data science, Orange empowers users to make data-driven decisions and gain insights without extensive technical expertise. **Average Rating:** 4.2/5.0 **Total Reviews:** 29 **User Satisfaction Scores:** - **Quality Control:** 8.1/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 9.2/10 (Category avg: 8.8/10) - **Survival Analysis:** 8.3/10 (Category avg: 8.4/10) - **Data Sampling:** 8.3/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [Orange](https://www.g2.com/sellers/orange) - **HQ Location:** Issy-les-Moulineaux, FR - **Twitter:** @OrangeDataMiner (2,906 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/orange/ (142,726 employees on LinkedIn®) **Reviewer Demographics:** - **Top Industries:** Computer Software - **Company Size:** 61% Small-Business, 21% Mid-Market #### Pros & Cons **Pros:** - Ease of Use (1 reviews) - Learning (1 reviews) - Machine Learning (1 reviews) ### 7. [OriginPro](https://www.g2.com/products/originpro/reviews) Origin is a user-friendly and easy-to-learn software application that provides data analysis and publication-quality graphing capabilities tailored to the needs of scientists and engineers. OriginPro offers extended analysis tools for Peak Fitting, Surface Fitting, Statistics, Signal Processing and Image Handling. Along with general statistical tools such as descriptive statistics, T-tests, ANOVA, and survival analysis, OriginPro also offers advanced Time Series analysis and Quality Improvement tools including DOE, SPC, and MSA. Users can customize operations such as importing, graphing and analysis, all from the GUI. Graphs, analysis results and reports update automatically when data or parameters change. This allows for batch analysis of multiple files or data sets without the need for programming. **Average Rating:** 4.7/5.0 **Total Reviews:** 138 **User Satisfaction Scores:** - **Quality Control:** 7.6/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 9.4/10 (Category avg: 8.8/10) - **Survival Analysis:** 8.3/10 (Category avg: 8.4/10) - **Data Sampling:** 9.1/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [OriginLab Corp.](https://www.g2.com/sellers/originlab-corp) - **Company Website:** https://www.originlab.com - **Year Founded:** 1992 - **HQ Location:** Northampton, MA - **Twitter:** @OriginLab (2,429 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/205815/ (34 employees on LinkedIn®) **Reviewer Demographics:** - **Who Uses This:** Research Scientist - **Top Industries:** Research, Higher Education - **Company Size:** 46% Enterprise, 34% Small-Business #### Pros & Cons **Pros:** - Analysis (10 reviews) - Data Analysis (10 reviews) - Ease of Use (10 reviews) - Visualization (10 reviews) - Graphical Visualization (9 reviews) **Cons:** - Learning Curve (5 reviews) - Not User-Friendly (4 reviews) - Complexity (3 reviews) - Expensive (3 reviews) - Limited Flexibility (3 reviews) ### 8. [Statista](https://www.g2.com/products/statista/reviews) Statista is a global leader in data and insights, trusted by 30,000 business and academic clients worldwide. If you’re tired of searching multiple sources for reliable information, Statista is your solution. With an unrivaled breadth of data on markets, industries, and consumers, Statista provides the essential foundation to uncover trends, validate strategies, and drive success. We help you quickly access credible market and consumer data, back up your ideas, and create impactful presentations, all while gaining comprehensive insights to inform your decisions and fuel growth. Book a demo today to see how Statista can simplify the way you access and use data. **Average Rating:** 4.4/5.0 **Total Reviews:** 29 **User Satisfaction Scores:** - **Quality Control:** 7.5/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 8.5/10 (Category avg: 8.8/10) - **Survival Analysis:** 7.4/10 (Category avg: 8.4/10) - **Data Sampling:** 8.1/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [Statista](https://www.g2.com/sellers/statista) - **HQ Location:** Hamburg, DE - **Twitter:** @StatistaCharts (145,680 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/statista/ (1,346 employees on LinkedIn®) **Reviewer Demographics:** - **Top Industries:** Marketing and Advertising - **Company Size:** 41% Small-Business, 31% Mid-Market #### Pros & Cons **Pros:** - Insights (5 reviews) - Statistical Analysis (5 reviews) - Customer Support (4 reviews) - Ease of Use (3 reviews) - Data Visualization (2 reviews) **Cons:** - Data Management (2 reviews) - Expensive (2 reviews) - Complexity (1 reviews) - Not User-Friendly (1 reviews) ### 9. [Qualtrics Strategy & Research](https://www.g2.com/products/qualtrics-strategy-research/reviews) Used by more than 13,000 brands and 75% of the Fortune 500, Qualtrics CoreXM is the most trusted, intelligent, and scalable all-in-one platform for experience management. Qualtrics CoreXM is the foundational research tool for building, launching, and analyzing survey research. With CoreXM, you can bring siloed or outsourced operations into a holistic, end-to-end platform for all insights that you are looking to gather and act upon. Featuring capabilities and solutions for every department, CoreXM helps you to reach your audiences wherever they are, ensuring you get insights faster than ever before. You can even create your own projects, or use projects designed by Qualtrics experts — for brand, customer insights, product research or employee experience — so you can take action where it’s needed most. With Qualtrics CoreXM, you enable everyone to capture, analyze and share actionable insights and use them to identify or improve existing products, services and experiences. It’s time to increase your experience data efficiency with the world’s most flexible solution for modern-day research and feedback. 1) Focus on the right outcomes Empower every decision with predictive insights and AI-powered recommendations to take the right actions and improve experiences. This includes AI-driven text analytics to understand open-ended feedback at scale, reporting for each stakeholder, and plenty more. 2) Sophisticated research made simple Create, customize, and modify any research project in minutes with a point-and-click UI, PhD-backed methodologies, and a robust library of more than 100 question types and templates designed by survey scientists. All ready to use, with no coding required, ever. 3) Drive speed and agility Scale access to experience insights across the organization with purpose-built solutions, workflows, and easy collaboration. Add to that a flexible platform with unmatched integrations into the systems your organization already uses. 4) Save time and money Standardize your research on a single platform to build out a comprehensive system of record for all your respondent data. Become a research expert with AI that does the heavy lifting for you, offering recommendations to improve survey quality and compatibility. 5) Consolidate and streamline research Through one unified system that connects and centralizes everyone’s ability to listen, understand and act on feedback and experience opportunities, delve deeper into data, design personal experiences at scale, and drastically increase research efficiency. 6) Reduce risk exposure Featuring unbeatable enterprise-grade security, compliance and governance functionality, Qualtrics CoreXM is GDPR, HITRUST, ISO 27001 certified and FedRAMP compliant. 7) Expand your bandwidth with experts on demand Make your data work harder for you. Enlist our Research Services and network of partners for support with design, analytics, reporting and respondent sourcing. Plus, thanks to a fully flexible engagement model, use us as much, or as little, as you need. \* Key Qualtrics CoreXM product features - Expert designed templates - Drag-and-drop survey builder - Automated XM Solutions - Customizable survey themes - Full collaboration tools - Advanced survey logic - Quota management - Built-in, AI-driven methodology and question quality analysis (ExpertReview) - AI-powered analytics and intelligence (Stats iQ & Text iQ) - Crosstabs - REST API access for system integration - SMS distribution - WCAG 2.0 compliant - Email and chat support \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ - ABOUT QUALTRICS Qualtrics is the technology platform that organizations use to collect, manage and act on experience data, also called X-data. The Qualtrics XM Platform is a system of action, used by teams, departments, and entire organizations to manage the four core experiences of business — customer, product, employee, and brand — on one platform. \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ - Qualtrics CustomerXM Hear every customer’s voice, fix every broken experience, and increase customer loyalty and spend. Featuring the ultimate listening engine, as well as predictive intelligence and analytics, and full closed-loop actioning capabilities, Qualtrics CustomerXM enables you to go beyond measurement and drive action throughout the organization. https://www.g2.com/products/qualtrics-customer-experience/reviews \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ - Qualtrics ProductXM Bring your customers into product development with Qualtrics ProductXM. Seek out and solve broken product experiences, all with one system of action for everything from market assessment and concept testing to pricing and packaging. https://www.qualtrics.com/product-experience/ \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ - Qualtrics EmployeeXM Gather continuous feedback from every employee experience to take the right actions to impact engagement, talent planning, productivity and innovation. With Qualtrics EmployeeXM, empower everyone in your organization to take actions that put your people first. This includes AI-driven analytics and IO psychology-based decision tools, guided manager action planning, real-time automated workflows and much more. https://www.g2.com/products/qualtrics-employee-experience/reviews \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ - Qualtrics BrandXM Don’t just track your brand’s past — get the keys to increase market share and acquire customers faster than ever before. With Qualtrics Brand Experience Management (BrandXM), empower your organization with world-class technology and trusted methodologies and expert guidance so you can stay ahead of the competition, both now and in the future. Featuring both holistic brand performance tools, real-time market insights, automated alerts, and adaptable surveys, you can quickly craft data-driven brand strategies based on proven approaches. https://www.qualtrics.com/brand-experience/ \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ - Qualtrics DesignXM Uncover market trends, changing behaviors, and unmet needs, and then take the right actions to design the experiences people want next. Qualtrics DesignXM is an advanced market research solution that combines experience feedback, sophisticated research methodologies, and analytics in a single platform. With real-time insights, and automated actions embedded into every business workflow, DesignXM gives everyone the tools to create experiences that power breakthrough products and services. https://www.qualtrics.com/design-xm/ **Average Rating:** 4.4/5.0 **Total Reviews:** 2,902 **User Satisfaction Scores:** - **Quality Control:** 8.5/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 8.7/10 (Category avg: 8.8/10) - **Survival Analysis:** 8.3/10 (Category avg: 8.4/10) - **Data Sampling:** 8.2/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [Qualtrics](https://www.g2.com/sellers/qualtrics) - **Company Website:** https://www.qualtrics.com - **Year Founded:** 2002 - **HQ Location:** Provo, UT - **Twitter:** @Qualtrics (42,143 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/314350/ (6,019 employees on LinkedIn®) **Reviewer Demographics:** - **Who Uses This:** Student, Research Assistant - **Top Industries:** Higher Education, Education Management - **Company Size:** 45% Enterprise, 33% Mid-Market #### Pros & Cons **Pros:** - Ease of Use (296 reviews) - Survey Creation (246 reviews) - Features (109 reviews) - Intuitive (99 reviews) - Ease of Creation (82 reviews) **Cons:** - Survey Issues (79 reviews) - Survey Limitations (62 reviews) - Learning Curve (53 reviews) - Limited Customization (47 reviews) - Pricing Issues (47 reviews) ### 10. [JMP](https://www.g2.com/products/jmp/reviews) JMP, data analysis software for Mac and Windows, combines the strength of interactive visualization with powerful statistics. Importing and processing data is easy. The drag-and-drop interface, dynamically linked graphs, libraries of advanced analytic functionality, scripting language and ways of sharing findings with others, allows users to dig deeply into their data, with greater ease and speed. Originally developed in the 1980’s to capture the new value in GUI for personal computers, JMP remains dedicated to adding cutting-edge statistical methods and special analysis techniques from a variety of industries to the software’s functionality with each release. The organization's founder, John Sall, still serves as Chief Architect. To see a full list of data connectors please visit https://www.jmp.com/en/software/analytic-workflow/data-connectors **Average Rating:** 4.5/5.0 **Total Reviews:** 206 **User Satisfaction Scores:** - **Quality Control:** 8.6/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 8.9/10 (Category avg: 8.8/10) - **Survival Analysis:** 8.7/10 (Category avg: 8.4/10) - **Data Sampling:** 8.8/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [JMP Statistical Discovery](https://www.g2.com/sellers/jmp-statistical-discovery) - **Company Website:** https://www.jmp.com - **Year Founded:** 1989 - **HQ Location:** Cary, North Carolina - **Twitter:** @JMP_software (2,759 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/jmp/ (1,002 employees on LinkedIn®) **Reviewer Demographics:** - **Who Uses This:** Student - **Top Industries:** Higher Education, Information Technology and Services - **Company Size:** 42% Enterprise, 33% Small-Business #### Pros & Cons **Pros:** - Ease of Use (10 reviews) - Data Visualization (9 reviews) - Statistical Analysis (5 reviews) - Visualization (5 reviews) - User Interface (4 reviews) **Cons:** - Expensive (6 reviews) - Learning Curve (4 reviews) - Limited Flexibility (4 reviews) - Learning Difficulty (3 reviews) - Limitations in Storage (2 reviews) ### 11. [GraphPad Prism](https://www.g2.com/products/graphpad-prism/reviews) GraphPad Prism is a comprehensive scientific software designed to streamline data analysis, graphing, and presentation for researchers across various disciplines. It combines robust statistical analysis capabilities with intuitive graphing tools, enabling users to efficiently interpret complex datasets and produce publication-quality visuals. Prism's user-friendly interface and guided workflows make it accessible to both novice and experienced scientists, facilitating accurate and reproducible results. Key Features and Functionality: - Data Organization: Prism offers structured data tables tailored for different types of analyses, including quantitative and categorical data, ensuring accurate data entry and management. - Statistical Analysis: The software provides a wide array of statistical tests such as t-tests, ANOVA (one-, two-, and three-way), linear and nonlinear regression, survival analysis, and principal component analysis, all presented in clear language to aid understanding. - Graphing and Visualization: Users can create a variety of graph types, including scatter plots, bar charts, and bubble plots, with extensive customization options to enhance data visualization. - Nonlinear Regression: Prism simplifies curve fitting with over 100 built-in equations, allowing for robust nonlinear regression analyses, including dose-response curves and growth models. - Automation and Reproducibility: The software enables automation of repetitive analyses without the need for programming, ensuring consistency and efficiency in data processing. - Collaboration Tools: Prism Cloud facilitates project sharing and collaboration, allowing teams to view and discuss projects in real-time, enhancing collective research efforts. Primary Value and User Solutions: GraphPad Prism addresses the critical need for accurate and efficient data analysis in scientific research. By integrating statistical analysis with advanced graphing capabilities, it reduces the complexity of data interpretation, allowing researchers to focus on deriving meaningful insights. The software's intuitive design and guided analyses minimize the learning curve, making sophisticated statistical methods accessible to a broader audience. Additionally, Prism's collaboration features streamline teamwork, ensuring that research findings are easily shared and discussed, ultimately accelerating the research process and enhancing the quality of scientific outputs. **Average Rating:** 4.6/5.0 **Total Reviews:** 54 **User Satisfaction Scores:** - **Quality Control:** 9.0/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 8.3/10 (Category avg: 8.8/10) - **Survival Analysis:** 9.2/10 (Category avg: 8.4/10) - **Data Sampling:** 9.3/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [GraphPad Software](https://www.g2.com/sellers/graphpad-software) - **Year Founded:** 1989 - **HQ Location:** San Diego, California - **Twitter:** @GraphPad (1,872 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/18737349/ (11 employees on LinkedIn®) **Reviewer Demographics:** - **Top Industries:** Research, Higher Education - **Company Size:** 35% Small-Business, 33% Enterprise #### Pros & Cons **Pros:** - Ease of Use (3 reviews) - Statistical Analysis (3 reviews) - Graphical Visualization (2 reviews) - Customer Support (1 reviews) - Data Analysis (1 reviews) **Cons:** - Expensive (2 reviews) - Limited Resources (1 reviews) - Poor Educational Resources (1 reviews) ### 12. [XLSTAT](https://www.g2.com/products/xlstat/reviews) The leading data analysis and statistical solution for Microsoft Excel®. XLSTAT is a powerful yet flexible Excel data analysis add-on that allows users to analyze, customize and share results within Microsoft Excel. With over 250 standard to advanced statistical features available, XLSTAT is the preferred tool for statistical analysis in businesses and universities, large and small, and for 110,000+ users in over 120 countries across the world. **Average Rating:** 4.7/5.0 **Total Reviews:** 45 **User Satisfaction Scores:** - **Quality Control:** 8.8/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 10.0/10 (Category avg: 8.8/10) - **Survival Analysis:** 7.4/10 (Category avg: 8.4/10) - **Data Sampling:** 8.9/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [Lumivero](https://www.g2.com/sellers/lumivero) - **Year Founded:** 1995 - **HQ Location:** Denver, CO - **Twitter:** @LUMIVER0 (397 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/76790/ (303 employees on LinkedIn®) **Reviewer Demographics:** - **Top Industries:** Research, Higher Education - **Company Size:** 58% Small-Business, 28% Enterprise #### Pros & Cons **Pros:** - Ease of Use (4 reviews) - Graphical Visualization (2 reviews) - Statistical Analysis (2 reviews) - Customer Support (1 reviews) - Data Analysis (1 reviews) **Cons:** - Expensive (3 reviews) - Expensive Subscriptions (1 reviews) ### 13. [SAS Visual Statistics](https://www.g2.com/products/sas-visual-statistics/reviews) Multiple users can explore data, then interactively create and refine predictive models. Distributed, in-memory processing slashes model development time, quickly surfacing valuable insights you can act on. **Average Rating:** 4.4/5.0 **Total Reviews:** 24 **User Satisfaction Scores:** - **Quality Control:** 7.5/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 8.1/10 (Category avg: 8.8/10) - **Survival Analysis:** 7.9/10 (Category avg: 8.4/10) - **Data Sampling:** 7.9/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [SAS Institute Inc.](https://www.g2.com/sellers/sas-institute-inc-df6dde22-a5e5-4913-8b21-4fa0c6c5c7c2) - **Year Founded:** 1976 - **HQ Location:** Cary, NC - **Twitter:** @SASsoftware (60,957 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1491/ (18,238 employees on LinkedIn®) - **Phone:** 1-800-727-0025 **Reviewer Demographics:** - **Company Size:** 52% Enterprise, 32% Small-Business #### Pros & Cons **Pros:** - Ease of Use (3 reviews) - Analytics (2 reviews) - Customer Support (2 reviews) - Machine Learning (2 reviews) - Reporting (2 reviews) **Cons:** - Expensive (3 reviews) - Learning Difficulty (2 reviews) - Cost (1 reviews) - Customization Difficulty (1 reviews) - Data Analysis Difficulty (1 reviews) ### 14. [eviews](https://www.g2.com/products/eviews/reviews) EViews offers academic researchers, corporations, government agencies, and students access to statistical, forecasting, and modeling tools through an object-oriented interface. **Average Rating:** 4.2/5.0 **Total Reviews:** 111 **User Satisfaction Scores:** - **Quality Control:** 7.8/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 8.2/10 (Category avg: 8.8/10) - **Survival Analysis:** 7.9/10 (Category avg: 8.4/10) - **Data Sampling:** 8.5/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [S&P Global](https://www.g2.com/sellers/s-p-global) - **HQ Location:** New York, NY - **Twitter:** @SPGlobal (46,886 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/2934/ (40,714 employees on LinkedIn®) - **Ownership:** NYSE: SPGI **Reviewer Demographics:** - **Top Industries:** Higher Education, Financial Services - **Company Size:** 40% Mid-Market, 40% Small-Business ### 15. [SAS/STAT](https://www.g2.com/products/sas-stat/reviews) SAS/STAT includes exact techniques for small data sets, high-performance statistical modeling tools for large data tasks and modern methods for analyzing data with missing values. **Average Rating:** 4.2/5.0 **Total Reviews:** 55 **User Satisfaction Scores:** - **Quality Control:** 9.0/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 7.6/10 (Category avg: 8.8/10) - **Survival Analysis:** 9.1/10 (Category avg: 8.4/10) - **Data Sampling:** 9.0/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [SAS Institute Inc.](https://www.g2.com/sellers/sas-institute-inc-df6dde22-a5e5-4913-8b21-4fa0c6c5c7c2) - **Year Founded:** 1976 - **HQ Location:** Cary, NC - **Twitter:** @SASsoftware (60,957 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1491/ (18,238 employees on LinkedIn®) - **Phone:** 1-800-727-0025 **Reviewer Demographics:** - **Top Industries:** Research, Higher Education - **Company Size:** 50% Enterprise, 30% Mid-Market #### Pros & Cons **Cons:** - Learning Curve (1 reviews) ### 16. [Spotfire Analytics](https://www.g2.com/products/spotfire-analytics/reviews) Spotfire® is a visual data science platform designed to help organizations address complex, industry-specific challenges by effectively utilizing data. This solution offers a range of flexible packaging options tailored to meet the diverse needs of teams at various stages of their visual data science journey. Turn raw data into real-time decisions with powerful, interactive visual analytics with Spotfire® Analytics. Spotfire Analytics is designed for business agility, enabling every user to explore data visually, uncover patterns quickly, and make confident, data-driven decisions without writing a single line of code. As a self-service visual data science solution, it empowers teams across roles and departments to gain fast, actionable insights that drive impact. With its no-code interactive dashboards and rich visual exploration capabilities, Spotfire Analytics connects natively to hundreds of cloud, on-premises, and real-time data sources. Built-in geoanalytics extend the power of analysis with multi-layer mapping and seamless integration of spatial data, while data wrangling and transformation can be performed directly within the visual interface, making it easy to clean, shape, and blend data as you analyze. AI-assisted recommendations and anomaly detection help uncover hidden patterns, suggest the most meaningful visualizations, and accelerate the path to discovery. Customizable visualizations, workflows, and an intuitive interface ensure that insights are not only easier to create but also easier to share. With seamless collaboration features, Spotfire Analytics enables teams to work together, align on insights, and act decisively. Whether the goal is to analyze trends, detect anomalies, or unlock location-based intelligence, Spotfire Analytics delivers the speed, flexibility, and depth needed to make smarter decisions with confidence. Explore and understand your data visually, uncover hidden insights, and build powerful analytics applications - all without writing a single line of code. Spotfire Analytics combines advanced interactive visualizations and intuitive data wrangling in one environment. Connect to hundreds of data sources, from files to real-time streaming data, and transform messy data directly within your visuals. Built-in AI recommendations help you find patterns, anomalies, and trends faster. With flexible visualizations, spatial analytics, and custom applications, anyone can turn raw data into actionable insights in minutes. Designed for business agility, Spotfire Analytics empowers every user to explore, analyze, and share results confidently - turning questions into decisions. Best for: Analysts, data-savvy professionals, and teams looking to explore and share data visually with maximum flexibility. **Average Rating:** 4.2/5.0 **Total Reviews:** 328 **User Satisfaction Scores:** - **Quality Control:** 6.3/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 8.4/10 (Category avg: 8.8/10) - **Survival Analysis:** 10.0/10 (Category avg: 8.4/10) - **Data Sampling:** 8.8/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [Spotfire](https://www.g2.com/sellers/spotfire-2d87c926-94f3-47ce-8a5d-44d930d7c744) - **HQ Location:** N/A - **LinkedIn® Page:** https://www.linkedin.com/company/spotfire/ (103 employees on LinkedIn®) **Reviewer Demographics:** - **Who Uses This:** Student, Manager - **Top Industries:** Oil & Energy, Information Technology and Services - **Company Size:** 52% Enterprise, 26% Mid-Market #### Pros & Cons **Pros:** - Data Visualization (15 reviews) - Ease of Use (15 reviews) - Insights (11 reviews) - Easy Integrations (10 reviews) - Features (10 reviews) **Cons:** - Learning Curve (9 reviews) - Learning Difficulty (7 reviews) - Expensive (5 reviews) - Steep Learning Curve (4 reviews) - Complexity (3 reviews) ### 17. [QI Macros SPC Add-in for Excel](https://www.g2.com/products/qi-macros-spc-add-in-for-excel/reviews) Affordable, easy to use add-in for Excel that creates Control Charts, Histograms, Pareto Charts, and more. Your data is already in Excel, shouldn't your SPC software be there too? QI Macros is an all-in-one toolkit used by quality and process improvement professionals for more than 20 years. In addition to drawing charts you can run Statistical Tests, create Fishbone Diagrams and Value Stream Maps, and perform complex analysis like Gage R&R and DOE. You'll save time and look like an expert! **Average Rating:** 4.5/5.0 **Total Reviews:** 28 **User Satisfaction Scores:** - **Quality Control:** 8.5/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 9.1/10 (Category avg: 8.8/10) - **Survival Analysis:** 8.4/10 (Category avg: 8.4/10) - **Data Sampling:** 8.7/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [KnowWare International](https://www.g2.com/sellers/knowware-international) - **Year Founded:** 2000 - **HQ Location:** Denver, Colorado - **LinkedIn® Page:** https://www.linkedin.com/company/knowware-international/ (3 employees on LinkedIn®) **Reviewer Demographics:** - **Top Industries:** Accounting - **Company Size:** 61% Small-Business, 29% Mid-Market ### 18. [Stata](https://www.g2.com/products/stata/reviews) The complete statistical software for data science. Stata delivers everything you need for reproducible data analysis—powerful statistics, visualization, data manipulation, and automated reporting—all in one intuitive platform. **Average Rating:** 4.3/5.0 **Total Reviews:** 162 **User Satisfaction Scores:** - **Quality Control:** 8.5/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 8.3/10 (Category avg: 8.8/10) - **Survival Analysis:** 8.7/10 (Category avg: 8.4/10) - **Data Sampling:** 8.9/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [StataCorp](https://www.g2.com/sellers/statacorp) - **Year Founded:** 1985 - **HQ Location:** College Station, TX - **Twitter:** @Stata (32,348 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/575050/ (135 employees on LinkedIn®) **Reviewer Demographics:** - **Who Uses This:** Analyst, Research Assistant - **Top Industries:** Higher Education, Research - **Company Size:** 42% Enterprise, 31% Mid-Market #### Pros & Cons **Pros:** - Coding Simplification (2 reviews) - Analytics Advancement (1 reviews) - Big Data Handling (1 reviews) - Data Management (1 reviews) - Ease of Installation (1 reviews) **Cons:** - Memory Usage (1 reviews) - Poor Customer Support (1 reviews) - Poor Graphics (1 reviews) ### 19. [Grapher](https://www.g2.com/products/grapher/reviews) Grapher™ is a full-function graphing application for scientists, engineers, and business professionals. With over 80 unique graph types, data is quickly transformed into knowledge. Virtually every aspect of the graph is customizable. Enhance your graph with legends, titles and labels, summation plots, graph magnifiers, and statistical reports. Grapher is used extensively by those who care deeply about the visual quality of their final plot. **Average Rating:** 4.5/5.0 **Total Reviews:** 113 **User Satisfaction Scores:** - **Quality Control:** 8.3/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 8.8/10) - **Survival Analysis:** 8.3/10 (Category avg: 8.4/10) - **Data Sampling:** 7.5/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [Golden Software](https://www.g2.com/sellers/golden-software-617368ba-9788-4952-a993-5ff6ea2becfd) - **Year Founded:** 1983 - **HQ Location:** Golden, CO - **Twitter:** @GoldenSoftware1 (783 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/2011794/ (34 employees on LinkedIn®) **Reviewer Demographics:** - **Top Industries:** Research, Environmental Services - **Company Size:** 39% Enterprise, 33% Mid-Market ### 20. [SAS Enterprise Miner](https://www.g2.com/products/sas-enterprise-miner/reviews) SAS Enterprise Miner is a comprehensive data mining and predictive analytics software designed to streamline the process of developing descriptive and predictive models. It enables users to analyze vast amounts of data efficiently, uncovering patterns and relationships that inform better decision-making. With an intuitive graphical user interface, SAS Enterprise Miner facilitates the entire data mining process, from data preparation to model assessment, making advanced analytics accessible to both technical and non-technical users. Key Features and Functionality: - User-Friendly Interface: An interactive GUI allows users to build process flow diagrams, simplifying the modeling process. - Advanced Data Preparation: Tools for handling missing values, filtering outliers, and performing data transformations enhance data quality. - Diverse Modeling Techniques: Supports a wide range of algorithms, including decision trees, neural networks, and regression models, catering to various analytical needs. - Open Source Integration: Seamless integration with R enables users to perform data transformations and model training within the platform. - High-Performance Capabilities: Incorporates high-performance data mining nodes to boost processing efficiency. - Automated Scoring: Generates score code in multiple languages (SAS, C, Java, PMML) for deployment across various environments. - Model Comparison and Management: Features for comparing multiple models using lift curves and statistical diagnostics to identify the best-performing models. Primary Value and Solutions Provided: SAS Enterprise Miner empowers organizations to harness the full potential of their data by providing a robust platform for developing accurate predictive models. It addresses challenges such as fraud detection, risk minimization, resource demand forecasting, and customer attrition reduction. By automating and simplifying complex data mining tasks, it enables users to make informed, data-driven decisions, ultimately enhancing operational efficiency and competitive advantage. **Average Rating:** 4.2/5.0 **Total Reviews:** 184 **User Satisfaction Scores:** - **Quality Control:** 7.8/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 8.3/10 (Category avg: 8.8/10) - **Survival Analysis:** 8.1/10 (Category avg: 8.4/10) - **Data Sampling:** 7.2/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [SAS Institute Inc.](https://www.g2.com/sellers/sas-institute-inc-df6dde22-a5e5-4913-8b21-4fa0c6c5c7c2) - **Year Founded:** 1976 - **HQ Location:** Cary, NC - **Twitter:** @SASsoftware (60,957 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1491/ (18,238 employees on LinkedIn®) - **Phone:** 1-800-727-0025 **Reviewer Demographics:** - **Top Industries:** Higher Education, Information Technology and Services - **Company Size:** 59% Enterprise, 29% Mid-Market #### Pros & Cons **Pros:** - Ease of Installation (1 reviews) - Ease of Use (1 reviews) - Statistical Analysis (1 reviews) **Cons:** - Learning Curve (1 reviews) - Not User-Friendly (1 reviews) - Steep Learning Curve (1 reviews) ### 21. [BlueSky Statistics](https://www.g2.com/products/bluesky-statistics/reviews) Fully featured Statistics application and development framework built on the open source R project Provides familiar powerful user interface available in mainstream statistical applications like SPSS, SAS etc. Unlocks the power of R for the analyst community by providing a rich GUI and output for several popular statistics, data mining, data manipulation and graphics commands, all out of the box... Provide a rich development framework for developing and deploying new statistical modules, applications or functions with rich graphical user interfaces and output, all through intuitive drag and drop user interfaces (No programming required). **Average Rating:** 4.5/5.0 **Total Reviews:** 13 **User Satisfaction Scores:** - **Quality Control:** 9.0/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 9.2/10 (Category avg: 8.8/10) - **Survival Analysis:** 9.6/10 (Category avg: 8.4/10) - **Data Sampling:** 8.8/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [BlueSky Statistics](https://www.g2.com/sellers/bluesky-statistics) - **Year Founded:** 2014 - **HQ Location:** Chicago, Illinois - **Twitter:** @BlueSky_Stat (45 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/blueskystatistics/ (1 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 62% Small-Business, 31% Mid-Market ### 22. [G*Power](https://www.g2.com/products/g-power/reviews) G\*Power is a tool to compute statistical power analyses for many different t tests, F tests, χ2 tests, z tests and some exact tests. G\*Power can also be used to compute effect sizes and to display graphically the results of power analyses. **Average Rating:** 4.7/5.0 **Total Reviews:** 10 **User Satisfaction Scores:** - **Quality Control:** 9.2/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 9.4/10 (Category avg: 8.8/10) - **Survival Analysis:** 8.3/10 (Category avg: 8.4/10) - **Data Sampling:** 8.9/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [University of D‚Äö√†o¬¨‚à´sseldorf](https://www.g2.com/sellers/university-of-d-ao-o-a-sseldorf) - **Year Founded:** 1965 - **HQ Location:** Düsseldorf, DE - **Twitter:** @HHU_de (8,193 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/15094013/ (3,844 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 40% Enterprise, 40% Small-Business ### 23. [nQuery](https://www.g2.com/products/nquery-sample-size-software/reviews) Design efficient, informative and ethical adaptive trials with nQuery. Use nQuery to minimize costs, reduce risks and boost efficiency in large-scale studies **Average Rating:** 4.8/5.0 **Total Reviews:** 11 **User Satisfaction Scores:** - **Quality Control:** 10.0/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 10.0/10 (Category avg: 8.8/10) - **Survival Analysis:** 10.0/10 (Category avg: 8.4/10) - **Data Sampling:** 8.3/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [StatSols](https://www.g2.com/sellers/statsols) - **Year Founded:** 1984 - **HQ Location:** Cork, IE - **Twitter:** @Statsols (955 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/206909/ (12 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 45% Mid-Market, 27% Enterprise ### 24. [ROOT](https://www.g2.com/products/root/reviews) ROOT is a modular scientific software framework that provides all the functionalities needed to deal with big data processing, statistical analysis, visualisation and storage, it is mainly written in C++ but integrated with other languages such as Python and R. **Average Rating:** 4.3/5.0 **Total Reviews:** 18 **User Satisfaction Scores:** - **Quality Control:** 8.2/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 8.9/10 (Category avg: 8.8/10) - **Survival Analysis:** 7.3/10 (Category avg: 8.4/10) - **Data Sampling:** 8.3/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [CERN](https://www.g2.com/sellers/cern) - **HQ Location:** N/A - **Twitter:** @ROOT_Project (844 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/No-Linkedin-Presence-Added-Intentionally-By-DataOps (1 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 56% Small-Business, 33% Mid-Market ### 25. [Altair SLC](https://www.g2.com/products/altair-slc/reviews) Are SAS Language Programs Mission Critical for Your Business? Many organizations have developed SAS language programs over the years that are vital to their operations. IT and analytics managers are also under pressure to reduce costs and find alternatives for handling their SAS language requirements. Altair SLC (formerly WPS Analytics) runs programs written with SAS language syntax without translation and without licensing other third-party products. Altair SLC is built to handle high levels of throughput and reduces clients’ capital costs and operating expenses. Multi Language, Multi-Platform Solution Altair SLC handles programs, workflows, and models that combine the SAS language and the SQL, Python, and R languages. Its built-in SAS language compiler runs SQL and SAS language code and utilizes Python and R compilers to run Python and R code and exchange Pandas and R data frames. Working on IBM mainframes and in the cloud, as well as on servers and workstations running a host of operating systems, Altair SLC supports remote job submissions and can exchange data between mainframe, cloud, and on-premises installations. Feature-Rich SAS Language Support In addition, Altair SLC doesn’t require any third-party middleware to process applications that contain the SAS language. Altair SLC’s built-in SAS language compiler supports SAS language and macro syntax, and includes procedure support for statistics, time series analytics, operational research, machine learning, matrix manipulation, graphing, and output delivery. Additionally, users can use Altair SLC in batch or standalone mode to execute programs and models or use it with Altair Analytics WorkbenchTM, a GUI/IDE that provides both no-code (workflow) and code facilities to create, maintain, and execute programs and models and interactively explore their outputs. **Average Rating:** 4.1/5.0 **Total Reviews:** 10 **User Satisfaction Scores:** - **Quality Control:** 8.1/10 (Category avg: 8.3/10) - **Has the product been a good partner in doing business?:** 8.3/10 (Category avg: 8.8/10) - **Survival Analysis:** 7.6/10 (Category avg: 8.4/10) - **Data Sampling:** 8.5/10 (Category avg: 8.6/10) **Seller Details:** - **Seller:** [Altair](https://www.g2.com/sellers/altair-186799f5-3238-493f-b3ad-b8cac484afd7) - **Year Founded:** 1985 - **HQ Location:** Troy, MI - **LinkedIn® Page:** https://www.linkedin.com/company/8323/ (3,169 employees on LinkedIn®) - **Ownership:** NASDAQ:ALTR - **Total Revenue (USD mm):** $458 **Reviewer Demographics:** - **Company Size:** 70% Small-Business, 20% Mid-Market #### Pros & Cons **Pros:** - Big Data Handling (1 reviews) - Customer Support (1 reviews) - Data Import (1 reviews) - Ease of Installation (1 reviews) - Ease of Use (1 reviews) **Cons:** - Complexity (2 reviews) - Limited Features (2 reviews) - Inadequate Help Resources (1 reviews) - Learning Curve (1 reviews) - Not User-Friendly (1 reviews) ## Parent Category [Analytics Tools & Software](https://www.g2.com/categories/analytics-tools-software) ## Related Categories - [Data Visualization Tools](https://www.g2.com/categories/data-visualization-tools) - [Predictive Analytics Software](https://www.g2.com/categories/predictive-analytics) - [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms) --- ## Buyer Guide ### What You Should Know About Statistical Analysis Software ### What is Statistical Analysis Software? Statistical analytics tools inform data-driven decisions, whether that be in a research or business context. Enterprises have started to recognize the importance of accessing and combining all business-critical data to get a better understanding of how a company performs. Connecting disparate systems to make data consumable is a complex process, but once done, businesses are enabled to utilize statistical analytics solutions along with other data analysis techniques. This helps them visualize and interpret the data in an easily digestible manner. A business cannot transform into a digitally native enterprise until it uses its data to make intelligent decisions. These data-driven decisions provide an important edge and help separate a business from its competitors.  Medium and large companies are facing unprecedented challenges when managing and analyzing data. Some of these challenges are the exponential growth of the volume of enterprise data and its increasing complexity caused by new technologies like social media and the internet of things (IoT). To address these challenges, companies need to gather and analyze large volumes of data, both structured and unstructured, from different sources. Companies need to find trends and patterns in historical data while identifying future opportunities and risks. They also cannot afford to spend a lot of time analyzing data which loses its relevance quickly. Advanced statistical procedures and visualization provide a robust, user-friendly, and integrated platform to understand business data and solve complex business and research problems. #### What Types of Statistical Analysis Software Exist? Statistical analysis comes in many different flavors with each type being appropriate or beneficial for different use cases. Although the methods are many, the ultimate goal of the analysis is broken into three types: descriptive, prescriptive, and predictive. Descriptive analysis simply looks at the data as it is, but does not refer to or recommend any future outcome. Prescriptive analysis uses historical data to recommend a particular outcome. Finally, predictive analysis uses historical data to predict future data or outcomes. Apart from these broad methods, statistical analysis software can perform the following types of analysis: **Regression analysis** This type of analysis allows for conducting various regression methods such as ordinary least squares (OLS), weighted least squares (WLS), or generalized linear model (GLM). **Predictive analytics** Predictive analytics mines and analyzes historical data patterns to predict future outcomes by extracting information from data sets to determine patterns and trends. Using a range of statistical analysis and algorithms, analysts use predictive analytics products to build decision models which business managers use to plan for the best possible outcome. **Survival analysis** This type of analysis allows for the evaluation of durations, events, and reliability in relation to statistical analysis. **Time series analysis** Time series analysis allows users to identify patterns within massive, continuous time series data sets to perform reporting, forecasting, and predictive analysis. **Bayesian analysis** This method of statistical inference allows one to combine prior information about a statistical parameter with evidence from information contained in a sample to guide the statistical inference process. **Decision trees** One common type of classification model is a decision tree. These models predict a number of possible outcomes based on a variety of inputs. For example, if a sales team builds $1 million in pipeline, they can close $100,000 in revenue, but if they build $10 million in pipeline, they should be able to close $1 million in revenue. ### What are the Common Features of Statistical Analysis Software? Statistical analysis tools allow users to mine and analyze structured or unstructured data. Through the process of analysis, data sets and visualizations are created from the compiled data. **Data preparation:** To analyze the data, it must be properly cleaned and should be of high quality. This preparation consists of deduplication, cleansing, and appending the data for statistical analysis. Not all analysis is achieved at the surface. Instead, robust statistical analysis tools mine data from databases and prepare it for analysis. **Data sampling:** Data sampling allows users to select samples of data for defined procedures. **Statistical modeling:** Statistical modeling involves creating a mathematical model that embodies a set of statistical assumptions concerning the creation of sample data which may be used to get a better idea about the makeup and distribution of the data. **Hypothesis testing:** Statistical analysis tools often provide hypothesis testing features to ensure the analysis is consistent with the data and correct based on predetermined factors. This helps the researcher, data scientist, or statistician evaluate the outcome based on their initial hypothesis. **Data visualization:** In addition to numerical inputs and outputs, statistical analysis software frequently allows the user to visualize results by means of graphs, charts, and reports. This not only helps the end user better understand them but also aids with communicating these results with the broader company. ### What are the Benefits of Statistical Analysis Software? Irrespective of the type of complex data manipulation or analysis being performed, statistical analysis tools enable statisticians or business professionals to find correlation, regression, analysis of variance, and more with ease. With these insights in hand, businesses can make sense of their data and make informed decisions based on it. These tools help identify duplicates and unusual cases that may arise during data cleaning and data curation and get detailed data analysis reports. **Manage large volumes of data:** Statistical analysis software gives one the ability to easily prepare, blend, and analyze company data using a repeatable workflow, then deploy and share analytics at scale for deeper insights. **Gain insight into company data:** Through data mining and statistical analysis, especially when coupled with other technology such as machine learning, data professionals are able to gain insights into data. **Better understand potential outcomes and scenarios:** With statistical analysis, especially of the predictive variety, businesses better understand how different variables will affect them and are able to plan accordingly. ### Who Uses Statistical Analysis Software? **Data analysts:** Depending on the complexity of the software, it is likely that analysts will be required. They can help set up the requisite queries, dashboards, and notebooks for other employees and teams. They can create complex queries inside the platforms to gather a deeper understanding of business-critical data. **Consultants:** Businesses do not always have the luxury to build, develop, and optimize their own analytics solutions. Some businesses opt to employ external consultants, such as [business intelligence (BI) consulting providers](https://www.g2.com/categories/business-intelligence-bi-consulting). These providers seek to understand a business and its goals, interpret data, and offer advice to ensure goals are met. BI consultants frequently have industry-specific knowledge alongside their technical backgrounds, with experience in healthcare, business, and other fields.  ### What are the Alternatives to Statistical Analysis Software? Alternatives to statistical analysis software can replace this type of software, either partially or completely: [Analytics platforms](https://www.g2.com/categories/analytics-platforms) **:** Analytics platforms might include statistical analysis, but are broader-focused tools that facilitate the following five elements: data preparation, data modeling, data blending, data visualization, and insights delivery. [Big data analytics software](https://www.g2.com/categories/big-data-analytics) **:** Big data analytics software connects to Hadoop or proprietary Hadoop distributions to better understand structured and unstructured data. These same data sources may be important for data scientists who are tasked with building predictive models. [Log analysis software](https://www.g2.com/categories/log-analysis): Businesses that are focused on log data might benefit from deploying log analysis software, which is used to analyze log data from applications and systems. It should be kept in mind that this software is much more limited in terms of data types and data sources to which it can be connected to. However, since log analysis software focuses on logs, it frequently provides more granular details around log-related data. [Stream analytics software](https://www.g2.com/categories/stream-analytics) **:** When one is looking for tools specifically geared toward analyzing data in real time, stream analytics software is a go-to solution. These tools help users analyze data in transfer through APIs, between applications, and more. This software can be helpful with IoT data, which one frequently wants to analyze in real time. [Predictive analytics software](https://www.g2.com/categories/predictive-analytics): Broad-purpose statistical analysis software allows businesses to conduct various forms of analysis, such as prescriptive, descriptive, and predictive. Businesses that are focused on looking at their past and present data to predict future outcomes can use predictive analytics software for a more fine-tuned solution.  [Text analysis software](https://www.g2.com/categories/text-analysis): Statistical analysis software is focused on structured or numerical data, allowing users to drill down and dig into numbers to inform business decisions. If the user is looking to focus on unstructured or text data, text analysis solutions are the best bet. These tools help users quickly understand and pull sentiment analysis, key phrases, themes, and other insights from unstructured text data. #### Software Related to Statistical Analysis Software Related solutions that can be used together with statistical analysis software include: [Data warehouse software](https://www.g2.com/categories/data-warehouse) **:** Most companies have a large number of disparate data sources, so to best integrate all their data, they implement a data warehouse. Data warehouses can house data from multiple databases and business applications, which allows BI and analytics tools to pull all company data from a single repository. This organization is critical to the quality of the data that is ingested by analytics software. [Data preparation software](https://www.g2.com/categories/data-preparation) **:** A key solution necessary for easy data analysis is a data preparation tool and other related data management tools. These solutions allow users to discover, combine, clean, and enrich data for simple analysis. Data preparation tools are often used by IT teams or data analysts tasked with using BI tools. Some BI platforms offer data preparation features, but businesses with a wide range of data sources often opt for a dedicated preparation tool. [Machine learning software](https://www.g2.com/categories/machine-learning) **:** Machine learning algorithms are a key component of building effective statistical models. Many machine learning algorithms are built to provide recommendations or suggestions which is particularly relevant for predictive analytics. ### Challenges with Statistical Analysis Software Software solutions can come with their own set of challenges.  **Need for skilled employees:** Statistical analysis software is not necessarily simple. Often, these tools require a dedicated administrator to help implement the solution and assist others with adoption. However, there is a shortage of skilled data scientists and analysts that are equipped to set up such solutions. Additionally, those same data scientists will be tasked with deriving actionable insights from within the data.  Without people skilled in these areas, businesses cannot effectively leverage the tools or their data. Even the self-service tools, which are to be used by the average business user, require someone to help deploy them. Companies can turn to vendor support teams or third-party consultants to assist if they are unable to bring someone in house. **Data organization:** To get the most of analytics solutions, that data needs to be organized. This means that databases should be set up correctly and integrated properly. This may require building a data warehouse, which can store data from a variety of applications and databases in a central location.  Businesses may need to purchase a dedicated [data preparation software](https://www.g2.com/categories/data-preparation) as well to ensure that data is joined and is clean for the analytics solution to consume in the right way. In the context of big data, a company might want to specifically consider big data processing and distribution software. This often requires a skilled data analyst, IT employee, or an outside consultant to help ensure data quality is at its finest for easy analysis. **User adoption:** It is not always easy to transform a business into a data-driven company. Particularly at more established companies that have done things the same way for years, it is not simple to force analytics tools upon employees, especially if there are ways for them to avoid it. If there are other options, such as spreadsheets or existing tools that employees can use instead of analytics software, they will most likely go that route. However, if managers and leaders ensure that analytics tools are a necessity in an employee’s day to day, then adoption rates will increase. ### Which Companies Should Buy Statistical Analysis Software? In the digital age, data is ubiquitous. Whether it is higher education or the healthcare industry, it is likely that a lot of data is involved. Statistical analysis software tools are typically used by data scientists and mathematicians, but it provides industry-specific features. These may be features tailored to scientific research, cost modeling, or health science. **Higher education:** Users from the higher education industry use statistical analysis tools to analyze data, obtain insights quickly, and find relevant trends in data. **Market research firms:** Researchers turn to statistical analysis to solve tough research problems. They are able to use these tools to dig into their research findings and find historical trends. With statistical analysis software, market researchers are enabled to handle a large volume of data in multiple formats. **Health care** : For health care professionals, time isn’t just money—it also means the difference between life and death. These workers look to statistical analysis tools to better understand health-related data and to improve efficiencies in hospitals, manage and contain diseases, and much more. ### How to Buy Statistical Analysis Software #### Requirements Gathering (RFI/RFP) for Statistical Analysis Software If a company is just starting out on their analytics journey, g2.com can help in selecting the best software for the particular company and use case. Since the particular solution might vary based on company size and industry, G2 is a great place to sort and filter reviews based on these criteria, along with many more. The variety, volume, and velocity of data are vast. Therefore, users should think about how the particular solution fits their particular needs, as well as their future needs as they accumulate more data.  To find the right solution, buyers should determine pain points and jot them down. These should be used to help create a checklist of criteria. Additionally, the buyer must determine the number of employees who will need to use this software, as this drives the number of licenses they are likely to buy. Taking a holistic overview of the business and identifying pain points can help the team springboard into creating a checklist of criteria. The checklist serves as a detailed guide that includes both necessary and nice-to-have features including budget, features, number of users, integrations, security requirements, cloud or on-premises solutions, and more. Depending on the scope of the deployment, it might be helpful to produce a request for information (RFI), a one-page list with a few bullet points describing what is needed from a statistical analysis software. #### Compare Statistical Analysis Software Products **Create a long list** From meeting the business functionality needs to implementation, vendor evaluations are an essential part of the software buying process. For ease of comparison after all demos are complete, it helps to prepare a consistent list of questions regarding specific needs and concerns to ask each vendor. **Create a short list** From the long list of vendors, it is helpful to narrow down the list of vendors and come up with a shorter list of contenders, preferably no more than three to five. With this list in hand, businesses can produce a matrix to compare the features and pricing of the various solutions. **Conduct demos** To ensure the comparison is thoroughgoing, the user should demo each solution on the shortlist with the same use case and data sets. This will allow the business to evaluate like for like and see how each vendor stacks up against the competition.  #### Selection of Statistical Analysis Software **Choose a selection team** As statistical analysis software is all about the data, the user must make sure that the selection process is data driven as well. The selection team should compare notes and facts and figures which they noted during the process, such as time to insight, number of visualizations, and availability of advanced analytics capabilities. **Negotiation** Just because something is written on a company’s pricing page, does not mean it is not negotiable (although some companies will not budge). It is imperative to open up a conversation regarding pricing and licensing. For example, the vendor may be willing to give a discount for multi-year contracts or for recommending the product to others. **Final decision** After this stage, and before going all in, it is recommended to roll out a test run or pilot program to test adoption with a small sample size of users. If the tool is well used and well received, the buyer can be confident that the selection was correct. If not, it might be time to go back to the drawing board. ### What Does Statistical Analysis Software Cost? Businesses decide to deploy statistical analysis software with the goal of deriving some degree of a return on investment (ROI). #### Return on Investment (ROI) As they are looking to recoup their losses that they spent on the software, it is critical to understand the costs associated with it. This software is typically billed per user, which is sometimes tiered depending on the company size. More users will typically translate into more licenses, which means more money. Users must consider how much is spent and compare that to what is gained, both in terms of efficiency as well as revenue. Therefore, businesses can compare processes between pre- and post-deployment of the software to better understand how processes have been improved and how much time has been saved. They can even produce a case study (either for internal or external purposes) to demonstrate the gains they have seen from their use of the statistical analysis tool. ### Implementation of Statistical Analysis Software **How is Statistical Analysis Software Implemented?** Implementation differs drastically depending on the complexity and scale of the data. In organizations with vast amounts of data in disparate sources (e.g., applications, databases, etc.), it is often wise to utilize an external party, whether that be an implementation specialist from the vendor or a third-party consultancy. With vast experience, they can help businesses understand how to connect and consolidate their data sources and how to use the software efficiently and effectively. **Who is Responsible for Statistical Analysis Software Implementation?** It may require a lot of people, or many teams, to properly deploy an analytics platform. This is because data can cut across teams and functions. As a result, it is rare that one person or even one team has a full understanding of all of a company’s data assets. With a cross-functional team in place, a business can piece together its data and begin the journey of analytics, starting with proper data preparation and management. ### Statistical Analysis Software Trends **Self service** As with other types of analytics tools (such as analytics platforms), there is an increasing trend for software to be of the self-service nature. This means that non professionals should be able to use the tool easily with little to no IT support for setting it up. With drag-and-drop interfaces or highly customizable setups, average business users are being empowered by statistical analysis capabilities. **Augmented analytics** Artificial intelligence and machine learning are making inroads across most industries and business use cases, with statistics being no exception. With machine learning powering statistical analysis, users are able to discover data, determine the best type of analysis to deploy for a particular data set or problem, and more. With augmented analytics, analysts can get a better understanding of their data, allowing them to drill in and dive deeper into trends and patterns. For example, the software might alert the user to an anomaly in the data which they can look into in order to rectify the issue or inform relevant individuals about it.