# Best Predictive Analytics Tools and Software - Page 12 *By [Bijou Barry](https://research.g2.com/insights/author/bijou-barry)* Predictive analytics software 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 tools to build decision models, which business managers can use to plan for the best possible outcome. Analysts, business users, data scientists, and developers all use predictive analytics solutions to better understand customers, products, and partners and to identify potential risks and opportunities for a company. Predictive analytics platforms enable organizations to use big data (both stored and real-time) to move from a historical view to a forward-looking perspective of the customer. These tools and techniques can be deployed both on premise (usually for enterprise users) and in the cloud. While the majority of predictive analytics software is proprietary, versions that are based on open-source technology do exist. Recent trends in software for predictive analytics show its integration with [business intelligence platforms](https://www.g2.com/categories/business-intelligence-platforms), [ERP systems](https://www.g2.com/categories/erp-systems), or other [digital analytics software](https://www.g2.com/categories/digital-analytics). To qualify for inclusion in the Predictive Analytics category, a product must: - Mine and analyze structured and/or unstructured data - Create datasets and/or data visualizations from compiled data - Create predictive models to forecast future probabilities - Adapt to change and revisions - Allow import and export from office suites or other data-collecting channels ## How Many Predictive Analytics Software Products Does G2 Track? **Total Products under this Category:** 287 ### Category Stats (May 2026) - **Average Rating**: 4.45/5 (↑0.01 vs Apr 2026) - **New Reviews This Quarter**: 107 - **Buyer Segments**: Enterprise 35% │ Small-Business 34% │ Mid-Market 31% - **Top Trending Product**: SAS Visual Forecasting (+0.049) *Last updated: May 18, 2026* ## How Does G2 Rank Predictive Analytics Software Products? **Why You Can Trust G2's Software Rankings:** - 30 Analysts and Data Experts - 30,200+ Authentic Reviews - 287+ Products - Unbiased Rankings G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category. ## Which Predictive Analytics Software Is Best for Your Use Case? - **Leader:** [Tableau](https://www.g2.com/products/tableau/reviews) - **Highest Performer:** [Nixtla](https://www.g2.com/products/nixtla/reviews) - **Easiest to Use:** [Nixtla](https://www.g2.com/products/nixtla/reviews) - **Top Trending:** [Tableau](https://www.g2.com/products/tableau/reviews) - **Best Free Software:** [Altair AI Studio](https://www.g2.com/products/rapidminer-studio/reviews) --- **Sponsored** ### Alteryx Alteryx, through it's Alteryx One platform, helps enterprises transform complex, disconnected data into a clean, AI-ready state. Whether you’re creating financial forecasts, analyzing supplier performance, segmenting customer data, analyzing employee retention, or building competitive AI applications from your proprietary data, Alteryx One makes it easy to cleanse, blend, and analyze data to unlock the unique insights that drive impactful decisions. AI-Guided Analytics Alteryx automates and simplifies every stage of data preparation and analysis, from validation and enrichment to predictive analytics and automated insights. Incorporate generative AI directly into your workflows to streamline complex data tasks and generate insights faster. Unmatched flexibility, whether you prefer code-free workflows, natural language commands, or low-code options, Alteryx adapts to your needs. Trusted. Secure. Enterprise-Ready. Alteryx is trusted by over half of the Global 2000 and 19 of the top 20 global banks. With built-in automation, governance, and security, your workflows can scale and maintain compliance while delivering consistent results. And it doesn’t matter if your systems are on-premises, hybrid, or in the cloud; Alteryx fits effortlessly into your infrastructure. Easy to Use. Deeply Connected. What truly sets Alteryx apart is our focus on efficiency and ease of use for analysts and our active community of 700,000 Alteryx users to support you at every step of your journey. With seamless integration to data everywhere including platforms like Databricks, Snowflake, AWS, Google, SAP, and Salesforce, our platform helps unify siloed data and accelerate getting to insights. Visit Alteryx.com for more information, and to start your free trial. [Visit website](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=ppc&secure%5Bad_slot%5D=category_product_list&secure%5Bcategory_id%5D=499&secure%5Bdisplayable_resource_id%5D=499&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=499&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=989&secure%5Bresource_id%5D=499&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fpredictive-analytics%3Fpage%3D14&secure%5Btoken%5D=965c6bfa8069caecd0a18a12e717fd55be7c06234116d3223ef8f49e20befcc3&secure%5Burl%5D=https%3A%2F%2Fwww.alteryx.com%2Ftrial%3Futm_source%3Dg2%26utm_medium%3Dreviewsite%26utm_campaign%3DFY25_Global_AllRegions_AlwaysOn_AllPersonas_IndustryAgnostic%26utm_content%3Dg2_freetrial&secure%5Burl_type%5D=free_trial) --- ## What Are the Top-Rated Predictive Analytics Software Products in 2026? ### 1. [Symec Connected Information](https://www.g2.com/products/symec-connected-information/reviews) Symec Technologies offer a wide range of Hardware, Services and Support solutions for your business critical mobile technology **Who Is the Company Behind Symec Connected Information?** - **Seller:** [Symec Technologies](https://www.g2.com/sellers/symec-technologies) - **Year Founded:** 2007 - **HQ Location:** Bristol, GB - **Twitter:** @SymecTech (396 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1130509 (73 employees on LinkedIn®) ### 2. [The Cognite AI & Data Platform](https://www.g2.com/products/the-cognite-ai-data-platform/reviews) The Cognite AI and Data Platform™ is a sophisticated Industrial DataOps solution specifically designed for asset-intensive industries seeking to harness the power of their operational and engineering data. Founded in 2016 and based in Tempe, Arizona, Cognite aims to facilitate the transformation of complex data environments into actionable insights that drive efficiency and innovation across various sectors. This cloud-native platform excels in ingesting and contextualizing data from a multitude of sources, including Information Technology (IT), Operational Technology (OT), and engineering systems. By creating a unified industrial knowledge graph, the Cognite AI and Data Platform integrates data from historians, Enterprise Resource Planning (ERP) systems, Computerized Maintenance Management Systems (CMMS), and even 3D models. This comprehensive approach allows organizations to standardize their data models and utilize robust APIs, enabling secure workspaces that support advanced analytics, interactive dashboards, and AI-driven applications. Targeted primarily at industries that rely heavily on operational data, such as manufacturing, energy, and utilities, the Cognite AI and Data Platform addresses specific use cases that enhance productivity and operational efficiency. For instance, organizations can leverage the platform for production optimization, where real-time data insights lead to improved throughput and reduced operational bottlenecks. Additionally, the platform supports predictive maintenance initiatives, allowing companies to anticipate equipment failures before they occur, thereby minimizing downtime and associated costs. Key features of the Cognite AI and Data Platform include its ability to transform fragmented data into a trusted and contextual foundation, which is crucial for making informed decisions. By providing a centralized repository of data, users gain full ownership and control over their information, facilitating compliance and security. Moreover, the platform’s scalability enables organizations to implement AI initiatives that can evolve with their operational needs, ensuring that they remain competitive in a rapidly changing industrial landscape. Overall, the Cognite AI and Data Platform stands out in the DataOps category by offering a comprehensive solution that not only integrates disparate data sources but also empowers organizations to unlock the full potential of their industrial data. Through its focus on contextualization and user-friendly interfaces, it provides significant value to companies looking to enhance their operational capabilities and drive long-term growth. **Who Is the Company Behind The Cognite AI & Data Platform?** - **Seller:** [Cognite](https://www.g2.com/sellers/cognite) - **Company Website:** https://www.cognite.com/en/ - **Year Founded:** 2016 - **HQ Location:** Tempe, Arizona, United States - **LinkedIn® Page:** https://www.linkedin.com/company/cognitedata (760 employees on LinkedIn®) ### 3. [Transorg Analytics](https://www.g2.com/products/transorg-analytics/reviews) TransOrg Analytics, legally known as Transorg Solutions & Services Private Limited, is a leading data science and AI consulting company headquartered in Gurugram, India. Established in 2009 by industry veteran Naveen Jain, the company delivers advanced analytics, machine learning, and big data solutions to help enterprises make smarter, data-driven decisions. With a team of experienced data scientists, engineers, and domain experts, TransOrg specializes in predictive analytics, customer analytics, risk modeling, big data engineering, and business intelligence. The company has worked with top players across banking, retail, telecom, healthcare, and manufacturing sectors, enabling them to unlock insights, optimize operations, and drive digital transformation. TransOrg combines deep industry knowledge with technological expertise to create tailored AI-driven solutions that deliver measurable business outcomes. Whether you're modernizing your data infrastructure, deploying machine learning models, or scaling your analytics capabilities — TransOrg is your trusted analytics partner. **Who Is the Company Behind Transorg Analytics?** - **Seller:** [Transorg Analytics](https://www.g2.com/sellers/transorg-analytics-a0ba0610-0f02-48ee-bd0a-bf4465113207) - **HQ Location:** N/A - **LinkedIn® Page:** https://www.linkedin.com/company/transorg-solutions-&-services/people/ (116 employees on LinkedIn®) ### 4. [Twinql](https://www.g2.com/products/twinql/reviews) Twinql is an AI-powered data analysis platform designed for data-driven teams. It allows users to integrate multiple data sources, visualize analytics via charts and visuals, and generate contextual insights and forecasts all from a conversational interface. The platform emphasizes enterprise-grade data security ensuring that user data is encrypted and never used to train AI models and supports use cases across finance, marketing, product metrics, and market research. **Who Is the Company Behind Twinql?** - **Seller:** [Conscious Technologies](https://www.g2.com/sellers/conscious-technologies) - **Year Founded:** 2024 - **HQ Location:** San Francisco, US - **LinkedIn® Page:** https://www.linkedin.com/company/twinql-ai/ (2 employees on LinkedIn®) ### 5. [Unified Call Accounting](https://www.g2.com/products/unified-call-accounting/reviews) Traditional reporting technologies only go one step beyond providing access to raw data straight off the network devices that output it. Even advanced systems that provide historical trending are siloed, providing limited visibility to a single UC technology and in many cases for a single manufacturer. Predictive UC Analytics provides significantly more. **Who Is the Company Behind Unified Call Accounting?** - **Seller:** [TeleMate.Net](https://www.g2.com/sellers/telemate-net) - **Year Founded:** 1986 - **HQ Location:** Peachtree Corners, US - **LinkedIn® Page:** https://www.linkedin.com/company/telemate-net-software/ (24 employees on LinkedIn®) ### 6. [Veritas NetInsights Console](https://www.g2.com/products/veritas-netinsights-console/reviews) Predictive Insights utilizes Artificial Intelligence (AI), and Machine Learning (ML), to deliver proactive support services that help organizations. **Who Is the Company Behind Veritas NetInsights Console?** - **Seller:** [Cohesity](https://www.g2.com/sellers/cohesity) - **Year Founded:** 2013 - **HQ Location:** San Jose, CA - **Twitter:** @Cohesity (29,286 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/3750699/ (7,721 employees on LinkedIn®) ### 7. [Vertify](https://www.g2.com/products/vertify/reviews) Grounded by the philosophy that all three key revenue teams—sales, marketing, and customer success—should be aligned by process and technology, Vertify provides business automation software that easily syncs, cleans, and curates customer data within existing revenue tech stacks. - Identify bottlenecks between teams - Unify your customer journey and team's productivity - Unlock new revenue potential - Maximize your existing RevTech ROI - Respond to customers quicker - Gain better insights, smoother lead and customer management, and better campaigns - Scale operations to achieve faster results Aligning and integrating your sales, marketing, and customer success systems means everyone can work together with the same data. Why on earth would you want to have disjointed apps and processes? You and your customers deserve better. You deserve actionable data that gives teams direction, confidence and a shared view. - Best in class UI, API, and workflow automation - Proven ability to scale - Robust governance and security - Cloud-native, flexible delivery **Average Rating:** 4.6/5.0 **Total Reviews:** 5 **How Do G2 Users Rate Vertify?** - **Has the product been a good partner in doing business?:** 9.4/10 (Category avg: 9.0/10) **Who Is the Company Behind Vertify?** - **Seller:** [Vertify](https://www.g2.com/sellers/vertify) - **Year Founded:** 2016 - **HQ Location:** Austin, US - **Twitter:** @VertifyData (119 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/vertifydata (9 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 60% Small-Business, 40% Mid-Market ### 8. [VerumAI](https://www.g2.com/products/verumai/reviews) AI-Powered affordable online on-demand consulting for SME Excellence. Enterprise-grade consulting services automated with AI. From instant answers to comprehensive strategic reports, scale your consulting needs effortlessly. **Who Is the Company Behind VerumAI?** - **Seller:** [Verum Nexus Consulting](https://www.g2.com/sellers/verum-nexus-consulting) - **HQ Location:** N/A - **LinkedIn® Page:** https://www.linkedin.com/company/No-Linkedin-Presence-Added-Intentionally-By-DataOps (1 employees on LinkedIn®) ### 9. [Vortexa](https://www.g2.com/products/vortexa/reviews) Vortexa tracks more than $1.8 trillion of waterborne energy trades per year in real-time, providing energy and shipping companies with the most complete picture of global energy flows available in the world today. Vortexa’s highly intuitive web-based app and programmatic API/SDK interfaces help traders, analysts and charterers make high-value trading decisions with confidence when it matters the most. **Who Is the Company Behind Vortexa?** - **Seller:** [Vortexa Ltd.](https://www.g2.com/sellers/vortexa-ltd) - **Year Founded:** 2016 - **HQ Location:** London, GB - **LinkedIn® Page:** https://www.linkedin.com/company/vortexa/ (196 employees on LinkedIn®) ### 10. [X-INTELLIGENCE (Decision)](https://www.g2.com/products/x-intelligence-decision/reviews) X-INTELLIGENCE (Decision) is a core component of Intelmatix's EDIX platform, designed to unify cross-functional teams by eliminating siloed decision-making through a fully integrated suite of enterprise applications. It provides a centralized decision-making platform where data from all departments and relevant external sources are collected, stored, accessed, managed, and utilized for improved planning and decision-making. **Who Is the Company Behind X-INTELLIGENCE (Decision)?** - **Seller:** [Intelmatix](https://www.g2.com/sellers/intelmatix) - **Year Founded:** 2021 - **HQ Location:** N/A - **LinkedIn® Page:** https://www.linkedin.com/company/intelmatix (58 employees on LinkedIn®) ### 11. [Zebra Workcloud Forecasting & Analysis](https://www.g2.com/products/zebra-workcloud-forecasting-analysis/reviews) Access a library of proven algorithms designed to address use cases across forecasting, demand sensing, optimization and more. Empower transformation with no code / low code interfaces. Configure science to meaningful business value, while providing analysis tools that unify demand intelligence for easier consumption. With Workcloud Forecasting and Analysis powered by antuit.ai, you’ll receive the intelligence, insights, and innovation to drive greater value for your organization. Key benefits realized by some of our customers: - $1.5-3M in Annual Profit Increase - $250-450K Ongoing Inventory Savings Gain data-driven insights for smarter decision-making through intelligent forecasting, pricing and demand analysis to accurately understand and predict customer demand. Zebra (NASDAQ: ZBRA) provides the tools to help businesses grow with asset visibility, connected frontline workers and intelligent automation. The company operates in more than 100 countries, and our customers include over 80% of the Fortune 500. Designed for the frontline, Zebra’s award-winning portfolio includes hardware, software, and services, all backed by our 50+ years of innovation and global partner ecosystem. Learn more: https://www.zebra.com/us/en/software/workcloud-solutions/workcloud-demand-intelligence-suite/workcloud-forecasting-analysis.html **Who Is the Company Behind Zebra Workcloud Forecasting & Analysis?** - **Seller:** [Zebra Technologies](https://www.g2.com/sellers/zebra-technologies) - **Year Founded:** 1969 - **HQ Location:** Lincolnshire, IL - **Twitter:** @ZebraTechnology (32,990 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/167024/ (11,659 employees on LinkedIn®) - **Ownership:** NASDAQ:ZBRA ### 12. [Zebra Workcloud Modeling Studio](https://www.g2.com/products/zebra-workcloud-modeling-studio/reviews) Simplify AI with Zebra Workcloud Modeling Studio—a top-tier low-code/no-code machine learning platform for swift data prep to model training. Democratize data science across your enterprise Utilize pre-built algorithms designed for retail and CPG, pipelines, and end-to-end solutions. Empower AI initiatives with Zebra Workcloud Modeling Studio—an innovative, simple solution for a powerful data-driven future. Key benefits realized by some of our customers: - 3X boost in ML experimentation velocity - Up to 30% reduction in time and cost Gain data-driven insights for smarter decision-making through intelligent forecasting, pricing and demand analysis to accurately understand and predict customer demand. Zebra (NASDAQ: ZBRA) provides the tools to help businesses grow with asset visibility, connected frontline workers and intelligent automation. The company operates in more than 100 countries, and our customers include over 80% of the Fortune 500. Designed for the frontline, Zebra’s award-winning portfolio includes hardware, software, and services, all backed by our 50+ years of innovation and global partner ecosystem. **Who Is the Company Behind Zebra Workcloud Modeling Studio?** - **Seller:** [Zebra Technologies](https://www.g2.com/sellers/zebra-technologies) - **Year Founded:** 1969 - **HQ Location:** Lincolnshire, IL - **Twitter:** @ZebraTechnology (32,990 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/167024/ (11,659 employees on LinkedIn®) - **Ownership:** NASDAQ:ZBRA ## What Is Predictive Analytics Software? [Analytics Tools & Software](https://www.g2.com/categories/analytics-tools-software) ## What Software Categories Are Similar to Predictive Analytics Software? - [Analytics Platforms](https://www.g2.com/categories/analytics-platforms) - [Embedded Business Intelligence Software](https://www.g2.com/categories/embedded-business-intelligence) - [Marketing Analytics Software](https://www.g2.com/categories/marketing-analytics) - [Machine Learning Software](https://www.g2.com/categories/machine-learning) - [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms) - [Statistical Analysis Software](https://www.g2.com/categories/statistical-analysis) - [Time Series Intelligence Software](https://www.g2.com/categories/time-series-intelligence) --- ## How Do You Choose the Right Predictive Analytics Software? ### What You Should Know About Predictive Analytics Software ### What are predictive analytics tools and software? Predictive analytics software is all about making business outcomes predictable. Data scientists and data analysts can do this by using data mining and predictive modeling to analyze historical data. By better understanding the past, businesses can gain insights into the future. [Predictive analytics](https://www.g2.com/articles/predictive-analytics) is a step further than general [business intelligence](https://www.g2.com/glossary/business-intelligence-definition), which companies use to pull actionable insights from their data sets. Instead, users can develop [machine learning algorithms](https://www.g2.com/articles/what-is-machine-learning) and predictive models to help forecast and achieve business-critical numbers. The reason businesses can hit those critical numbers and become more predictive is due to the boom of big data. Companies can harness their data like never before. By recording and owning more and more historical and real-time data, data scientists have larger sample sizes to work with, meaning they can be much more accurate. Additionally, companies investing in predictive analytics without ensuring that their data is accurate, clean, and accessible will ultimately be wasting their time. However, those who can wrangle their data properly will create a significant competitive edge and hold an advantage in the market. ### Benefits of using predictive analytics tools - Accurately predict and forecast revenue numbers based on a wide range of variables - Understand and account for customer churn and retention - Predict employee churn based on historical factors for turnover - Make more precise, data-driven decisions in all departments based on available data - Determine both risks and opportunities that were otherwise hidden within company data ### Why use predictive analytics solutions? There are a number of applications for predictive analytics software and reasons businesses should adopt them, but they all boil down to understanding what has happened in the past, what could happen in the future, and what should be done to ensure positive business outcomes. These are considered [descriptive analytics, predictive analytics, and prescriptive analytics](https://www.g2.com/articles/types-of-data-analytics). **Descriptive Analytics (understanding the past) —** Descriptive analytics deals with understanding what has happened in the past and how it has influenced where a business is in the present. This means undergoing data mining on a company’s historical data. This type of analysis can be obtained by using business intelligence tools, big data analytics, or time-series data. Regardless of how it is attained, providing descriptive analytics is a key foundation of predictive analytics and creating data-driven decision-making processes. It requires thorough data preparation and organizing the data for easy descriptive analysis. **Predictive Analytics (knowing what is possible) —** Predictive analytics allows users and businesses to know and anticipate potential outcomes. Building predictive models based on descriptive analysis can ensure that businesses do not make the same mistake twice. It can also provide more accurate forecasting and planning, which helps to optimize efficiency. Ultimately, this analysis makes the unknown known. **Prescriptive Analytics (so now what?) —** The final step and ultimate reason for using predictive analytics tools is to make clear actions based on the suggestions and recommendations of the predictive models. This is where machine learning and deep learning functionality come into play. Some predictive analytics solutions can provide actionable insights without human intervention. For example, it can provide a short list of sales accounts that should close quickly based on several variables. Becoming prescriptive takes analytics a step further and is the ultimate reason for adopting advanced, predictive analytics. ### Who uses predictive analytics platforms? To fully take advantage of predictive analytics platforms, businesses need to hire highly skilled data scientists with knowledge in machine learning development and predictive modeling. These skilled workers are not abundant, so they are often paid very well. Dedicating financial resources to these positions may not be an option for every company, but those who can afford data scientists have a leg up on the competition. While data scientists or data analysts are the employees tasked with using predictive analytics software, there are many industries and departments that can be impacted by using predictive analytics: **Manufacturing and Supply Chain—** One area that can be greatly enhanced by using predictive analysis is demand planning for manufacturing companies. With more accurate forecasting, businesses can avoid risks like shortages and surpluses. Additionally, companies can become predictive about quality management and production issues. By analyzing what has caused production failures in the past, companies can anticipate and avoid production breakdowns in the future. Distribution is another major aspect of the supply chain that can be further optimized with predictive modeling. By better estimating where goods will need to be delivered and the risks that may hold up distribution modes, businesses can provide better service and more efficiently deliver their products to customers. Taking into account historical data, such as weather, traffic, and accident records, shipping can become a more precise science. **Retail —** Retail is another industry that is ripe for optimization with the help of predictive analytics. Retail predictive analytics can provide businesses with insights on everything from pricing optimization to understanding how shoppers navigate brick-and-mortar stores for better in-store organization of merchandise. E-commerce businesses can track these factors in a much more efficient manner. All e-commerce interactions can be recorded into a database and influenced by predictive models. This is one of the main reasons Amazon has been so successful and disruptive to brick-and-mortar retailers. Every decision can be made predictive with the help of data. **Marketing and Sales —** Being able to predict the actions of customers and prospects is an invaluable service for any business. Marketing teams can leverage predictive analytics software to project how marketing campaigns may perform, which segment of prospects to target with ads, and the potential conversion rates of each campaign. Understanding how these efforts impact the bottom line is critical to the success of marketing teams and translates into a much more efficient and productive sales team. At the same time, sales teams can leverage predictive modeling in such areas as lead scoring, determining which accounts to target first because they have a higher chance of closing. Ensuring that sales representatives are working smarter instead of harder means more revenue. A few [CRM](https://www.g2.com/categories/crm) and [marketing automation solutions](https://www.g2.com/categories/marketing-automation) provide some level of predictive functionality, but data scientists can separately funnel that data into dedicated predictive analytics tools to find cross-departmental correlations. **Financial Services—** The banking industry has long been ripe for disruption, but financial administrations are using predictive analytics solutions to better predict risk. Historical data can power predictive analytics software to predict fraudulent transactions and determine credit risks, among other functions. ### Types of predictive analytics software Predictive modeling is a complex science that requires years of training to understand. There is a reason data scientists are in high demand: not many people have a complete grasp of how to build predictive models. There are two main types of predictive models: classification and regression models. **Classification Models—** Simply put, classification puts a piece of data into a bucket or a class and labels it as such. Classification models essentially label data based on what an algorithm has already learned. The ultimate goal of classification models is to accurately bucket new data points into the proper classes so that the data can become predictive and prescriptive. **Regression Models—** Regression models analyze the relationship between two separate data points and help forecast what happens when they are placed side by side. For example, in baseball, teams may perform a regression analysis on the relationship between the number of fastballs thrown and the number of home runs hit. **Decision Trees —** One common type of classification model is a decision tree. These models predict several possible outcomes based on a variety of inputs. For example, if a sales team builds $1 million in a pipeline, they can close $100,000 in revenue, but if they create $10 million in a pipeline, they should be able to close $1 million in revenue. **Neural Networks—** Neural networks, known in the AI world as artificial neural networks, are extremely complex predictive models. These models can predict and analyze unstructured, nonlinear relationships between data points. These solutions provide pattern recognition and can help track anomalies. Artificial neural networks were originally created and built to mimic the synapses and neural aspects of the human brain. They are one of the contributing factors to the accelerated growth in artificial intelligence and deep learning. Other types of predictive modeling include Bayesian analysis, memory-based reasoning, k-nearest neighbor, support vector machines, and time-series data mining. ### Potential issues with predictive analytics software solutions **Lack of Skilled Employees—** The main issue with adopting predictive analytics software is the need for a skilled data scientist to interact with the data and build the models. There is a distinct skill gap in terms of finding users who understand how to pull data and build models and the implications that the data has on the overall business. For this reason, data scientists are in very high demand and, thus, expensive. **Data Organization—** Many companies face the challenge of organizing data so that it can be easily accessed. Harnessing big data sets that contain historical and real-time data is not easy in today's world. Companies often need to build a data warehouse or a data lake that can combine all the disparate data sources for easy access. This, again, requires highly knowledgeable employees. ### Software and services related to predictive analytics tools Predictive analytics software relates to many other analytics and [artificial intelligence software](https://www.g2.com/categories/artificial-intelligence) categories. [**Machine Learning Software**](https://www.g2.com/categories/machine-learning) **—** Machine learning algorithms are a key component of building effective predictive models. Many machine learning algorithms are built to provide recommendations or suggestions, which is also the end goal of predictive analytics software. Developers use these tools to embed machine learning inside applications, often to provide predictive and prescriptive analysis. [**Business Intelligence Platforms**](https://www.g2.com/categories/business-intelligence) **—** These tools are the traditional analytics solutions used to understand a company’s data. Data analysts use BI platforms to visualize and understand how specific actions impact business-critical initiatives. Some of these platforms offer predictive features, but their core purpose is not predictive modeling. [**Big Data Analytics**](https://www.g2.com/categories/big-data-analytics) **—** Big data analytics software, like business intelligence platforms, often provides predictive modeling functionality. However, these solutions are used more to track real-time data than to understand historical data. 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.