IBM watsonx.data Features
Model Development (5)
Language Support
Supports programming languages such as Java, C, or Python. Supports front-end languages such as HTML, CSS, and JavaScript
Drag and Drop
Offers the ability for developers to drag and drop pieces of code or algorithms when building models
Pre-Built Algorithms
Provides users with pre-built algorithms for simpler model development
Model Training
Supplies large data sets for training individual models
Feature Engineering
Transforms raw data into features that better represent the underlying problem to the predictive models
Machine/Deep Learning Services (6)
Computer Vision
Offers image recognition services
Natural Language Processing
Offers natural language processing services
Natural Language Generation
Offers natural language generation services
Artificial Neural Networks
Offers artificial neural networks for users
Natural Language Understanding
Offers natural language understanding services
Deep Learning
Provides deep learning capabilities
Deployment (5)
Managed Service
Manages the intelligent application for the user, reducing the need of infrastructure
Application
Allows users to insert machine learning into operating applications
Scalability
Provides easily scaled machine learning applications and infrastructure
On-Premise
Provides On-Premise deployment options.
Cloud
Provides Cloud deployment options (private or public cloud, hybrid cloud).
Database (3)
Real-Time Data Collection
Collects, stores, and organizes massive, unstructured data in real time This feature was mentioned in 28 IBM watsonx.data reviews.
Data Distribution
Facilitates the disseminating of collected big data throughout parallel computing clusters 27 reviewers of IBM watsonx.data have provided feedback on this feature.
Data Lake
Creates a repository to collect and store raw data from sensors, devices, machines, files, etc. 28 reviewers of IBM watsonx.data have provided feedback on this feature.
Integrations (2)
Hadoop Integration
Based on 28 IBM watsonx.data reviews. Aligns processing and distribution workflows on top of Apache Hadoop
Spark Integration
As reported in 27 IBM watsonx.data reviews. Aligns processing and distribution workflows on top of Apache Hadoop
Platform (3)
Machine Scaling
Based on 27 IBM watsonx.data reviews. Facilitates solution to run on and scale to a large number of machines and systems
Data Preparation
Based on 28 IBM watsonx.data reviews. Curates collected data for big data analytics solutions to analyze, manipulate, and model
Spark Integration
Based on 27 IBM watsonx.data reviews. Aligns processing and distribution workflows on top of Apache Hadoop
Processing (2)
Cloud Processing
Moves big data collection and processing to the cloud This feature was mentioned in 27 IBM watsonx.data reviews.
Workload Processing
Based on 25 IBM watsonx.data reviews. Processes batch, real-time, and streaming data workloads in singular, multi-tenant, or cloud systems
Data Transformation (2)
Real-Time Analytics
Facilitates analysis of high-volume, real-time data.
Data Querying
Allows user to query data through query languages like SQL.
Connectivity (4)
Hadoop Integration
Aligns processing and distribution workflows on top of Apache Hadoop
Spark Integration
Aligns processing and distribution workflows on top of Apache Spark
Multi-Source Analysis
Integrates data from multiple external databases.
Data Lake
Facilitates the dissemination of collected big data throughout parallel computing clusters.
Operations (5)
Data Visualization
As reported in 10 IBM watsonx.data reviews. Processes data and represents interpretations in a variety of graphic formats.
Data Workflow
Based on 10 IBM watsonx.data reviews. Strings together specific functions and datasets to automate analytics iterations.
Governed Discovery
Isolates certain datasets and facilitates management of data access.
Embedded Analytics
As reported in 10 IBM watsonx.data reviews. Allows big data tool to run and record data within external applications.
Notebooks
Use notebooks for tasks such as creating dashboards with predefined, scheduled queries and visualizations This feature was mentioned in 10 IBM watsonx.data reviews.
Administration (4)
Data Modelling
Tools to (re)structure data in a manner that allows extracting insights quickly and accurately
Recommendations
Analyzes data to find and recommend the highest value customer segmentations.
Workflow Management
Tools to create and adjust workflows to ensure consistency.
Dashboards and Visualizations
Presents information and analytics in a digestible, intuitive, and visually appealing way.
Compliance (4)
Sensitive Data Compliance
Supports compliance with PII, GDPR, HIPPA, PCI, and other regulatory standards.
Training and Guidelines
Provides guidelines or training related to sensitive data compliance requirements,
Policy Enforcement
Allows administrators to set policies for security and data governance
Compliance Monitoring
Monitors data quality and send alerts based on violations or misuse
Data Quality (3)
Data Preparation
Curates collected data for big data analytics solutions to analyze, manipulate, and model
Data Distribution
Facilitates the disseminating of collected big data throughout parallel computing clusters
Data Unification
Compile data from across all systems so that users can view relevant information easily.
Management (7)
Reporting
View ETL process data via reports and visualizations like charts and graphs.
Auditing
Record ETL historical data for auditing and potential data correction needs.
Business Glossary
Lets users build a glossary of business terms, vocabulary and definitions across multiple tools.
Data Discovery
Provides a built-in integrated data catalog that allows users to easily locate data across multiple sources.
Data Profililng
Monitors and cleanses data with the help of business rules and analytical algorithms.
Reporting and Visualization
Visualize data flows and lineage that demonstrates compliance with reports and dashboards through a single console.
Data Lineage
Provides an automated data lineage functionality which provides visibility over the entire data movement journey from data origination to destination.
Functionality (5)
Extraction
Extract data from the designated source(s) like relational databases, JSON files, and XML files.
Transformation
Cleanse and re-format extracted data to the needed target format.
Loading
Load reformatted data into target database, data warehouse, or other storage location.
Automation
Arrange ETL processes to occur automatically on needed time schedule (e.g., daily, weekly, monthly).
Scalability
Capable of scaling processing power up or down based on ETL volume.
System (1)
Data Ingestion & Wrangling
Gives user ability to import a variety of data sources for immediate use
Data Management (9)
Data Integration
Consolidates, Cleanses and Normalizes data from multiple disparate sources.
Data Compression
Helps save storage capacity and improves query performance.
Data Quality
Eliminates data inconsistency and duplications ensuring data integrity.
Built-In Data Analytics
SQL based analytics functions like Time series, pattern matching, geospatial analytics etc.
In-Database Machine Learning
Provides built in capabilities like machine learning algorithms, data preparation functions, model evaluation and management etc.
Data Lake Analytics
Allows data querying across data formats like parquet, ORC, JSON etc and analyze complex data types on HDFS
Data Migration
As reported in 46 IBM watsonx.data reviews. Provides movement of data from one location to another.
Managing Data
Provides an overall strategy for data governance. 45 reviewers of IBM watsonx.data have provided feedback on this feature.
Secured Data Storage
Aids in providing secured storage solutions for data extracted. 45 reviewers of IBM watsonx.data have provided feedback on this feature.
Integration (3)
AI/ ML Integration
Integrates with data science workflows, Machine Learning and artificial intelligence (AI) capabilities.
BI Tool Integration
Integrates with BI Tools to transform data into Actionable Insights.
Data lake Integration
Provides speed in data processing and capturing unstructured, semi-structured and streaming data.
Performance (1)
Scalability
Manages huge volumes of data, upscale or downscale as per demand.
Security (5)
Data Governance
Policies, procedures and standards to manage and access data.
Data Security
Restricts data access at a cell level, mask or hide parts of cells, and encrypt data at rest and in motion
Access Control
Authenticates and authorizes individuals to access the data they are allowed to see and use.
Roles Management
Helps identify and manage the roles of owners and stewards of data.
Compliance Management
Helps adhere to data privacy regulations and norms.
Maintainence (2)
Data Quality Management
Defines, validates, and monitors business rules to safeguard master data readiness.
Policy Management
Allows users to create and review data policies to make them consistent across the organization.
Data as a Service (2)
Self-Service Isights
As reported in 45 IBM watsonx.data reviews. Provides specialization in data-driven insights by direct access to data analysts or end users.
DaaS Quality
As reported in 45 IBM watsonx.data reviews. Provides data in structured and readable formats.
Architecture (2)
Data Fabric Creation
Aids in establishing a data fabric with a network of various tools to operationalize data. This feature was mentioned in 45 IBM watsonx.data reviews.
DaaS Architecture
Provides users with options of architecture such as centralized or decentralized. 45 reviewers of IBM watsonx.data have provided feedback on this feature.
Generative AI (7)
AI Text Generation
Allows users to generate text based on a text prompt.
AI Text Summarization
Condenses long documents or text into a brief summary.
AI Text Generation
Allows users to generate text based on a text prompt.
AI Text Summarization
Condenses long documents or text into a brief summary.
AI Text-to-Image
Provides the ability to generate images from a text prompt.
AI Text Generation
Allows users to generate text based on a text prompt.
AI Text Summarization
Condenses long documents or text into a brief summary.
Agentic AI - Data Governance (6)
Autonomous Task Execution
Capability to perform complex tasks without constant human input
Multi-step Planning
Ability to break down and plan multi-step processes
Cross-system Integration
Works across multiple software systems or databases
Adaptive Learning
Improves performance based on feedback and experience
Natural Language Interaction
Engages in human-like conversation for task delegation
Decision Making
Makes informed choices based on available data and objectives
Agentic AI - Data Science and Machine Learning Platforms (7)
Autonomous Task Execution
Capability to perform complex tasks without constant human input
Multi-step Planning
Ability to break down and plan multi-step processes
Cross-system Integration
Works across multiple software systems or databases
Adaptive Learning
Improves performance based on feedback and experience
Natural Language Interaction
Engages in human-like conversation for task delegation
Proactive Assistance
Anticipates needs and offers suggestions without prompting
Decision Making
Makes informed choices based on available data and objectives
