IBM watsonx.data Features
What are the features of IBM watsonx.data?
Database
- Real-Time Data Collection
- Data Distribution
- Data Lake
Integrations
- Hadoop Integration
- Spark Integration
Platform
- Data Preparation
- Spark Integration
Processing
- Cloud Processing
Data Management
- Data Migration
- Managing Data
- Secured Data Storage
Data as a Service
- Self-Service Isights
- DaaS Quality
Architecture
- Data Fabric Creation
- DaaS Architecture
IBM watsonx.data Categories on G2
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Model Development
Language Support | Supports programming languages such as Java, C, or Python. Supports front-end languages such as HTML, CSS, and JavaScript | Not enough data | |
Drag and Drop | Offers the ability for developers to drag and drop pieces of code or algorithms when building models | Not enough data | |
Pre-Built Algorithms | Provides users with pre-built algorithms for simpler model development | Not enough data | |
Model Training | Supplies large data sets for training individual models | Not enough data | |
Pre-Built Algorithms | Provides users with pre-built algorithms for simpler model development | Not enough data | |
Model Training | Supplies large data sets for training individual models | Not enough data | |
Feature Engineering | Transforms raw data into features that better represent the underlying problem to the predictive models | Not enough data |
Machine/Deep Learning Services
Computer Vision | Offers image recognition services | Not enough data | |
Natural Language Processing | Offers natural language processing services | Not enough data | |
Natural Language Generation | Offers natural language generation services | Not enough data | |
Artificial Neural Networks | Offers artificial neural networks for users | Not enough data | |
Computer Vision | Offers image recognition services | Not enough data | |
Natural Language Understanding | Offers natural language understanding services | Not enough data | |
Natural Language Generation | Offers natural language generation services | Not enough data | |
Deep Learning | Provides deep learning capabilities | Not enough data |
Deployment
Managed Service | Manages the intelligent application for the user, reducing the need of infrastructure | Not enough data | |
Application | Allows users to insert machine learning into operating applications | Not enough data | |
Scalability | Provides easily scaled machine learning applications and infrastructure | Not enough data | |
Managed Service | Manages the intelligent application for the user, reducing the need of infrastructure | Not enough data | |
Application | Allows users to insert machine learning into operating applications | Not enough data | |
Scalability | Provides easily scaled machine learning applications and infrastructure | Not enough data | |
On-Premise | Provides On-Premise deployment options. | Not enough data | |
Cloud | Provides Cloud deployment options (private or public cloud, hybrid cloud). | Not enough data |
Database
Real-Time Data Collection | As reported in 22 IBM watsonx.data reviews. Collects, stores, and organizes massive, unstructured data in real time | 86% (Based on 22 reviews) | |
Data Distribution | Facilitates the disseminating of collected big data throughout parallel computing clusters This feature was mentioned in 21 IBM watsonx.data reviews. | 87% (Based on 21 reviews) | |
Data Lake | As reported in 22 IBM watsonx.data reviews. Creates a repository to collect and store raw data from sensors, devices, machines, files, etc. | 86% (Based on 22 reviews) |
Integrations
Hadoop Integration | Based on 22 IBM watsonx.data reviews. Aligns processing and distribution workflows on top of Apache Hadoop | 83% (Based on 22 reviews) | |
Spark Integration | Based on 21 IBM watsonx.data reviews. Aligns processing and distribution workflows on top of Apache Hadoop | 86% (Based on 21 reviews) |
Platform
Machine Scaling | Based on 21 IBM watsonx.data reviews. Facilitates solution to run on and scale to a large number of machines and systems | 83% (Based on 21 reviews) | |
Data Preparation | As reported in 22 IBM watsonx.data reviews. Curates collected data for big data analytics solutions to analyze, manipulate, and model | 85% (Based on 22 reviews) | |
Spark Integration | Aligns processing and distribution workflows on top of Apache Hadoop This feature was mentioned in 21 IBM watsonx.data reviews. | 86% (Based on 21 reviews) |
Processing
Cloud Processing | Based on 21 IBM watsonx.data reviews. Moves big data collection and processing to the cloud | 88% (Based on 21 reviews) | |
Workload Processing | Processes batch, real-time, and streaming data workloads in singular, multi-tenant, or cloud systems This feature was mentioned in 20 IBM watsonx.data reviews. | 88% (Based on 20 reviews) |
Data Transformation
Real-Time Analytics | Facilitates analysis of high-volume, real-time data. | Not enough data | |
Data Querying | Allows user to query data through query languages like SQL. | Not enough data |
Connectivity
Hadoop Integration | Aligns processing and distribution workflows on top of Apache Hadoop | Not enough data | |
Spark Integration | Aligns processing and distribution workflows on top of Apache Spark | Not enough data | |
Multi-Source Analysis | Integrates data from multiple external databases. | Not enough data | |
Data Lake | Facilitates the dissemination of collected big data throughout parallel computing clusters. | Not enough data |
Operations
Data Visualization | Processes data and represents interpretations in a variety of graphic formats. | Not enough data | |
Data Workflow | Strings together specific functions and datasets to automate analytics iterations. | Not enough data | |
Governed Discovery | Isolates certain datasets and facilitates management of data access. | Not enough data | |
Embedded Analytics | Allows big data tool to run and record data within external applications. | Not enough data | |
Notebooks | Use notebooks for tasks such as creating dashboards with predefined, scheduled queries and visualizations | Not enough data |
Administration
Data Modelling | Tools to (re)structure data in a manner that allows extracting insights quickly and accurately | Not enough data | |
Recommendations | Analyzes data to find and recommend the highest value customer segmentations. | Not enough data | |
Workflow Management | Tools to create and adjust workflows to ensure consistency. | Not enough data | |
Dashboards and Visualizations | Presents information and analytics in a digestible, intuitive, and visually appealing way. | Not enough data |
Compliance
Sensitive Data Compliance | Supports compliance with PII, GDPR, HIPPA, PCI, and other regulatory standards. | Not enough data | |
Training and Guidelines | Provides guidelines or training related to sensitive data compliance requirements, | Not enough data | |
Policy Enforcement | Allows administrators to set policies for security and data governance | Not enough data | |
Compliance Monitoring | Monitors data quality and send alerts based on violations or misuse | Not enough data |
Data Quality
Data Preparation | Curates collected data for big data analytics solutions to analyze, manipulate, and model | Not enough data | |
Data Distribution | Facilitates the disseminating of collected big data throughout parallel computing clusters | Not enough data | |
Data Unification | Compile data from across all systems so that users can view relevant information easily. | Not enough data |
Management
Reporting | View ETL process data via reports and visualizations like charts and graphs. | Not enough data | |
Auditing | Record ETL historical data for auditing and potential data correction needs. | Not enough data | |
Business Glossary | Lets users build a glossary of business terms, vocabulary and definitions across multiple tools. | Not enough data | |
Data Discovery | Provides a built-in integrated data catalog that allows users to easily locate data across multiple sources. | Not enough data | |
Data Profililng | Monitors and cleanses data with the help of business rules and analytical algorithms. | Not enough data | |
Reporting and Visualization | Visualize data flows and lineage that demonstrates compliance with reports and dashboards through a single console. | Not enough data | |
Data Lineage | Provides an automated data lineage functionality which provides visibility over the entire data movement journey from data origination to destination. | Not enough data |
Functionality
Extraction | Extract data from the designated source(s) like relational databases, JSON files, and XML files. | Not enough data | |
Transformation | Cleanse and re-format extracted data to the needed target format. | Not enough data | |
Loading | Load reformatted data into target database, data warehouse, or other storage location. | Not enough data | |
Automation | Arrange ETL processes to occur automatically on needed time schedule (e.g., daily, weekly, monthly). | Not enough data | |
Scalability | Capable of scaling processing power up or down based on ETL volume. | Not enough data |
System
Data Ingestion & Wrangling | Gives user ability to import a variety of data sources for immediate use | Not enough data | |
Language Support | Supports programming languages such as Java, C, or Python. Supports front-end languages such as HTML, CSS, and JavaScript | Not enough data | |
Drag and Drop | Offers the ability for developers to drag and drop pieces of code or algorithms when building models | Not enough data |
Data Management
Data Integration | Consolidates, Cleanses and Normalizes data from multiple disparate sources. | Not enough data | |
Data Compression | Helps save storage capacity and improves query performance. | Not enough data | |
Data Quality | Eliminates data inconsistency and duplications ensuring data integrity. | Not enough data | |
Built-In Data Analytics | SQL based analytics functions like Time series, pattern matching, geospatial analytics etc. | Not enough data | |
In-Database Machine Learning | Provides built in capabilities like machine learning algorithms, data preparation functions, model evaluation and management etc. | Not enough data | |
Data Lake Analytics | Allows data querying across data formats like parquet, ORC, JSON etc and analyze complex data types on HDFS | Not enough data | |
Data Migration | Based on 29 IBM watsonx.data reviews. Provides movement of data from one location to another. | 82% (Based on 29 reviews) | |
Managing Data | Provides an overall strategy for data governance. This feature was mentioned in 29 IBM watsonx.data reviews. | 84% (Based on 29 reviews) | |
Secured Data Storage | As reported in 29 IBM watsonx.data reviews. Aids in providing secured storage solutions for data extracted. | 86% (Based on 29 reviews) |
Integration
AI/ ML Integration | Integrates with data science workflows, Machine Learning and artificial intelligence (AI) capabilities. | Not enough data | |
BI Tool Integration | Integrates with BI Tools to transform data into Actionable Insights. | Not enough data | |
Data lake Integration | Provides speed in data processing and capturing unstructured, semi-structured and streaming data. | Not enough data |
Performance
Scalability | Manages huge volumes of data, upscale or downscale as per demand. | Not enough data |
Security
Data Governance | Policies, procedures and standards to manage and access data. | Not enough data | |
Data Security | Restricts data access at a cell level, mask or hide parts of cells, and encrypt data at rest and in motion | Not enough data | |
Access Control | Authenticates and authorizes individuals to access the data they are allowed to see and use. | Not enough data | |
Roles Management | Helps identify and manage the roles of owners and stewards of data. | Not enough data | |
Compliance Management | Helps adhere to data privacy regulations and norms. | Not enough data |
Maintainence
Data Quality Management | Defines, validates, and monitors business rules to safeguard master data readiness. | Not enough data | |
Policy Management | Allows users to create and review data policies to make them consistent across the organization. | Not enough data |
Data as a Service
Self-Service Isights | As reported in 29 IBM watsonx.data reviews. Provides specialization in data-driven insights by direct access to data analysts or end users. | 84% (Based on 29 reviews) | |
DaaS Quality | Provides data in structured and readable formats. This feature was mentioned in 29 IBM watsonx.data reviews. | 84% (Based on 29 reviews) |
Architecture
Data Fabric Creation | Aids in establishing a data fabric with a network of various tools to operationalize data. This feature was mentioned in 29 IBM watsonx.data reviews. | 83% (Based on 29 reviews) | |
DaaS Architecture | Provides users with options of architecture such as centralized or decentralized. 29 reviewers of IBM watsonx.data have provided feedback on this feature. | 84% (Based on 29 reviews) |
Generative AI
AI Text Generation | Allows users to generate text based on a text prompt. | Not enough data | |
AI Text Summarization | Condenses long documents or text into a brief summary. | Not enough data | |
AI Text Generation | Allows users to generate text based on a text prompt. | Not enough data | |
AI Text Summarization | Condenses long documents or text into a brief summary. | Not enough data | |
AI Text-to-Image | Provides the ability to generate images from a text prompt. | Not enough data | |
AI Text Generation | Allows users to generate text based on a text prompt. | Not enough data | |
AI Text Summarization | Condenses long documents or text into a brief summary. | Not enough data |
Agentic AI - Data Governance
Autonomous Task Execution | Capability to perform complex tasks without constant human input | Not enough data | |
Multi-step Planning | Ability to break down and plan multi-step processes | Not enough data | |
Cross-system Integration | Works across multiple software systems or databases | Not enough data | |
Adaptive Learning | Improves performance based on feedback and experience | Not enough data | |
Natural Language Interaction | Engages in human-like conversation for task delegation | Not enough data | |
Decision Making | Makes informed choices based on available data and objectives | Not enough data |
Agentic AI - Data Science and Machine Learning Platforms
Autonomous Task Execution | Capability to perform complex tasks without constant human input | Not enough data | |
Multi-step Planning | Ability to break down and plan multi-step processes | Not enough data | |
Cross-system Integration | Works across multiple software systems or databases | Not enough data | |
Adaptive Learning | Improves performance based on feedback and experience | Not enough data | |
Natural Language Interaction | Engages in human-like conversation for task delegation | Not enough data | |
Proactive Assistance | Anticipates needs and offers suggestions without prompting | Not enough data | |
Decision Making | Makes informed choices based on available data and objectives | Not enough data |
