IBM StreamSets Features

The ability to process large amounts of data.

The ability to process data from a wide variety of sources and formats.

The ability to work seamlessly with another software platform.

Processing data from a variety of sources in real time as it arrives.

Tools to visualize and analyze data.

Provides a high performance, flexibile analytics platform to support data management and embrace data driven decision making.

Collect and displays metrics across the data integration via a dashboard.

Pull any required data from a variety of sources, including email, web pages, PDFs, and other documents.

Organize extracted data into a more easily digestible structure.

Amass extracted data in a variety of data formats like spreadsheets and .csv.

Clean extracted data by removing duplicates, clearing excess characters, grouping by characteristic, and more.

Stores data in cloud storage for access at any point.

Generate visual data representations from extracted data.

Extract data from the designated source(s) like relational databases, JSON files, and XML files.

Cleanse and re-format extracted data to the needed target format.

Load reformatted data into target database, data warehouse, or other storage location.

Arrange ETL processes to occur automatically on needed time schedule (e.g., daily, weekly, monthly).

Capable of scaling processing power up or down based on ETL volume.

View ETL process data via reports and visualizations like charts and graphs.

Record ETL historical data for auditing and potential data correction needs.

Integrates data and data-related technologies into a single environment.

Provides metadata management capabilities.

Empowers the user via a self-service capability to manage data workflows.

Completely automates end-to-end data workflows across the data integration lifecycle.

Involved solely in monitoring data pipelines, sending alerts and troubleshooting data.

Deploys testing capabilities such as report testing, big data testing, cloud data migration testing, ETL and data warehouse testing.

Supports analytical platforms and data pipelines across complex hybrid environments.

Supports migration of component or pipeline to different cloud environments.

Pull any required data from a variety of sources, including email, web pages, PDFs, and other documents.

Allows users to generate text based on a text prompt.

Condenses long documents or text into a brief summary.

Capability to perform complex tasks without constant human input

Ability to break down and plan multi-step processes

Works across multiple software systems or databases

Improves performance based on feedback and experience

Makes informed choices based on available data and objectives