IBM Enhances Data Intelligence and Data Integration

I previously wrote about IBM’s strategy of consolidating analytics, data and artificial intelligence (AI) functionality from various products under its watsonx brand, which was launched in 2023 to address the AI development life cycle, as well as data storage processing and AI governance. The company has added two more offerings to its watsonx portfolio in recent months, combining established functionality with recently acquired assets and newly developed capabilities to better address requirements for data intelligence and data integration. The newly launched products make it easier for IBM customers to access functionality for data discovery, data governance, data quality, data lineage and the development and sharing of data products, as well as the creation, orchestration and observability of both batch and streaming data pipelines.

IBM unveiled its watsonx brand at its Think customer event in 2023 with the launch of its platform to address the development, testing, training, tuning and deployment of AI applications utilizing both machine learning and foundation models. The watsonx product portfolio initially included the watsonx.ai development environment, as well as watsonx.data, a data lakehouse environment, and watsonx.governance for collaboratively managing, cataloging and monitoring AI models. A year later, at Think 2024, IBM made a series of announcements that enhanced all three offerings, while also boosting its complementary data governance, data integration, data lineage, data sharing and data observability capabilities. Earlier this year the company brought those capabilities under the watsonx brand with the announcements of watsonx.data intelligence and watsonx.data integration. As well as combining established and internally-developed functionality for data integration, data governance, data sharing and data quality, the new products also incorporated capabilities accumulated through various acquisitions, including the real-time data integration capabilities acquired with StreamSets in 2024, data lineage capabilities acquired with Manta in 2023 and the data observability expertise acquired with Databand.ai in 2022. IBM was well-placed to address enterprise requirements for data intelligence and data integration even before the announcements of the new products, having been rated as Exemplary in the 2024 ISG Buyers Guides for Data Intelligence, Data Governance, Data Quality, Data Integration and Data Products.

ISG defines data intelligence products as software that provides a holistic view of data production and consumption, enabling data administrators to understand and manage the use of data in BI and AI initiatives and accelerate strategic data-democratization initiatives to provide data analysts and business users with governed self-service access to data across an enterprise. This combination of functionality is increasingly important in enabling enterprises to ensure data is fit for AI initiatives. More than one-half of respondents to ISG’s Market Lens Data and AI Study cited data usability for AI as a data challenge. Data intelligence platforms provide a combination of data inventory, data discovery and metadata management functionality, as well as data governance, data quality and data lineage to ensure that business users and data analysts can find and access the data they need, while providing analytics and data leaders with key metrics on data production and consumption, including the value generated by data-projects. 

IBM’s watsonx.data intelligence combines data governance capabilities formerly available as IBM Knowledge Catalog along with functionality for curating and preparing both structure and unstructured data, analyzing and monitoring data quality, viewing and managing data lineage, as well as data product development, sharing and management functionality. The watsonx.data integration offering provides functionality for transforming data using IBM’s DataStage ETL tool as well as real-time data processing using StreamSets, running data replication jobs using IBM Data Replication, and observing and monitoring data integration flows using IBM Data Observability. AI-powered assistance is a key feature of both watsonx.data intelligence and watsonx.data integration. Data Intelligence Assistant offers a natural language interface for finding, understanding and classifying cataloged data, while DataStage Assistant provides a natural language interface for building integration data flows and transformations. I assert that through 2027, almost all data intelligence software providers will deliver support for GenAI-driven assistants to automate and accelerate data management and integration processes.

Watsonx.data intelligence and watsonx.data integration are available as a combined Data Fabric experience on IBM Software Hub as well as via the watsonx.data lakehouse environment on IBM Cloud. While the launch brings together functionality required for data management from across the wider IBM software portfolio, the consolidation of IBM’s data-related capabilities remains a work in progress. Many of the capabilities delivered with watsonx.data intelligence and watsonx.data integration also continue to be separately available via IBM Cloud Pak for Data. While IBM Cloud Pak for Data does not include the generative AI or unstructured data processing capabilities, it does provide functionality that is not available with watsonx.data intelligence and watsonx.data integration, such as data virtualization and master data management functionality, as well as Watson Studio and Watson Machine Learning for the development and deployment of AI projects, which are separately available via watsonx.ai. The data product development, sharing and management functionality of watsonx.data intelligence also continues to be available on a standalone basis via IBM Data Product Hub. I recommend that enterprises exploring data intelligence and data integration products include IBM’s watsonx portfolio in their evaluations. However, potential adopters are advised to check product details carefully to ensure they understand what is and isn’t included.

Regards,

Matt Aslett