6 December 2024
The rapid growth of data and fragmentation of technical stacks have only intensified data silos, significantly impacting data team productivity—Forrester found that employees are spending an average of 12 hours a week “chasing data.” This challenge is intensified by a similar growth in the diversity of data formats, especially when it comes to unstructured data. Unstructured data can produce valuable insights on consumer behavior and market trends, though processing it is a manually intensive process, which few tools can manage effectively.
Not only does siloed data impact productivity, but siloed data causes inconsistency and poor quality, jeopardizing AI initiatives. A robust data integration strategy is key to overcoming these challenges—unifying data, ensuring high-quality information, boosting productivity and enabling AI-readiness.
Today, we are excited to share that IBM has been named a Leader in the 2024 Gartner® Magic Quadrant™ for Data Integration Tools.
IBM is dedicated to providing customers a complete and performant approach to data integration as a cornerstone to their wider data fabric strategy. We feel IBM’s continued investment in enabling modern data workloads recognizes IBM for its IBM Data Integration as both a Leader in the report over the past 19 years in a row and an innovator for the years to come.
IBM supports the entire lifecycle of data integration, with multiple integration patterns and the flexibility to support hybrid-multi cloud infrastructure, so that organizations can unlock value regardless of wherever their data resides.
Let’s dive deeper into the selection of integrated capabilities across IBM Data Integration.
IBM Data Integration offers clients a flexible and adaptable approach to data integration, providing multiple patterns tailored to their unique use cases. Clients can leverage interoperable solutions, purpose-fit to specific scenarios, such as IBM DataStage for ETL/ELT/TETL processing, the recent acquisition, IBM StreamSets for real-time streaming data integration, and IBM Data Replication for low-latency, near real-time data synchronization. This level of adaptability enables clients to match integration styles to meet performance service level agreements or requirements based on cost, latency, availability, quality and security.
Additionally, IBM’s various integration patterns support different kinds of data, including structured, semi-structured, and unstructured data. This enables clients to unlock value from all their data and manage it from a unified place to streamline outcomes across use cases, including generative AI, retrieval-augmented generation (RAG), warehouse and lakehouse modernization, and beyond. Learn more about IBM Data Integration for Unstructured Data.
IBM Data Integration tackles the fragmentation of data tooling stacks and data itself by embedding integration capabilities within any hybrid infrastructure—specifically remote data planes and remote engines. This enables clients to process data across any geography, cloud, and even on-premises, ensuring data security, cost-effectiveness, and minimizing unnecessary data movement. This hybrid approach accommodates complex regulatory and financial optimization needs.
Moreover, IBM’s hybrid by design architecture enables compatibility with existing systems, eliminating the need for a complete "rip and replace.” This adaptable data management environment reduces the risk of vendor lock-in.
Enterprise data teams are under growing pressure from rising data requests, often lacking the resources to manage them effectively. IBM Data Integration addresses this need with tooling that empowers less technical users to respond to downstream data needs and seasoned engineers to accelerate inception to production. Including:
Data teams often struggle with visibility into the health and behavior of their data, impacting quality, costs, and decision-making. IBM Data Integration mitigates these challenges with built-in data observability, powered by IBM Databand®, enabling users to detect and remediate quality issues proactively, fostering trust and improving downstream reliability. Continuous monitoring of data pipelines at scale allows operators to quickly identify failures, manage data quality SLAs, assess cost and performance, and receive proactive anomaly notifications, ensuring high-quality data, efficient operations and optimal data management.
IBM is dedicated to evolving with clients to meet modern data and integration needs, offering next-generation data integration solutions. With IBM’s in-built migration utility for DataStage modernizations (available at no extra cost), a highly experienced support team, IBM customer success teams, and other accelerators, IBM ensures clients can modernize at their own pace with operational continuity whether scaling existing systems or executing new workloads.
With the recent acquisition of StreamSets, IBM is poised to help businesses unlock new use cases and tackle real-time data challenges that optimize decision-making. This portfolio addition underscores IBM’s commitment to delivering the most complete set of data integration capabilities that meet enterprises unique needs so that they can optimize data usage for AI, business intelligence, analytics, and so much more. This strategy helps organizations optimize data usage, expand into new markets, and increase revenue.
We’re excited to be named a Leader in the 2024 Gartner® Magic Quadrant™ for Data Integration Tools. Read the report for more information on our positioning.
Gartner, Magic Quadrant for Data Integration Tools, Thornton Craig, Sharat Menon, Robert Thanaraj, Michele Launi, Nina Showell, 3 December 2024.GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved.
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