Redwood City — Aug. 17, 2017 — Alation Inc.,the collaborative data company, today announced its debut as a Leader in the 2017 Gartner Magic Quadrant for Metadata Management Solutions. Alation premiered in the Leaders quadrant evaluated among 14 companies for both “ability to execute” and “completeness of vision.”
The complete report, including the quadrant graphic, is available at: http://go.alation.com/gartner-mq-2017-aug16
As organizations seek to gain more value out of their data assets, metadata management has become a strategic business investment. Increasing volumes of data and the reduction in data storage costs have driven organizations to adopt metadata management systems to organize the influx of new data assets. At the same time, widespread adoption of self-service analytics has increased the audience for discovering, using and understanding metadata beyond the developer or IT professional. The metadata repository designed for data integration or compliance initiatives is no longer sufficient to meet the needs of today’s analytics organization. Data catalogs service the new, broad constituency of data users in enterprises, including analysts and business users as well as developers and IT professionals.
According to Gartner, “Leveraging established metadata management capabilities (such as business glossaries, data lineage and impact analysis) and other innovative approaches (such as self-generating topic extraction, taxonomy generation, semantic discovery, machine-learning pattern mapping and knowledge graphing), new technology-based solutions are emerging to effectively support the generation and curation of data catalogs. This support enables enterprises to get the most value from their existing data assets, by making them easily discoverable and understandable by the users who need the data they manage.”*
Data catalogs rely on artificial intelligence (AI) to deliver value. Embedded AI technology automatically collects technical metadata, business metadata, and key learnings on how data is being used, freeing teams from the tedious work of manual documentation. AI also makes active suggestions to data consumers in order to optimize the analytics process, remove complexity from data management, and promote team collaboration during analysis.
“Metadata management solutions are no longer static repositories. By embracing data catalogs with the power of artificial intelligence and active metadata management, solutions like Alation empower organizations with proactive recommendations and collaboration between IT and business users,” said Satyen Sangani, CEO of Alation. “By listening to our customers and iterating based on their feedback, Alation has been able to achieve the right balance of both AI innovation and usability to deliver business impact and meet the strategic needs of CIOs and CTOs. Our customers are using data catalogs to transform from process-centric to data-driven organizations.”
The Alation Data Catalog leverages Behavior I/O, a machine learning engine that identifies meaningful patterns about how data is being used and how data curators are managing data governance. From those patterns, Behavior I/O makes recommendations, like which data set is best suited to the analytic question at hand, how it should be labeled for standardization, what term to tag it with so it is easy to find, and which data sets could be blended for further insight. For example, the Alation Compose application leverages Behavior I/O to turn a static metadata repository into active recommendations that appear directly within the SQL query writing experience, making it easy for users to find and use data efficiently and accurately.
To learn more about Alation’s data catalog and how it differentiates from other metadata management offerings, visit www.alation.com/product
Learn more about Alation
- Check out Alation’s blog post: “Gartner Magic Quadrant for Metadata Management Includes Alation
- 2017 Gartner Magic Quadrant for Metadata Management Solutions
*Gartner, Magic Quadrant for Metadata Management Solutions, 10 August 2017
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