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It addresses many of the shortcomings of traditional data lakes by providing features such as ACID transactions, schema evolution, row-level updates and deletes, and time travel. In this blog post, we’ll discuss how the metadata layer of Apache Iceberg can be used to make data lakes more efficient.
A combined, interoperable suite of tools for data team productivity, governance, and security for large and small data teams. Central IT Data Teams focus on standards, compliance, and cost reduction. ’ They are dataenabling vs. value delivery. And their business customers want more data trust.
IDC, BARC, and Gartner are just a few analyst firms producing annual or bi-annual market assessments for their research subscribers in software categories ranging from data intelligence platforms and data catalogs to datagovernance, data quality, metadata management and more.
For business users Data Catalogs offer a number of benefits such as better decision-making; data catalogs provide business users with quick and easy access to high-quality data. This availability of accurate and timely dataenables business users to make informed decisions, improving overall business strategies.
Yes, let’s talk about datagovernance, that thing we love to hate. I just attended the 17th Annual Chief Data Officer and Information Quality Symposium in July, and there, I heard many creative suggestions for renaming datagovernance.
Datagovernance , thankfully, provides a framework for compliance with either or both – in addition to other regulatory mandates your organization may be subject to. DataGovernance for Regulatory Compliance. Regulatory compliance remains a key driver for datagovernance. A Regulatory EDGE.
These data requirements could be satisfied with a strong datagovernance strategy. Governance can — and should — be the responsibility of every data user, though how that’s achieved will depend on the role within the organization. How can data engineers address these challenges directly?
Advanced analytics and enterprise data are empowering several overarching initiatives in supply chain risk reduction – improved visibility and transparency into all aspects of the supply chain balanced with datagovernance and security. . Improve Visibility within Supply Chains.
One of the first steps in any digital transformation journey is to understand what data assets exist in the organization. When we began, we had a very technical and archaic tool, an enterprise metadata management platform that cataloged our assets. Learn how AmFam balances datagovernance with self-service analytics.
Built on the Gartner-recognized DQLabs augmented data quality platform, erwin Data Intelligence’s new data quality offering provides erwin Data Intelligence customers with the ability to leverage erwin Data Catalog metadata to initiate a need for data quality assessment. Another exuberant 12.0
Practitioners and hands-on data users were thrilled to be there, and many connected as they shared their progress on their own data stack journeys. People were familiar with the value of a data catalog (and the growing need for datagovernance ), though many admitted to being somewhat behind on their journeys.
Once you’ve determined what part(s) of your business you’ll be innovating — the next step in a digital transformation strategy is using data to get there. Constructing A Digital Transformation Strategy: DataEnablement. Many organizations prioritize data collection as part of their digital transformation strategy.
As IT leaders oversee migration, it’s critical they do not overlook datagovernance. Datagovernance is essential because it ensures people can access useful, high-quality data. Therefore, the question is not if a business should implement cloud data management and governance, but which framework is best for them.
I assert that through 2027, three-quarters of enterprises will be engaged in data intelligence initiatives to increase trust in their data by leveraging metadata to understand how, when and where data is used in their organization, and by whom. Regards, Matt Aslett
Datagovernance is growing in urgency and prominence. As regulations grow more complex (and compliance fines more onerous) organizations aren’t just adapting datagovernance frameworks to drive compliance – they’re leveraging governance to fuel a growing range of use cases, from collaboration to stewardship, discovery, and more.
Enterprises are… turning to data catalogs to democratize access to data, enable tribal data knowledge to curate information, apply data policies, and activate all data for business value quickly.”. Gartner: Magic Quadrant for Metadata Management Solutions. Below are some of our other favorites.
So it’s fitting that Snowflake Summit , the premier event for data cloud strategy, will occur at Caesars Forum in Las Vegas on June 26–29 (togas not required). As a 2-time Snowflake DataGovernance Partner of the Year , Alation knows how important this event is to the Snowflake community. The datagovernance team’s solution?
See The Future of Data and Analytics: Reengineering the Decision, 2025. You mentioned a few times that most enterprises are not good at datagovernance. It is much less just about defensive controls and more about enabling capabilities. Which tools would you recommend for getting governance in place? Do you agree?
According to the report, “Demand for data catalogs is soaring as organizations struggle to inventory distributed data assets to facilitate data monetization and conform to regulations.” The tour stops at Gartner Symposium next month, where you can learn first hand why Gartner believes “Data Catalogs are the New Black.”.
After investing in self-service analytic tooling, organizations are now turning their attention to linking infrastructure and tooling to data-driven decisions. The Forrester Wave : Machine Learning Data Catalogs, Q2 2018. But as the category gains greater recognition, more companies are building data catalog solutions.
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