data catalog

Why Your Data Catalog Can’t Exist on its Own

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Why Your Data Catalog Can’t Exist on its Own

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Data catalogs are an essential component of your broader data strategy. Modern data catalogs, “Make it easier for your analysts to find, understand and trust the data” within your database. Your data catalog is essential for synthesizing information about your data and making that information available across your company but isn’t the actual data. Your catalog may give users the ability to search and index meta information about your data, but it won’t go all the way to providing access control and security on your data.

This past quarter, many of our partners shared their guidance on data catalogs and the value they add to your data solution. We checked in on a what a few of our partners were saying and compiled the best in thought leadership for you here.

Alation: How to Get Immediate Value from Your Data Catalog

This blog post, written by GT Volpe, describes factors that will help your organization see immediate value in your data catalog. Volpe begins this piece by defining what it means for an organization to be data-driven and how data catalogs fit seamlessly in the push to be a data driven organization. Volpe shares considerations that you should think through prior to applying a data catalog, including focusing on planned outcomes and user skills, considering culture, industry, and regional needs, and embracing scalability and expansion.

Volpe talks of the importance of ensuring that your data catalog works for you and will continue to work for you as you scale, and as priorities may change. He writes of the importance of seeing immediate value from your data catalog, and that the one way to ensure success and accelerate time to value is to implement a data catalog plus data governance solution from day one – he writes that with the combination of a good data governance solution and a good data catalog, you will see immediate business value.

Alation: What Is the True Value of a Data Catalog?

Aaron Bradshaw, Data Governance & Enablement Specialist - Solutions Engineer at Alation, wrote about the specific value adds of implementing a data catalog. Bradshaw explains the reasons one may consider implementing a data catalog and what each implementor may expect from their catalog. He goes on to describe the difference between offensive and defensive approaches to data strategy and how that may play part in the decisions your organization makes surrounding investment and implementation of your data strategy.

Bradshaw concludes this blog post by outlining the strategic decision to implement a data catalog by quantifying its monetary value. Through a study done in partnership with Forrester, Alation discovered that “Adopting data catalogs has both quantitative and qualitative advantages, including a 364% return on investment (ROI).”

Collibra: Data Catalogs, Data Governance, and the Journey to Data Intelligence

This blog post, written by Paul Ewasuik, Director of Cloud Partnerships at Collibra, takes readers through the key points of a data governance plus data catalog solution. This post breaks down the often-intimidating components of data governance and data catalogs and turns it into understandable and digestible actionable items for your organization to follow. Collibra mentions a critical component of successfully implementing a data catalog:your data catalog won’t be complete unless you partner it with a data governance solution, like ALTR. “Data governance allows your data citizens — and that’s everyone in your organization — to create value from data assets.”

Collibra continues on by explaining that data catalogs and data governance go hand in hand, but you won’t have complete data protection and accessibility without one or the other. They mention that “A data catalog creates and maintains an inventory of an enterprise’s data assets across its entire digital environment… A data catalog provides a reliable solution for the discovery, description, and organization of data sets,” while, “Data governance is the practice of managing and organizing data and processes to enable collaboration and compliant access to data.”

Snowflake: How Implementing a Data Catalog Optimizes Your Snowflake Data Cloud Migration

Juan Sequeda, Principal Scientist at data.world, a Snowflake partner, wrote about how you can optimize your Snowflake data cloud migration with a data cloud. Sequeda explains that often, migration to Snowflake’s Data Cloud is done without intention or thoughtfulness, leaving many people to fall into a “lift and shift” approach, meaning they sloppily copy all data to the cloud, likely including errors and messy data. The solution to this, Sequeda explains, lies in implementing a data catalog — empowering your organization to have a better inventory of your data before, during, and after migration to the cloud.

Sequeda explains the key differences of data catalogs and describing a few key capabilities you should be mindful of when choosing a data catalog. A unique topic that this blog expands on is the intersection of high-value and low-complexity data. Sequeda writes that the sweet spot for your cloud data migration lies in figuring out, “what data is most important, what data is of the highest business value, and what data sees the most use.”

Conclusion

There is no doubt that data catalogs are beneficial, but they are just the first step to a fully operational data governance solution, and our partners agree that the best implementation of a data catalog is side-by-side with a scalable, simple, SaaS based data governance solution.

ALTR’s cloud data governance solution allows you to automatically discover, classify, and tag sensitive data with a checkbox in our no-code interface. We allow you to see what data is used, by whom, when, and how much with our industry-first interactive data usage heat maps and drill-down analytics dashboards. You’re able to control access to your sensitive data with classification-based policies so only approved users can see it, while quickly applying flexible, dynamic data masking over PII like social security numbers or email addresses to keep sensitive data private. It’s all part of ensuring data is governed securely from database to data catalog to data user.

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