We’ve reached the end of our Back to Basics: Data Catalog Webinar Series! Hopefully, you were able to join us for one or more episodes and gained a solid understanding of data catalog essentials along the way.
In our initial episode, we kicked off the series by answering fundamental questions such as “What is a data catalog?” and “Why do you need a data catalog?” In subsequent episodes, we explored some of the key capabilities of data catalogs, including data discovery, data lineage, and data asset analytics.
To wrap up the series, the fifth and final episode featured our data catalog and data and analytics governance experts along with another special guest. Each panelist shared their thoughts regarding how a data catalog and its key capabilities support a broader data and analytics governance program.
If you couldn’t join us live for Episode 5: Data and Analytics Governance, you can catch the replay on demand. We’ve also summarized some of the key takeaways from the immensely informative discussion:
1. Elements of a Successful Data and Analytics Governance Program Include Collaboration, Trust and Scale
Not surprisingly, collaboration among teams, especially between technical and business stakeholders, is critical to the success of any enterprise-wide data and analytics program. Teams must be able to work together and communicate regularly to align on goals and workflows, share best practices, and prioritize areas for improvement, for example.
Trust is another important element for successful data and analytics governance. Data consumers having access to clean and trustworthy data is one of the primary outputs of a functional program.
Finally, scale is an additional necessary element for governing data and analytics. Although organizations should start small with their governance initiatives, they should be able to expand their efforts over time. Organizations must efficiently scale their programs to handle the volume and variety of data that needs to be governed across the wider enterprise, while continuing to meet the needs of the business.
Read more about each of these elements and how to develop a more agile, transparent and collaborative data governance program in our eBook, Reimagine Data Governance.
2. Data and Analytics Governance Is Important for Advanced Analytics and Digital Transformation Initiatives
Why do we need data and analytics governance? As more organizations continue to roll out next-generation analytics and data-driven digital transformation initiatives, they face the challenge of providing data consumers with the data and artificial intelligence (AI) models they need while remaining compliant with various policies and regulations pertaining to data privacy and security.
Data and analytics governance addresses this balancing act by helping to ensure that authorized data consumers have access to the right data and models when they need them (to make day-to-day and business-critical decisions) while minimizing risks and inefficiencies. Through coordinated strategic organizational policies, technology, etc., ultimately, governance greatly assists organizations with sharing and democratizing their data with confidence.
3. With an Intelligent Data Catalog, Organizations Can Overcome Many of the Common Challenges Encountered When Establishing and Scaling a Data and Analytics Governance Program
Some of the common challenges with establishing and scaling a data and analytics governance program are:
- Deciding where to start
- Not knowing what data exists across the enterprise
- Lack of collaboration among stakeholders
- Scaling and replacing manual/inefficient processes
Having an intelligent data catalog can help address each of these major challenges. For instance, when deciding where to start with governance, organizations first must understand what data exists across the organization. Having an intelligent data catalog allows you to scan for data across your data landscape, regardless of where it lives. Once armed with this information, along with intel regarding the data’s quality, sensitivity, usage, etc. can help prioritize where to start and develop a roadmap for where to go next.
4. A Data Marketplace Can Help Operationalize Data and Analytics Governance Best Practices
Best practices for successful data governance programs include:
- Discovering and cataloging your data assets
- Building trust with intelligent data quality
- Defining policies and business terms
- Sharing and democratizing your data
A self-service data marketplace, especially when used in conjunction with an intelligent data catalog, integrated data quality and automated data governance capabilities, can help organizations operationalize these best practices by enabling data consumers to find, understand, trust and access their data with confidence. As mentioned above, one of the highlights of a successful data and analytics governance program is being able to provide the right data consumers with the right data when they need it.
5. It’s Possible to Establish a Successful Data and Analytics Governance Program Quickly…with an Intelligent Data Catalog as a Foundation!
During our final episode, we had an opportunity to hear how Shaw Enterprises was able to establish a data and analytics governance program within 90 days. I won’t give away all the details here, but it’s a great story, and an intelligent data catalog was an essential component (of course!).
If you want to know more, be sure to watch the episode on demand. You can also read more about Shaw’s story here: Gaining Adoption and Building Momentum for Enterprise Data Governance at Shaw Industries
Watch all the previous episodes of our Back to Basics: Data Catalog Webinar series on demand
Thank you to all the panelists, guests and attendees that participated throughout our Back to Basics: Data Catalog Series! Once again, you can watch any of the previous episodes on demand. If you found these sessions valuable, don’t forget to share them with your coworkers and peers! We hope you enjoyed this series as much as we did and that you’ll join us for more of our upcoming webinars and/or live demos to learn more.