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The Modern Data Stack Conference 2023: Fireside Chat

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Building data governance into the foundation of your enterprise business fireside chat session

Modern Data Stacks and Coffee Chats

Hosted by Fivetran, The Modern Data Stack Conference explores the power and promise of data and analytics through a series of talks by industry thought leaders. The event this year featured over 30 sessions delivered over 2 days featuring keynotes from luminaries like DJ Patel, breakout sessions, and lightning talks. Topics ranged from data fabrics, orchestration, data sharing, and data governance with leaders from Snowflake, dbt, Sigma Computing, and our own founder and CEO Shinji Kim. 

The Select Star team chats with MDS conference attendees while they refuel

Fireside Chat: Building Data Governance into the Foundation of Your Enterprise Business

In a fireside chat facilitated by Mark Van de Wiel (Fivetran), Veronica Zhai (Fivetran) and Shinji Kim (Select Star) our panelists dove into an honest discussion about the role of data governance in the Modern Data Stack. Earlier that day, DJ Patel impressed upon the importance of a data catalog, pointing out that data teams can’t effectively leverage data without an understanding of the data model. Modern data governance involves more than just a data catalog – it needs aspects of data discovery, data catalog, and data observability. In addition, it is much more than just adopting new tools. It is also about realizing the full potential of people, systems, and data. 

During the panel, Veronica brought a unique viewpoint to the conversation based on her experience running the Fivetran data team and also in her previous work building out the first modern analytics team at J.P. Morgan. She spoke about the key aspects of data management to prioritize and organize your team around, including ensuring a feedback loop to hone best practices.

Shinji pointed out the main challenge to modern data governance is the explosion of data inside organizations. No longer just database primitives, SaaS applications across the business generate vast amounts of data. On top of that, data is being democratized and used in a decentralized manner across the organization, leaving data teams feeling out of control. So how should data teams think about data governance?  

4 Pillars of Data Governance

Data governance is all about balancing control vs. the enablement of your organization to better utilize company data. In order to build an effective data governance model, Veronica shared the four pillars that need to be considered:

  1. Data Access and Data Discovery: Who has access to production data? Are business and technical owners documented?
  2. Data Quality: Is your data complete? How do you deal with latency?
  3. Validity: How do you define your KPI’s? What does it mean to say “customer” or “sale”?
  4. Standardization: How do you standardize definitions across large organizations or affiliated companies? How do we ensure that everyone speaks the same language when using data?

Data Discovery at Pitney Bowes & Fivetran

One joint intersection between the speakers was engagement with the global logistics company, Pitney Bowes. Pitney Bowes is a 100-year-old company with over 700 million IoT devices tracking 17 billion parcel and mail assets with data being pushed through multiple solutions. They have gone through different phases of their data management strategy, but have now standardized on modern platforms like Snowflake, Fivetran, and Select Star. Pitney Bowes uses Fivetran to Ingest data from their Oracle finance systems and to get better access to sensor data used in their logistics operation to predict supply-chain bottlenecks. Pitney Bowes uses Select Star to implement data mesh architecture with automated data context. Select Star provides both business and technical users with a better way to find and understand the data inside their organization. 

How does a modern, data-first company like Fivetran handle its own data? Fivetran is a data-driven company consuming over 100 data sources across the business, alongside multiple BI and visualization tools. The main obstacle they found was that business users had difficulty finding the right information they needed because there was so much data available. That was the start of looking for a data discovery platform at Fivetran.

The data team at Fivetran uses Select Star to discover and manage their data. One major feature they use is column-level data lineage to understand how data is accessed and transformed on the way to its destination. If they need to deprecate an asset, they can also see the upstream and downstream dependencies and notify the proper users and owners. Read more on how Fivetran approached solving their data discovery to survive the data explosion.

Wrapping Up

As companies begin to build out their “Modern Data Stack” to handle their exploding data, it is just as important that they consider the changes needed to processes and teams. Data governance is at the center of that concern and should be implemented considering multiple factors.

Select Star is a next-generation data discovery, catalog, and governance platform enabling everyone to find and understand their data. To learn more about modern data governance and data discovery, find time with one of our experts by requesting a demo.

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