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Sailing Through Uncertainty: Building the Law Firm Lakehouse

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Manage episode 510581596 series 3669344
Content provided by Entegrata and Tom Baldwin. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Entegrata and Tom Baldwin or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

What makes a modern data platform actually work inside a law firm?

In this episode, Mark Thorogood, Director of Enterprise Data Operations & Software Engineering at Perkins Coie LLP, breaks down how his team moved beyond on-prem constraints to a DIY lakehouse and logical data fabric that unify insights across the firm. Drawing on lessons from the army and time at sea, Mark explains why standards, simplicity, and focusing on “critical data elements” beat boiling the ocean, and how a business glossary (not just a data dictionary) turns data into decisions.

Mark also shares the nuts and bolts: Databricks and Microsoft Fabric on Delta/Parquet, Denodo for virtualization, and Power BI on the front end, plus the outcomes that matter (costs cut to one-fifteenth, 12× more finished rows, and cycle times moving from months to sprints). We get into API realities (why you’ll cache), medallion-style layers (including their “copper” tier), portfolio-level budgeting beyond matter records, and what’s next with agentic AI producing defensible, explainable analyses across practice groups.

Timestamps:

(00:00) Intro

(01:34) Mark's career journey

(02:48) Lessons from the Army and sailing

(05:09) Leadership and team building

(06:21) The importance of data

(08:27) Building a data platform

(12:52) Implementing a lakehouse

(16:03) Architecture inspiration and choices

(17:47) Business glossary vs. Data dictionary

(22:03) Challenges in scaling and API performance

(23:24) Utilizing API data for enrichment

(26:37) Building and managing a data team

(28:52) Client portfolio budgets and AI integration

(30:43) Future of data analytics and AI in legal

(35:18) Virtualization and semantic layers

(36:50) Resistance to change and overcoming it

(38:57) Practical tips for data platform transition

Connect with our guest:

Connect with Tom:

  continue reading

7 episodes

Artwork
iconShare
 
Manage episode 510581596 series 3669344
Content provided by Entegrata and Tom Baldwin. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Entegrata and Tom Baldwin or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

What makes a modern data platform actually work inside a law firm?

In this episode, Mark Thorogood, Director of Enterprise Data Operations & Software Engineering at Perkins Coie LLP, breaks down how his team moved beyond on-prem constraints to a DIY lakehouse and logical data fabric that unify insights across the firm. Drawing on lessons from the army and time at sea, Mark explains why standards, simplicity, and focusing on “critical data elements” beat boiling the ocean, and how a business glossary (not just a data dictionary) turns data into decisions.

Mark also shares the nuts and bolts: Databricks and Microsoft Fabric on Delta/Parquet, Denodo for virtualization, and Power BI on the front end, plus the outcomes that matter (costs cut to one-fifteenth, 12× more finished rows, and cycle times moving from months to sprints). We get into API realities (why you’ll cache), medallion-style layers (including their “copper” tier), portfolio-level budgeting beyond matter records, and what’s next with agentic AI producing defensible, explainable analyses across practice groups.

Timestamps:

(00:00) Intro

(01:34) Mark's career journey

(02:48) Lessons from the Army and sailing

(05:09) Leadership and team building

(06:21) The importance of data

(08:27) Building a data platform

(12:52) Implementing a lakehouse

(16:03) Architecture inspiration and choices

(17:47) Business glossary vs. Data dictionary

(22:03) Challenges in scaling and API performance

(23:24) Utilizing API data for enrichment

(26:37) Building and managing a data team

(28:52) Client portfolio budgets and AI integration

(30:43) Future of data analytics and AI in legal

(35:18) Virtualization and semantic layers

(36:50) Resistance to change and overcoming it

(38:57) Practical tips for data platform transition

Connect with our guest:

Connect with Tom:

  continue reading

7 episodes

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