Please enjoy this quick ILTACON 2023 summary/takeaway of session "Why the Time Is Now; A Central Repository for All Your Firm Data."
Presenters: Tom Baldwin, CEO, Entegrata; Paul Casey, Data Operations and Analytics Manager, Frost Brown Todd LLP; Reanna Martinez, Solutions Manager, Munger Tolles & Olson LLP; Stacy Rushing, Senior KM and Data Analytics Counsel, Fisher Phillips.
The goals of the session were to provide attendees with an understanding of: 1) why developing a Data Lake for all a firm's data can help simplify the integration process, and create a central data repository, which can then be leveraged for firm-wide reporting, data integration, and data backup/archiving; 2) why there is an increasing need across industries for the centralization of data; and 3) how centralization of data improves data integrity and consistency, reduces data loss, helps limit security and reputational risks, and assists in the elimination of duplicative efforts for data capture and management.
In furtherance of these goals, the presenters used a question-and-answer format, with Mr. Baldwin eliciting information from each of the others about each of five (5) subtopics: 1) Why now; 2) The Approach; 3) Benefits; 4) Lessons Learned; and 5) Operationalization. The order in which these subtopics were addressed during the session was determined by the results of a digital poll that asked the attendees to rank each of the subtopics in order of interest.
1. The Approach: What are the first steps to focus on to ensure success in your data lake project? The approach should be outcome-driven, begin with what you want to power. Go for the Minimum Viable Product. It helps keep you on track and deliver on time. Gain leadership support by quickly showing value. Build upon wins. Define the Project and Resources - scope both the short-term and long-term project requirements, goals, and timelines. Important considerations include Data Strategy, Data Governance, Data Architecture, Data Integration, Scalability & Performance, Security & Privacy, Data Lake Operations, Change Management & Collaboration, Data Access & Analytics, Metadata Management, Analytics & Tools, and Skills & Resources.
2. Lessons Learned: The primary takeaways from the Lessons Learned portion of the session were: (1) don't let perfection be the enemy of good; and (2) trust but verify. First and foremost, it's essential to remember that perfection should never become the enemy of progress. Data lakes offer vast potential for insights and efficiencies, but the pursuit of perfection can lead to paralysis. Instead, focus on achieving a functional and adaptable data lake that evolves with your needs.
Secondly, "trust but verify" emerges as a fundamental principle in data management. While it's crucial to trust the data sources and processes, maintaining a continuous verification process is equally essential. Rigorous data quality checks and regular audits can help ensure that your data lake remains a reliable foundation for informed decision-making. These lessons remind us that while data lakes can be powerful tools, a balanced approach and ongoing diligence are key to their successful implementation in the legal industry.
3. Operationalization: How to manage your data lake after it's been built. Ms. Rushing showed how her firm built an internal data lake and management system, Ms. Martinez detailed her firm’s Azure data lake interface, and Mr. Casey explained his firm’s use of Snowflake as a data warehouse.
4. Benefits: What are the (not so obvious) benefits of implementing a data lake? Benefits of having a central repository of firm data include Data on Demand, Data Normalization, Speed to Market, and Forecasting capabilities. Common “Pain Points” that a data lake can help eliminate encompass Data Silos, Data Integration Challenges, Scalability & Storage Costs, Analytical Agility, Advanced Analytics & Machine Learning, and Data Governance & Security.
5. Why Now: Talking points for market conditions and driving buy-in to your data lake project.
The presentation concluded with an animated video, created by Ms. Rushing and her FP KM colleagues, demonstrating the path a byte of data might travel to and from a data lake. A brief period for audience questions followed.