Understanding what a data lake is and what it needs to do is as important as understanding how to technically build it. A strong data lake strategy must be grounded in business goals and iteratively developed to ensure the platform provides value now and into the future.

As enterprise organizations look to comprehend and capitalize upon the opportunities presented by growing, in volume and number, data sources, capabilities of modern BI technologies and sophistication of user demands, it’s important to think about where a data lake may add organizational value.

To provide value, a data lake should be flexible, adaptable and built in a way so it can evolve as data and analytics needs to develop and grow. In this recorded webcast, Thorogood Consultant Ben Dunmire shares considerations on implementing a robust strategy to drive the design and implementation of a data lake solution to provide high business value. By understanding common challenges, identifying existing synergies, and planning for future opportunities, a data lake or similar solution can be leveraged for various business functions as data and analytic needs evolve.

What we cover:

Drawing from our own client experiences, we demonstrate:

• How to balance solution flexibility and responsiveness with development guidelines and technical structures in a data lake.
• Common pain points and bottlenecks that organizations experience with data lakes, and how to mitigate those risks during solution strategizing.
• Enlightening questions and topics to explore with business groups and stakeholders which provide valuable insights when developing a data lake strategy.
• How to identify synergies with existing data assets and recognize where asks for future phases and future enhancements may come from.

Is it for you?

• Are you in the process of exploring data lake technology options to maximize the use of your organization’s data?
• Have you begun designing or implementing a data lake?
• Are you interested in learning how to seamlessly integrate a data lake and enhance your organization’s existing data ecosystem?
• Is your organization interested in capturing and experimenting with a broader array of data with modern tools?