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GenAI Deployment: Should You Start with a Data Lake?
INTERESTING ARCHITECTURE TRENDS
Lorem ipsum dolor sit amet consectetur adipiscing elit obortis arcu enim urna adipiscing praesent velit viverra. Sit semper lorem eu cursus vel hendrerit elementum orbi curabitur etiam nibh justo, lorem aliquet donec sed sit mi dignissim at ante massa mattis egestas.
- Neque sodales ut etiam sit amet nisl purus non tellus orci ac auctor.
- Adipiscing elit ut aliquam purus sit amet viverra suspendisse potenti.
- Mauris commodo quis imperdiet massa tincidunt nunc pulvinar.
- Adipiscing elit ut aliquam purus sit amet viverra suspendisse potenti.
WHY ARE THESE TRENDS COMING BACK AGAIN?
Vitae congue eu consequat ac felis lacerat vestibulum lectus mauris ultrices ursus sit amet dictum sit amet justo donec enim diam. Porttitor lacus luctus accumsan tortor posuere raesent tristique magna sit amet purus gravida quis blandit turpis.
WHAT TRENDS DO WE EXPECT TO START GROWING IN THE COMING FUTURE?
At risus viverra adipiscing at in tellus integer feugiat nisl pretium fusce id velit ut tortor sagittis orci a scelerisque purus semper eget at lectus urna duis convallis porta nibh venenatis cras sed felis eget. Neque laoreet suspendisse interdum consectetur libero id faucibus nisl donec pretium vulputate sapien nec sagittis aliquam nunc lobortis mattis aliquam faucibus purus in.
- Neque sodales ut etiam sit amet nisl purus non tellus orci ac auctor.
- Eleifend felis tristique luctus et quam massa posuere viverra elit facilisis condimentum.
- Magna nec augue velit leo curabitur sodales in feugiat pellentesque eget senectus.
- Adipiscing elit ut aliquam purus sit amet viverra suspendisse potenti .
WHY IS IMPORTANT TO STAY UP TO DATE WITH THE ARCHITECTURE TRENDS?
Dignissim adipiscing velit nam velit donec feugiat quis sociis. Fusce in vitae nibh lectus. Faucibus dictum ut in nec, convallis urna metus, gravida urna cum placerat non amet nam odio lacus mattis. Ultrices facilisis volutpat mi molestie at tempor etiam. Velit malesuada cursus a porttitor accumsan, sit scelerisque interdum tellus amet diam elementum, nunc consectetur diam aliquet ipsum ut lobortis cursus nisl lectus suspendisse ac facilisis feugiat leo pretium id rutrum urna auctor sit nunc turpis.
“Vestibulum pulvinar congue fermentum non purus morbi purus vel egestas vitae elementum viverra suspendisse placerat congue amet blandit ultrices dignissim nunc etiam proin nibh sed.”
WHAT IS YOUR NEW FAVORITE ARCHITECTURE TREND?
Eget lorem dolor sed viverra ipsum nunc aliquet bibendumelis donec et odio pellentesque diam volutpat commodo sed egestas liquam sem fringilla ut morbi tincidunt augue interdum velit euismod. Eu tincidunt tortor aliquam nulla facilisi enean sed adipiscing diam donec adipiscing ut lectus arcu bibendum at varius vel pharetra nibh venenatis cras sed felis eget.
In many recent discussions about GenAI adoption, a key question keeps coming up: Should the first step be building a big data lake for the entire organization?
It’s an understandable idea. A central data platform sounds like a strong foundation. But based on my experience, this approach is not the best way to start. Here’s why— and what we recommend instead.
Why a Data Lake Sounds Like a Good Idea
- One place for all the data – A data lake can store both structured and unstructured data, which is important for GenAI.
- Future flexibility – If you have all your data in one place, it might be easier to build new GenAI tools later.
- More insights – With access to more data, you might discover new use cases.
But while these points are valid in the long term, they aren’t strong enough to justify this as the first step.
Why a Data Lake Should Not Be the First Step
- Too expensive and slow – Building a full data lake takes a lot of time, people, tools, and money — and it won’t give you quick GenAI results.
- Low data quality risk – Without clear goals, a data lake can become a “data swamp” full of messy, hard-to-use data.
- Difficult integrations – Collecting data from different systems takes time and exposes old problems.
- Security and compliance issues – Storing all your sensitive data in one place means big security risks and complex rules to follow.
- The GenAI world is changing fast – You don’t want to invest in a big system today that might not match your real needs tomorrow.
- Context is missing – GenAI models need more than data — they need meaning. A data lake doesn’t automatically give you context or useful answers.
What’s a Better Way to Start?
Instead of starting big, we suggest beginning with a focused, use-case-first approach. That means:
- Define a small number of GenAI use cases with real business value.
- Collect and prepare only the data you need for those cases.
- Build simple, practical solutions — and show results quickly.
This way, you can:
- Show value early and get buy-in from management
- Save time and money
- Avoid large, unnecessary complexity
- Stay flexible and grow step by step
- Learn what works before scaling
Think Big. Start Smart. Scale Fast.
Yes, amore advanced data lake or lake house might be part of your long-term plan. But don’t start there. Start with one real problem. Use the data you need. Prove it works. Then move forward with confidence.
GenAI Deployment: Should You Start with a Data Lake?
INTERESTING ARCHITECTURE TRENDS
Lorem ipsum dolor sit amet consectetur adipiscing elit obortis arcu enim urna adipiscing praesent velit viverra. Sit semper lorem eu cursus vel hendrerit elementum orbi curabitur etiam nibh justo, lorem aliquet donec sed sit mi dignissim at ante massa mattis egestas.
- Neque sodales ut etiam sit amet nisl purus non tellus orci ac auctor.
- Adipiscing elit ut aliquam purus sit amet viverra suspendisse potenti.
- Mauris commodo quis imperdiet massa tincidunt nunc pulvinar.
- Adipiscing elit ut aliquam purus sit amet viverra suspendisse potenti.
WHY ARE THESE TRENDS COMING BACK AGAIN?
Vitae congue eu consequat ac felis lacerat vestibulum lectus mauris ultrices ursus sit amet dictum sit amet justo donec enim diam. Porttitor lacus luctus accumsan tortor posuere raesent tristique magna sit amet purus gravida quis blandit turpis.
WHAT TRENDS DO WE EXPECT TO START GROWING IN THE COMING FUTURE?
At risus viverra adipiscing at in tellus integer feugiat nisl pretium fusce id velit ut tortor sagittis orci a scelerisque purus semper eget at lectus urna duis convallis porta nibh venenatis cras sed felis eget. Neque laoreet suspendisse interdum consectetur libero id faucibus nisl donec pretium vulputate sapien nec sagittis aliquam nunc lobortis mattis aliquam faucibus purus in.
- Neque sodales ut etiam sit amet nisl purus non tellus orci ac auctor.
- Eleifend felis tristique luctus et quam massa posuere viverra elit facilisis condimentum.
- Magna nec augue velit leo curabitur sodales in feugiat pellentesque eget senectus.
- Adipiscing elit ut aliquam purus sit amet viverra suspendisse potenti .
WHY IS IMPORTANT TO STAY UP TO DATE WITH THE ARCHITECTURE TRENDS?
Dignissim adipiscing velit nam velit donec feugiat quis sociis. Fusce in vitae nibh lectus. Faucibus dictum ut in nec, convallis urna metus, gravida urna cum placerat non amet nam odio lacus mattis. Ultrices facilisis volutpat mi molestie at tempor etiam. Velit malesuada cursus a porttitor accumsan, sit scelerisque interdum tellus amet diam elementum, nunc consectetur diam aliquet ipsum ut lobortis cursus nisl lectus suspendisse ac facilisis feugiat leo pretium id rutrum urna auctor sit nunc turpis.
“Vestibulum pulvinar congue fermentum non purus morbi purus vel egestas vitae elementum viverra suspendisse placerat congue amet blandit ultrices dignissim nunc etiam proin nibh sed.”
WHAT IS YOUR NEW FAVORITE ARCHITECTURE TREND?
Eget lorem dolor sed viverra ipsum nunc aliquet bibendumelis donec et odio pellentesque diam volutpat commodo sed egestas liquam sem fringilla ut morbi tincidunt augue interdum velit euismod. Eu tincidunt tortor aliquam nulla facilisi enean sed adipiscing diam donec adipiscing ut lectus arcu bibendum at varius vel pharetra nibh venenatis cras sed felis eget.
In many recent discussions about GenAI adoption, a key question keeps coming up: Should the first step be building a big data lake for the entire organization?
It’s an understandable idea. A central data platform sounds like a strong foundation. But based on my experience, this approach is not the best way to start. Here’s why— and what we recommend instead.
Why a Data Lake Sounds Like a Good Idea
- One place for all the data – A data lake can store both structured and unstructured data, which is important for GenAI.
- Future flexibility – If you have all your data in one place, it might be easier to build new GenAI tools later.
- More insights – With access to more data, you might discover new use cases.
But while these points are valid in the long term, they aren’t strong enough to justify this as the first step.
Why a Data Lake Should Not Be the First Step
- Too expensive and slow – Building a full data lake takes a lot of time, people, tools, and money — and it won’t give you quick GenAI results.
- Low data quality risk – Without clear goals, a data lake can become a “data swamp” full of messy, hard-to-use data.
- Difficult integrations – Collecting data from different systems takes time and exposes old problems.
- Security and compliance issues – Storing all your sensitive data in one place means big security risks and complex rules to follow.
- The GenAI world is changing fast – You don’t want to invest in a big system today that might not match your real needs tomorrow.
- Context is missing – GenAI models need more than data — they need meaning. A data lake doesn’t automatically give you context or useful answers.
What’s a Better Way to Start?
Instead of starting big, we suggest beginning with a focused, use-case-first approach. That means:
- Define a small number of GenAI use cases with real business value.
- Collect and prepare only the data you need for those cases.
- Build simple, practical solutions — and show results quickly.
This way, you can:
- Show value early and get buy-in from management
- Save time and money
- Avoid large, unnecessary complexity
- Stay flexible and grow step by step
- Learn what works before scaling
Think Big. Start Smart. Scale Fast.
Yes, amore advanced data lake or lake house might be part of your long-term plan. But don’t start there. Start with one real problem. Use the data you need. Prove it works. Then move forward with confidence.
