Data Warehouse, Data Lake, or Data Lakehouse, which one to choose?
This is one of the most common questions that's been asked by many data professionals!! The answer lies in many factors, but in this article, we will see some key factors that will help us assess the right solution.
Below are some key factors that we need to consider before we choose any solution
The size of the data being colected , the diversity of the data formats and types , speed at which data is being generated, produced, created, or refreshed ,the quality and accuracy of data , how much value the organization will gain from analyzing the data and the people directly or indirectly consuming the data
Unified Architecture for Data Warehouse, Data Lake, and Data Lakehouse
Below is a unified data architecture that covers the three approaches for the implementation of a data platform solution for diverse needs.
Now let's look at the each solution and see what its sutiable for
→ Tradional Data Warehouse : For Business Intelligence (BI)
→ Data Lake : For Business Intelligence (BI) and Data Science and Machine Learning ( two seperate data platforms)
→ Data Lakehouse : For Business Intelligence (BI), Stream Analaytics , Data Science and Machine Learning ( unified data platform)
In this article I described few key points in choosing the right data platform solution, but there are a lot many to look at based on your organizations strategy and roadmap.
I hope this artcle is informative, see you in my next article until then have a great time and enjoy the hot weather.