A data lake is a centralized repository where businesses can store all of their structured and unstructed data. Store the data as-is, Ex. A manufacturing company can store data of all the Invoices issues to all its customers over last 5 years AS IS in a data lake.
The need for a data lake is because organizations have lots of data in various different structures and formats. In todays competive world, companies have to get insights from the data stored in this lake.
Difference between data lake and data warehouse.
Data warehouse is a database which is optimized for analyses for relational data and this data is coming from transactional systems. Here the data strucutre the schema are well defined.
Whereas data lake is different, it will store all types of data, relational data from business applications, and non relational data from iot devices, social media, logs, media, files, and much more.
The strucutre of data or schema is not defined.
As business processes mature the businesses benefits from data in data lakes, because
Data lakes allow analytics to be performed using any framework like Hadoop, Spark, or any proprietary solutions like Microsoft BI etc. Here the anlaytics can be done without the need to move data to any separate systems.
The capability to harness more and more data from more sources in lesser time and empowering users to collaborate and analyse data in all possible ways leads to better and faster decision making.
Future belongs to those businesses who harness the power of Data.
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Tony R.
