In todays world of data science, there is increasingly urgent need for data storage for future transformation and deployment. One of the ways by which this is done is by what is called a data lake and data warehouse. Data lake is storage and collection of unrefined data i.e, data in its native form, with limited transformation captured from a diverse array of source systems.
In its most basic definition, data lake is a system or repository of data stored in its natural or raw format, usually object or files. It is a huge store of data including raw copies of source system data, sensor data, social data etc. It could also mean so many things to different people.
What you should know.
The terms data warehouse and data lake are often misleading but are totally different, though their popularity with large enterprises is similar. A research conducted by Gartner shows that about 80% of enterprises use data warehouses or plan to use them in the next 12 months, while 73% use or plan to use data lakes in a similar time period.
Data lakes are set up to capture much or all the data that an enterprise generates not just data that is needed for specific types of queries. All manner of data including those from relevant sources and irrelevant are poured into the data lake without any kind of being processed or transformed.
What you must know.
Data lakes makes it a lot more easier to handle a new stream of data because no transformations need to be done, and it also means that data lakes are so big that you can call on them for immediate processing when an urgent analytics is deployed to solve a peculiar problems.
In most cases, they are kept indefinitely, in case it is needed in the future, this is in contrast to data in data warehouses which are often subjected to a lifecycle that means that it is discarded after a certain period of time or even transferred to a data lake for future and indefinite storage.
One of the major importance of this is for easy deployment and analytics purposes. It also gives an organisation immediate access to large volume of data which could be turned into a veritable tool for immediate problem solving.
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