TECHNOLOGY
IN TODAY ’ S ENTERPRISE data world , there ’ s currently a big shift from data warehouses to the emergence of data lakes . Although data warehouses have been the foundation for business intelligence for the past several decades , data lakes are beginning to make them far less necessary .
Information in a data lake — which is a storage area that holds large amounts of raw data in its native format until it is needed — is normally either digital data or data that is relatively new to an organisation . It ’ s the information an organisation wants to capture at a relatively low cost , find out how to derive value from it and how to store it long term once they know it ’ s value . The limitation of a data warehouse is that it stores data from various sources in specific structures and categories that dictate the type of analysis possible from it .
But this doesn ’ t mean structured data warehouses are going anywhere . They will still be around to carry out the same tasks they have been doing all along , and will continue to be the downstream system of a data lake . What data lakes bring in their raw , unmuddled format is allow business analysts access to data across different
With data often so large and comple
divisions within their organisation .
When new data came along , businesses traditionally had to wait for it to be loaded into the staging layer of the data warehouse , where it would then be presented to them in one form or another . However , this becomes quite time-consuming as well as expensive .
“ Having ( information ) landed in a data lake in its raw form is a great opportunity for an analyst to access it
16 July 2015