Lots of technologists are promoting replacement of data warehouse by data lake. In the view point of our data science team, a modernized data warehouse should carry its own value for the analytics nowadays.
There is an article by TDWI.org sharing the viewpoint of CEO of Yellowbrick – Neil Carson what vital technology and tools being used.
His opinion is aligning with our data science evangelist – Samuel Sum on Hadoop. It is a large-scale data store but it is not easy to access and manage in many situations. It is always better to have a structured data store like data warehouse for easy user access. Also, a key-point of a successful data analytic environment is the storage speed storing the data. With SSD (flash memory), the data warehouse (both ETL and access) are now several times faster than before.
Finally, the editor of this webpage suggests read an article of Samuel Sum – talking about the Data Lake (Data Lake VS Data Warehouse).
Our team leader / founder – Samuel Sum has written an article on his blog about Data Lake and Data Warehouse. There are lots of people trying to drop their data warehouse. However, Samuel is providing his viewpoint on the value of the data warehouse. Also, his suggestion on data lake architecture is being discussed by the real-world experiences with our professional service team.
After a number of years with Big Data, more and more people are talking about Data Lake. Hardware & software vendors are always happy to push boxes and big bills. However, there is no myth and the lake is not just a collection of “water”. The quality of the content within the data lake is the key of success. Just like a lake, you should jump into water as not swimmable.
The editorial team of the “insidebigdata.com” use swimming to describe the concept of data lake application. The article below is worth to read and understand the concepts before going ahead to the data lake.