Data Lake vs Data Warehouse: What is the difference and why do you need both?

FAQ6: What is the difference between data lake and data warehouse
In the previous blog <<What is a Data Lake & a Data Warehouse?>>, we’ve introduced about data lake and data warehouse. You may want to know what is the difference between data lake and data warehouse?
Data lake and data warehouse are both widely used for storing big data. Data lake is used to store big data of all structures and its purpose has not been defined yet. Data warehouse is used to analyze archived structured data, filtered data that has been processed for a specific purpose. Data warehouse has been an integral part of the companies in the IT field, and now the data lake is causing ripples and changing the data management domain to a large extent. In this post, we will introduce the differences between a data lake and a data warehouse.

FAQ7: What can data lake and data warehouse work together?
Organizations use data warehouse and data lake to store, manage and analyze data. Data lake will not replace data warehouse, rather the two options are complements to one another. If the business stakeholders need certain pieces of information or analyze specific data, the data warehouse is sufficient. As enterprises begin to collect more types of data, and want to explore more possibilities from it, the data lake becomes a crucial addition. If the data lake and data warehouse are combined to accommodate and analyze the data, it will become a powerful tool and change the way companies derive value from the data.

2020-06-17T18:20:48+00:00 2020/06/17 |Insights|