We explore the concept of a data lake (DL), big data fabric, DL architecture and various layers of a DL. We also present various components of each of the layers that exist in a DL. We compare and contrast the notion of data warehouses and DLs concerning some key characteristics. Moreover, we explore various commercial- and open-source-based DLs with their strengths and limitations. Also, we discuss some of the key best practices for DLs. Further, we present two case studies of DLs: Lumada data lake (LDL) and Temenos data lake (TDL) for digital banking. Finally, we explore some of the crucial challenges that are facing in the formation of DLs.
The role of data lake in big data analytics: recent developments and challenges, Page 1 of 2
< Previous page Next page > /docserver/preview/fulltext/books/pc/pbpc037f/PBPC037F_ch3-1.gif /docserver/preview/fulltext/books/pc/pbpc037f/PBPC037F_ch3-2.gif