Businesses are increasingly turning to data lakes as a means of addressing the challenges commonly associated with managing big data. But they face confusion and ambiguity: There is no single definitive data lake model, but rather a variety of options around how this component of the enterprise data fabric can be architected and implemented.
Much of the current discussion about data lakes centers on Hadoop, which is — without question — a core big data technology. However, an exclusive focus on Hadoop is misdirected, as would be an exclusive focus on traditional data warehousing technology.
Download this white paper to learn:
- The limitations of an EDW-only approach
- The advantages of a hybrid environment over an exclusive focus on either Hadoop or traditional data warehousing — and why it’s the most likely option for most organizations
- What a data lake is, and why this concept has attracted significant attention as an EDW alternative
- Typical deployment options of a data lake within a larger data management framework
- What solutions SAP offers for real-time operations, data warehousing, and managing big data to support implementing and managing a hybrid data lake environment
You’ll also walk through eBay’s SAP HANA implementation story, which provides an example of how the platform supports a true contextual data lake environment.