Introducing data lakes
Over the last few years, the markers for effective data engineering and data analytics have shifted. Up to now, organizational data has been dispersed over several internal systems (silos), each system performing analytics over its own dataset.
Additionally, it has been difficult to interface with external datasets for extending the spectrum of analytic workloads. As a result, it has been difficult for these organizations to get a unified view of their data and gain global insights.
In a world where organizations are seeking revenue diversification by fine-tuning existing processes and generating organic growth, a globally unified repository of data has become a core necessity. Data lakes solve this need by providing a unified view of data into the hands of users who can use this data to devise innovative techniques for the betterment of mankind.
The following diagram outlines the characteristics of a data lake:
Figure 2...
