What are data lakes and how are they used for big data analytics? A definition and description of data lakes, how they work and what are their benefits, drivers and disadvantages.
To make a big data project succeed you need at least two things: knowing what (blended) actionable data you need for your desired outcomes and getting the right data to analyze and leverage in order to achieve those outcomes.
That much seems obvious. However, as you know we have ever more data coming from ever more sources and in ever more forms and shapes. Big data indeed. As you also know this volume of data, nor the variety and so forth are about to decline any time soon. Well on the contrary.
Data lakes as a way to end data silos in a fast growing and increasingly unstructured big data universe
Just look at the Internet of Things, where mainly the Industrial Internet of Things is poised to grow fast the coming years.
And with that growth indeed comes more data or better: data is what we are after with the Internet of Things, in order to gain big insights and drive relevant actions and operations to achieve whatever outcome: big data analytics with a purpose; smart data for smart applications.
This article originally appeared in i-scoop. To read the full article, click here.