Self-service analytics and data lakes have a little in common. Both are widely popular concepts that have been shaping the big data world and both offer a variety of approaches and tools. ZD Net brought this news to us in their article, “Data lakes going the way of the visual spreadsheet?”
There is also a fair amount of overlap between the two. Hadoop-based data lakes are rather common these days, but that does not make them easy to work with for the non-data science types. Self-service analytics tools try to support them as data sources their users can connect to through a layer of mediation, typically SQL-based.
However, the whole point in self-service analytics, as opposed to traditional data warehouses, is to skip the data mediation process and let users explore data sources on their own, on the fly and using visual paradigms.
Melody K. Smith
Sponsored by Access Innovations, the world leader in thesaurus, ontology, and taxonomy creation and metadata application.