Data Logz

Suppose you assign your data team what sounds like a relatively simple task – say, determining year over year change in product sales. The first step is to identify the relevant data sets. Typically, this involves wading through a data lake (which is really just an unorganized dumping ground for data), sorting through vast amounts of data in a warehouse, contacting colleagues in different departments to ask for specific data, waiting days or weeks for it, ensuring data governance, wrangling and preparing the data, and finally performing some hasty analysis to meet a fast-approaching deadline.

Not only is this inefficient and frustrating for the data team, it also makes mistakes much more likely, keeps you in an eternal state of catch-up instead of leading the pack, and costs you between $10 - $14 million each year, according to Gartner.

With Datalogz, data discovery is more like a Google search. Analysts simply type in the keywords of the data they’re looking for, and instantly receive high-quality, relevant data resources across the entire company ecosystem, ready for immediate use in the analysis. They don’t have to wonder if the data is outdated, and they don’t have to spend hours or days searching it out and guessing the meaning behind it. They simply get straight to work uncovering the insights that keep driving the company forward.