Filter By "analytics"

This blog is focused on how Imply Pivot delivers the final mile for building an anlaytics app. It showcases two customer examples - Twitch and ironsource.

For decades, analytics has been defined by the standard reporting and BI workflow, supported by the data warehouse. Now, 1000s of companies are realizing an expansion of analytics beyond reporting, which requires a new type of database.

Imply Pivot offers multi step aggregations, which is valuable for timeseries data where measures are not evenly distributed in time.

After over 30 years of working with data analytics, we’ve been witness (and sometimes participant) to three major shifts in how we find insights from data - and now we’re looking at the fourth.

Everything is going to fail. If this is your first time working with or building out a distributed system, the fact that everything is going to fail may seem like an extremely scary concept, but it is one you will always have to keep in mind.

I recently read a great article by Jeffrey Heer, Michael Bostock, and Vadim Ogievetsky that showcases the various techniques for visualizing and interacting with diverse data sets. I thought it may be useful to write something similar to showcase the various open source systems that exist in the “big data” space, including Druid, which is an open source data store I work on.

Today, Gian Merlino, Vadim Ogievetsky, and I are extremely excited to announce Imply, a company for interactive analytics at scale, centered around the Druid open source data store. We first began working on Druid at a startup called Metamarkets, and over the last few years, we’ve been proud to watch the project grow and take on a life of its own.