Today we’re excited and proud to announce Aginity support for the newly released Amazon Redshift Data Sharing.

With all the interest over the Snowflake IPO, I wanted to share a few thoughts. Now I am not the right person to tell you if these valuations will pay off and for whom. You’ll have to look elsewhere for investment advice.

At Aginity, we are lucky to interact with Data Analysts, Data Engineers and Data Scientists from across a wide range of industries and company sizes. It gives us a birds-eye view of some trends in data processing and the thousands of users of our SQL query applications…

It’s been an unprecedented year of growth for us at Aginity. With the recent launch of our two next-generation solutions Pro and Premium, we’ve got tens of thousands of individuals and enterprises depending on our products in their everyday workflow.

If the retirement of Netezza has you floundering, we’ve got at least one point of consolation: this doesn’t mean you have to part ways with Aginity! In addition to supporting IBM’s next generation database offerings with support coming out this year, Aginity already enables your SQL query and development workloads on 10 different databases (and counting), including cloud specialists like Azure Data Warehouse and Amazon Redshift.

It feels like every conference talk, blog post, podcast or marketing message that I get these days is touting the amazing benefits of Data Science, Machine Learning (ML) or Artificial Intelligence (AI) (or if you are old school, you probably recall the marketing and promotion of many similar techniques as “Statistical Modeling”).

Anyone who works with code knows that learning doesn’t stop when school’s out—it continues every single day. (Even on luxurious summer days!)

There is a movement that’s happening. An analytic movement. Analytics is one of the most important and valuable assets to an organization—next to you, of course. Yet we don’t seem to give analytics the love it deserves. This motivated us to take a deeper look at how we treat analytics today and how we can uncover its potential and showcase its value.

It finally happened. Your star analyst, beloved by the business for producing those top-notch analytics, just flew the nest.

In the past week, two leading tech platforms spent $18.3B acquiring business intelligence and data visualization companies.  Google acquired Looker for $2.6B, and Salesforce acquired Tableau for $15.7B. 

We all have our own ways of organizing stuff at home and at work. My friend swears by bullet journaling, my boss juggles multiple Google calendars and productivity apps, and my daughter keeps a simple to-do list. There’s no right or wrong answer here. We all have different ways of keeping a grip on our life.

It’s unavoidable—at every conference, all I seem to hear about is Artificial Intelligence (AI) and Machine Learning (ML). I can’t help but think about when I was kid and AI meant robots like C3PO from Star Wars, Chip from Not Quite Human, or Rosie the Maid from The Jetsons.