How large is your Hadoop data lake? 500 terabytes? A petabyte? Even more? And it is certainly growing, bit by bit, day after day. What began as inexpensive big data infrastructure now demands ever more expenditures on storage and servers while becoming increasingly unwieldy and expensive to manage. Such rapacity makes it ever harder to realize a proper return on investment from that Hadoop infrastructure.

On December 8th, it was time for the annual “State of the Union” from Qlik, with regards to BI & Data Trends. Overwhelmingly, attendance was in the many thousands, and we received thousands of questions. To get that type of engagement in a year where people have done nothing but virtual conferences is amazing. One person put it to me like this: “I just joined in on your webinar on the top data and analytics trends and it was truly fantastic.

The problem with modern analytics is that it overpromises and underdelivers. We can even quantify the disappointment: This begs the question: why even bother with analytics? Well, when analytics is done right, it pays back $13.01 for every dollar spent. In fact, data-driven companies outperform their competitors in almost every conceivable way. We have broached the topic of extracting value from data before, from how to set up the right data strategy to building a data-driven culture.

In my last two blogs (Get to Know Your Retail Customer: Accelerating Customer Insight and Relevance, and Improving your Customer-Centric Merchandising with Location-based in-Store Merchandising) we looked at the benefits to retail in building personalized interactions by accessing both structured and unstructured data from website clicks, email and SMS opens, in-store point sale systems and past purchased behaviors.

2021 is the year of the Data Cloud. Powered by the Snowflake platform, the Data Cloud will be the place where organizations across industries can converge to mobilize their data. Snowflake estimates that there are still hundreds of millions of data sets isolated in cloud data storage and on-premises data centers globally. The Data Cloud eliminates these silos, allowing you to seamlessly unify, analyze, and share your data to reach deeper insights and even open new revenue streams.

We have three big announcements to our community today, and I wanted to talk to you about them: One, Allegro Trains is changing its name, two, we’re adding a completely new way to use Trains, and three, we’re announcing a bunch of features that make Trains an even better product for you! Read all about it on our blog at Clear.ml, our new website for our open source suite of tools.

Artificial intelligence and machine learning are relentlessly revolutionizing marketplaces and ushering in radical, disruptive changes that threaten incumbent companies with obsolescence. To maintain a competitive edge and gain entry into new business segments, many companies are racing to build and deploy AI applications.

Once, dashboards and reports were limited to being embedded into our apps as standalone modules - essentially, as separately accessed product features. This limitation sometimes meant analytics is forgotten by users, and more often than not, underutilized in its potential. Today, contextual analytics makes it possible to embed analytics directly into the core workflow of your software.