As we all navigate these uncertain times, one thing has never been more certain — the need to reduce spend. Dollars saved directly equates to employees kept, strategic investments continued, and savings passed on to customers. Finding unnecessary spend and inefficiencies across the business is more important than ever before.
Data scientists and data engineers play the primary role in accelerating a company’s data sophistication, providing both the technology and domain expertise from a sea of zeros and ones into valuable data products. As we reflect on 2019 and look forward to the year and decade ahead, we will examine the evolving nature of these roles and teams.
Let’s look at how managers of data teams can set the stage for a path that fuels speed and business results, by sorting out different aspects of what needs to get accomplished, and tagging four common mistakes as killer anti-patterns.
Today’s scale of data creation and ingestion has reached magnitudes that have fueled an Icarus-like obsession with data-driven business decisions. The desire for velocity in analytical processing, machine learning, and visualization has only enlarged the gap between the vision of a data-powered intelligence engine and the actual tools used for this concept.
While your data team likely includes people with all three of these points of view, what really matters is the position of the leaders, and the pace with which the team is adapting to the real needs of the business. So while we’re rolling the dice with the alphas, let’s take a moment to look at the two sources of value in this context: data and code.
One of these emerging technologies I evaluated is Istio – named after the Greek word for sailing and backed by Google, IBM, and Lyft. Istio can be implemented within a Kubernetes cluster and proxy all the networking between the microservices.
It is a lesson that Sean Knapp, Founder and CEO at Ascend lives by. I met Sean at his Palo Alto office a few weeks ago, and as we chatted about the state of the market and how industries are shifting towards “as a Service” in almost every aspect, we found ourselves on a track about what really makes a startup successful.