What is DataOps-IST & Why Do You Need It?

In the technology world, things change quickly. It’s common knowledge, so we don’t feel there’s a huge need to convince people of the fact. Often times, there are buzz words which surface and catch on like rampant wildfire: there’s no escaping it. Some of these continue on and become verifiable domains and others wither and are quickly extinguished.

One word (or domain) which has certainly taken root in an abundance of phenomenal technology and devices is Data; big, small or any size between, it’s simply data and we have plenty of it. The theme that follows is our belief that Data needs it’s own domain and cannot exist without a solid foundation in, well, Data.

There are domains which serve to enhance and support the DataOps realm. Some examples: IT, Development and Engineering are a few that, in some form, support a piece of the larger DataOps domain. Companies abound with Analysts and reporting experts but there is no specific focus on the merit and value of Data as a whole. We propose that without a focus on Data, businesses will fail to realize the bigger picture in which each piece of the organization connects to the other.

DataOps, and more specifically, DataOps-IST is simple and involves three foundational pillars:

  • Infrastructure: Data and an appropriate Analytics Infrastructure (Tableau in our case)
  • Social Engineering (and Research)
  • Toolmaking & Delivery

DataOps (1)

Between each pillar, there are the obvious feedback loops wherein each connects to the other and serves to enhance and support the domain. Around the domain exists a logging and monitoring aspect; we want to know how well and to what extent we are serving our customers. For this function, we use Logentries to answer questions such as:

  • Who is using our particular report and what are the load times?
  • Where are there gaps in performance?Is it hardware or report related?
  • Can we potentially remove parts of a report/dashboard because of performance?
  • Can we, in real time, monitor a new report and quickly (also in real time) update parts which are not performing?

Again, the domain monitoring is critical since it enhances how we discuss progress and future enhancements with customers.

In the DataOps domain, there is a vast opportunity, mostly because of the natural growth of other fields, to firmly establish a pattern of analytics and data in any organization (big and small).   We are in a transitional time where the technology has promoted the growth of analytics as a separate, yet, equally foundational part of any company.

Look for further updates on the topic. We’ll start to discuss the specifics of each pillar and why it’s important to leverage them correctly, not to mention the functionality which makes each uniquely DataOps-oriented.

Enjoy!

 

 This post was originally published on blog.logentries.com in April 2015.

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