As organizations look for opportunities to put data analytics to work, DevOps is one area that deserves attention. In many organizations, data scientists and software developers are still siloed, but bringing their talents together makes sense. Development informed by data can help teams in a number of ways.

The goal of DevOps is to shorten the time required to get ideas into practice by accelerating the development process in a quality-controlled way. Its methodology depends on a steady, reliable source of clean, organized and indexed data. Generating the right data during the DevOps process, and then using the resulting insights to inform the next iteration, can minimize error and increase the likelihood of success.

Analytics is a natural complement to the DevOps feedback loop, providing valuable insights that inform continuous improvement in decision-making. Collaboration, however, is essential. When developers know what data they need to collect, they can create code that will write logs to a file for analysts’ review. That requires not only joint planning but also clarity about what the goals are — both for development and for the business as a whole.

Increasingly, the power of data analytics is within reach for small and midsized businesses, even if they lack the in-house expertise to launch these efforts on their own. Modern data platforms, coupled with expert guidance, enable SMBs to take advantage of data-driven insights.

The caveat? Implementing sophisticated analytics is a process. Here are some key considerations for SMBs as they work to derive customized, prescriptive insights.

My colleagues and I jokingly follow the Fight Club rule when talking with business and IT leaders about artificial intelligence: The first rule of AI is you don’t talk about AI. When people hear the phrase “artificial intelligence,” they often imagine complicated, expensive solutions, their minds leaping to sci-fi cultural artifacts such as the 2001…

In the previous installment in this blog series, I discussed the practical applications of using IT Operations Analytics (ITOA) technologies in the real world. In this installment, I’ll introduce Splunk and discuss how its platform delivers the benefits of ITOA. Introducing Splunk Splunk unleashes the power of machine data to help with IT operations, application…

When I learned that one of my favorite stores had introduced the purchase option to buy online and pick up in the store (BOPIS), I was delighted. Then I tried it. I expected to be able to pick up my purchase quickly, bypassing the checkout lines. Instead, I was directed to the back of the…

In the previous installment in this series, I made the case for utilizing IT Operations Analytics (ITOA) technologies. In this post, the focus will be on the practical application of these technologies in the real world. The Benefits According to IDC, the principal benefits of IT Operations Analytics include the following: Avoidance of service interruptions,…