If the value of efficient business processes is obvious, it makes sense to us process data mining to improve DevOps. Here’s how you can…

How to use process data mining to improve DevOps
How to use process data mining to improve DevOps

Process data mining shows specifics about processes and their effects, equipping DevOps professionals with the ability to recognise which changes should occur to help the team excel and avoid wasting resources to figure out how to make improvements.

DevOps combines the information technology and software development teams and increases communication and collaboration between the two groups.

With DevOps, then, it becomes possible to adopt an approach to project management that allows for shorter times between new versions of apps or other products. As such, DevOps encourages continual evolution brought about by team or client needs and feedback.

Something called process data mining — analysing large amounts of data about processes and taking action accordingly — could enhance DevOps practices in several ways.

Here are five ways that leaders and IT professionals can apply process data mining to DevOps:

  1. Let process data mining reduce decisions made on gut instinct or opinions
  2. Explore insights gleaned from process data mining before making major workflow changes
  3. Let process data mining reveal the gap between the real and ideal
  4. Stop only relying on periodic reporting for decision making
  5. Include process data mining in audit preparation

Most teams don’t know where the problems in their processes exist, or they may go through trial and error to fix known problems. This shows specifics about processes and their effects, equipping DevOps professionals with the ability to recognise which changes should occur to help the team excel and avoid wasting resources to figure out how to make improvements.

This article originally appeared on information-age.com.  To read the full article, click here.

Nastel Technologies uses machine learning to detect anomalies, behavior and sentiment, accelerate decisions, satisfy customers, innovate continuously.  To answer business-centric questions and provide actionable guidance for decision-makers, Nastel’s AutoPilot® for Analytics fuses:

  • Advanced predictive anomaly detection, Bayesian Classification and other machine learning algorithms
  • Raw information handling and analytics speed
  • End-to-end business transaction tracking that spans technologies, tiers, and organizations
  • Intuitive, easy-to-use data visualizations and dashboards

If you would like to learn more, click here