Build a DataOps environment to enhance your

operational team's performance

Data Operations (DataOps) is the latest agile operations methodology and one we use here at Intergence as it’s a huge differentiator for our managed service customers.  Essentially, It focuses on cultivating data management practices and processes, that improve the speed and accuracy of analytics. These include; data access, quality control, automation, orchestration, integration, and, ultimately, model deployment and management.

 

At its core is Stratiam DataOps with its unique iSEE (integrated Service Exchange Engine) layer that can orchestrate multiple underlying sources of data to surface blended visualisations which can be used by everyone. 

So What’s the Benefit?

  • Everyone benefits - by making more data available, you gain clearer insight into business performance which ultimately steers developments into producing higher profitability

  • Stratiam DataOps fosters collaboration between your teams and your data. Having an agile data-driven approach exceeds business service expectation

  • With blended visualisations the business can start to disrupt the markets it operates in, staying ahead of the curve, maintaining relevancy and driving profitability

Only companies that embrace this approach will fall under the Stratiam DataOps umbrella

How do I start Implementing Stratiam DataOps?

 

Intergence has developed a framework that enables you to garner real value from the underlying data of your organisation’s many, many data sources.

Collaboration, integration, automation, machine learning, and governance are a few key areas of focus for embracing a DataOps environment.

  • Identify your Data - Having a constant stream of new data is essential for machine learning to improve intelligence. Datasets need to be readily available for tapping into their richness

  • Open APIs – Integration into your identified data sets is of paramount importance for automation and harvesting of that data into one platform

  • Automate & Orchestrate - Essential for self-sufficiency, it’s imperative that you automate steps which usually require lots of manual effort, to provide a constant analytics pipeline for monitoring

  • Governance – A larger proportion of companies are now taking a ‘Centre of Excellence’ approach to DataOps Service Management. Until you’ve established a blueprint for success that addresses the processes, tools, infrastructure, priorities, and KPI’s, it’s unlikely you’ll get the return on investment you were expecting

  • Smash the Silos - Collaboration is essential to implementing DataOps. The tools and platforms you embrace as part of the DataOps journey should support a larger goal of bringing teams together to use data more effectively.

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