When Agile Meets Data Analytics | Everything You Need to Know About DataOps

What Is DataOps? 

DataOps is an automated, process-oriented methodology that ensures optimal utilization of data in a company with the use of better tools, automation, and collaboration. The primary purpose of DataOps is to align data management tools and processes with data goals and improve communication and integration between data managers and the end-users who utilize data. 

Concisely, DataOps is derived from the principles of DevOps – an approach to more agile and collaborative software development to speed up building lifecycles – it applies those principles and processes to data analytics. DataOps encourages improvement and innovation by introducing the concepts of agile development into the world of data analytics, so data teams and the users who work with data can collaborate effectively to create a smooth, hassle-free data pipeline. 

Read More: Top Best Practices and Trends for Managing DevOps in 2021

Deploying DataOps improves the speed and accuracy of data analytics across a company – including data quality, access to data, automation, integration, and development and deployment of data products and applications. DataOps practitioners, who can come from several different departments, engage with teams of data scientists, analysts, engineers, and developers to create cross-functional collaboration and increase the pace of their data-driven deployments and initiatives. 

Major Benefits of DataOps 

  • DataOps methodologies lead to better and cleaner data, which leads to improved analysis and business insights. 
  • Improving collaboration between different parts of the technical team – including engineers and data scientists helps companies access and leverage data better, in considerably less time. 
  • Organizations that take an agile approach to data science are four times more likely to hit their financial goals. 
  • DataOps makes data more manageable and accessible for its biggest users. Many times, these users are data scientists or analysts who are not as technically savvy as engineers, and they need tools and processes for getting the data they need as efficiently as possible so they can focus on their primary jobs. 
  • Creation and management of central repositories for application data and data models allow for more detailed layers of analytics for organizations. 
  • Companies that deploy DataOps can reduce the cost of data management. 

Read More: 5 Ways DevSecOps can Manage Software Supply Chains

    DataOps for Leaders 

    Effective deployment of DataOps provides teams with a more agile, collaborative, efficient approach to managing and automating the flow of data, so stakeholders can get the data they need, when they need it, in a way that works for them. 

    As companies ease into democratizing their data and giving users more self-service ways to get data without needing to involve IT or engineering teams, it is predicted that more and more companies will deploy DataOps methodologies to keep processes running smoothly and optimize their data analytics processes as much as possible. 

    Strategic Systems International’s team of 450+ professionals provides our clients with a full range of software engineering and consultancy services. Please contact us at sales@ssidecisions.com to explore how your business can benefit from DataOps. E-mail to book a free consultation now!

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