It has become critical for enterprises to embrace data-driven decision-making to accelerate operational efficiency, reduce costs and achieve competitive advantage. The impact of the novel coronavirus makes this even more imperative.

As such, many enterprises are increasing their focus on real-time data processing to complement investments in batch processing. Adopting real-time data processing can present significant challenges to companies that are used to making decisions using traditional batch approaches; embracing real-time data processing and analytics isn’t as simple as adopting event and stream processing technologies. Cultural and organizational change are also ingredients of real-time decision-making.

DataOps has emerged in recent years as a driver of the cultural and organizational change that enables enterprises to realize the potential advantages of real-time data processing and analytics. DataOps provides a platform for improved observability of data processing pipelines and collaboration among the participants in the decision making process. 451 Research survey data indicates that the adoption of DataOps is growing rapidly, with 72% of respondents agreeing that their organization is investing in DataOps. That figure rises to 85% at those companies for which nearly all strategic decisions are data-driven.

DataOps Adoption at the Most Data-Driven Companies is Higher than Average

My organization is investing in DataOps. Strategic decisions at my organization are currently ‘data-driven.’

While the definition of DataOps is evolving, many of the key concepts behind DataOps are being widely adopted to reduce data friction, which occurs when the demands of data consumers (such as data analysts, developers and senior decision-makers) are not aligned with those of data operators (data management and IT professionals). DataOps enables engineering teams to change focus from building and managing data platform infrastructure to leveraging cloud and turnkey data services that prioritize business outcomes. DataOps supports improved data privacy and ethics through higher levels of data and application transparency.

Business Impact

  • DATAOPS ACCELERATES THE DEVELOPMENT OF DATA-INTENSIVE APPLICATIONS designed to provide the benefits of data-driven decision-making, including improved efficiency through lower costs and automated business processes, as well as the derivation of new value through the development of new and improved products and services, enhanced customer service and increased sales.
  • DATAOPS IS INSTRUMENTAL IN THE ADOPTION OF NEW DATA PLATFORMS (including stream data processing and microservices architecture, as well as modern approaches to batch data processing) across any physical, virtual or cloud infrastructure. This enables adopters to combine the benefits of analyzing both real-time and historical data regardless of the underlying infrastructure.
  • A FUNDAMENTAL BENEFIT OF DATAOPS IS GREATER COLLABORATION between data consumers (e.g., data analysts, developers and senior decision-makers) and data operators (e.g., data management and IT professionals), reducing friction and the time taken to provision data platforms for analytics projects and generate business insight.
  • DATAOPS HELPS MAKE DATA GOVERNANCE AN ENABLER OF BUSINESS VALUE, allowing organizations to deliver compliance with regulatory requirements as well as a trusted platform for self-service data preparation and analytics, decreasing time to insight.
  • INCREASED DATA AND APPLICATION TRANSPARENCY PROVIDES A BETTER UNDERSTANDING OF HOW DATA IS BEING USED within the organization and the many initiatives that span multiple infrastructure and data processing technologies, raising the potential for more ethical use of data.

In many organizations, the IT group has traditionally acted as a gatekeeper to analytics insight responsible for reports, data models and data warehouses as well as building microservices and streaming data pipelines in response to demand from business users. This traditional approach is unsuitable for driving real-time decision-making on large volumes of live data. Given this, organizations must focus on delivering self-service data access to data consumers (data analysts, product teams, developers and senior decision-makers).

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DataOps: Fueling the Success of Modern Data Platform Initiatives

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