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What is DataOPS?

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By: Nihad Hassan

June 16, 2021

Digital transformation is rushing to occupy all business areas. In today's information age, organizations of all sizes and across all industries utilize digital solutions to facilitate work operations and enhance efficiency. The most apparent aspect of digitalization appears in the massive volume of digital data stored and processed by all organizations, from small to enterprise.

Data becomes the lifeblood of organizations, and without it, an organization will fail to deliver its services and consequently cease operations. To operate effectively, This is now integrated with most business process life cycles. If it is inaccurate or unavailable for any reason, businesses will not make informed decisions.

In today's complex IT environments, it is difficult to track data sources or data dependencies; make sure your documentations are all up to date; in addition to seeing precisely how your data flows within your systems. By following a proper DataOPS practice when developing applications and business processes, organizations will accelerate their data lifecycle and will become able to send the correct data at the right time to interested stockholders like decision-makers and end-users.

What is DataOPS?

DataOPS (data operations) is a new IT discipline first termed in 2014; it gathers a DevOps team, data engineers, data scientists, and other data professionals. DataOPS follows agile philosophy to develop or maintain data-driven applications. It helps the DevOps team in various system development phases, beginning from data collection and delivery. It fosters project delivery and allows data specialists to take their role in the early stages of system design, update or maintain applications based on data and analytics.

Similar to DevOps, DataOPS enhance communications between the different parties involved in DevOps projects; it applies the following three methodologies into data analytics and operations:

  1. Agile framework
  2. DevOps
  3. Lean manufacturing

DataOPS benefits

Similar to DevOps methodology, developing a DataOPS program within your company will bring the following advantages:

  1. Solves massive volume data problem: According to IDC, the Global Datasphere is experiencing tremendous growth and is projected to grow from 33 Zettabytes (ZB) in 2018 to 175 ZB by 2025. By applying the proper DataOPS process, the massive amount of raw data can quickly and efficiently be turned into useful information to support business objectives.
  2. Improves data analytics: DataOPS promotes using modern technologies to enhance the process. An example of such technology is utilizing machine learning algorithms to guide data through all phases of project analysis. This allows data scientists to gather, process, and classify data before shifting it to the end-users and process end-users' feedback in the shortest period.
  3. Allows businesses to understand better their stored data and their importance to different work processes.
  4. Accelerates IT project delivery by applying data automation.
  5. Enhances project testing by applying ''Production-Like'' data & patterns.
  6. Ensures Personally Identifiable Information (PII) of end-users comply with the various data protection regulations such as the European Generate Data Protection Regulation (GDPR), HIPAA, and PCI DSS.
  7. Becomes more secure from different risks targeting data.
  8. Allows catching errors quickly by running continual tests on the data while still in the pipeline to produce the desired output. For instance, incorrectly processed data can be caught early before it is passed to later project phases.
  9. Saves time for analyzing data and allows the DataOPS team to focus on other urgent issues.
  10. This Allows gaining real-time insight into your data due to speeding the entire data analysis process.
  11. Increases customer stratification by knowing what they want, when they want it, and how. By applying the DataOPS process, organizations can discover new ways to improve their services/ products and develop new ones.
  12. Enhance data collaborations between different DevOps team members.


As digital transformation accelerates rapidly, the digital ecosystems of organizations face many challenges when handling the increased volume of data. The complexity of managing it in a multi-cloud environment, different compliance regulations in addition to the siloed data problem (which makes data available to only a small group of users within an organization) that many organizations suffer from makes having a DataOPS program essential to meet this ever-growing challenge.

Keep in mind, DataOPS is a process or methodology and not a tool. Many tools are in the market to help you build your strategy. Using the right tools and understanding your needs, DataOPS will allow your organization to enhance its data operations and analytics process.

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