DataOps, short for Data Operations is a modern approach to data management that focuses on improving coordination between data science and operations. In the recent years, digital transformation which includes adoption of cloud architecture and work from anyhwere or distributed workforce results in the production of massive amount of data. While the term DataOps is actually not recent where its introduction happened years ago in 2014, significantly, with various types of data needed to be processed and analysed, DataOps is growing its value in enterprises. What are the benefits of DataOps in organisation?
The benefits of DataOps include:
1. Enhance workforce efficiency
At its core, DataOps mainly focuses on automation automation and process-oriented methodologies. With DataOps bringing testing and observation mechanisms into the analytics pipeline, employee can spend more time on strategic task instead of hovering over spreadsheets or mundane task.
2. Higher Quality data
Human errors can affect the quality of data. DataOps approach which involves automated, repeatable processes and automates code checks and controlled rollouts dismisses human errors that may be distributed to multiple servers thus prevents inaccurate results.
3. Simplify Cloud Migration Process
Cloud migrations had gradually becoming the next normal in industry. Organisation are aiming towards being cloud-native to take full advantage of their cloud migration project. DataOps which combines DevOps, Agile Development, and lean manufacturing into its platforms automates workflows on both on-premises and cloud architecture. This helps eliminate errors, reduces product lifecycle span, and promotes seamless collaboration between data teams and stakeholders.
4. Enhance Visibility on Dataflow
DataOps are able to generate macro view of dataflow which is impossible to be obtained through constant analysis to abnormalities and errors using manual processes. The macro view being revealed includes adoption rate of services or features, search pattern as well as behavioural or geographic patterns.
5. Quicker Access to Actionable Business Intelligence
DataOps enhances agility as it removes toil and increases data quality. Through automation of data ingestion, processing, analytics and also elimination of data errors, DataOps enable instant delivery of valuable insights into customer behavioural patterns, market shift, price fluctuation and many more, thus allowing quicker Access to actionable Business Intelligence.
6. Career Advancement
DataOps opens doors to professional growth. Data analytics and operations professionals who learn the implementation and management of DataOps processes will then able to become leaders of the next generation of data teams. In addition, DataOps improves employee experiences as it replaces the once repetitive and monotonous task into a fast-moving and innovative workflow.
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Related post that may interest you:
1. What is DataOps – Origin, Evolution and Future
2. Toward the data-driven enterprise
