As data is universally important and has a major role in decision-making and other business operations, a strong data-driven culture has become extremely important for business organisations.
This calls for a successful and efficient DataOps framework. Let us explore more about this emerging methodology.
Creating a Successful DataOps
Framework for Your Business
The current pandemic has pointed out that businesses must be prepared to face unexpected
challenges. It has also made it very evident that businesses must be equipped with the best
technologies and ideas that can help them sustain themselves during these challenging times.
As data is universally important and has a major role in decision-making and other business
operations, a strong data-driven culture has become extremely important for business
organisations.
This calls for a successful and efficient DataOps framework. Let us explore more about this
emerging methodology.
DataOps: What Is It?
The concept is quite similar to DevOps, which brings together Development and Operational
processes. Similarly, DataOps refers to improved data management by bringing together
different teams like data scientists, DevOps practitioners as well as data engineers.
The fact that data architecture is quite complex cannot be ignored. An enormous volume of data
needs to be collected, analysed, organised, aggregated, and even cleaned repeatedly. It
becomes quite challenging and consumes a good deal of time as well as effort.
As a result, a structured process can be drafted that helps in better decision-making. Also, data
compliance can be ensured, and data analytics challenges can be resolved.
A structured framework and collaboration between teams can help standardise these
processes, which will also improve productivity.
A Successful DataOps Framework
The three main components of data pipelines are :
● Data Ingestion
● Data Engineering
● Data Analytics
With DataOps, these components can be integrated for efficient processing. As a result,
complex and hybrid data architectures can also be managed efficiently through a unified model.
DataOps for Business
For successful data analysis, data operations, processing and data compliance, it is important
for businesses to invest in technology and processes. Some of the important components that
can help in creating a successful fram