Five Approaches to Boosting Business value with DataOps


    Data management in businesses is becoming more challenging due to the need to store and evaluate enormous amounts of data in order to acquire insights. Many firms are focusing on improving their agility to increase the pace of data processing and improve the quality of data in order to generate meaningful insights. This emphasis necessitates a flexible data management strategy, such as Data Operations (DataOps).

    The quantity of data generated and collected by organizations continues to grow, and businesses that want to expedite their end-to-end processes and get business insight can’t continue to rely on manual legacy data management methods.

    Things are simply going to get worse in the coming years. According to IDC, data will expand at a 32% Compound Annual Growth Rate (CAGR) to 180 zettabyte by 2025. DataOps, fortunately, can assist.

    The following five touch points are the most critical deliverables firms may use when integrating DataOps technologies into their business operations.

    Workforce efficiency has improved

    Essentially, DataOps is all about process-oriented approaches and automation that boost labor efficiency. Employees may focus on strategic objectives instead of wasting time examining spreadsheets or doing other tedious tasks by including testing and observation methods into the analytics pipeline.

    Getting a better understanding of data flow

    DataOps can give an aggregated picture of the whole data flow through time, across the company and out to end-users, in addition to the business-critical day-to-day insights.

    This can highlight broad patterns like product or service adoption rates or search pattern deltas over time. For specialized or global data sets, even behavioral or geographic patterns are possible. For teams that are continuously responding to anomalies and problems using manual methods, creating such a perspective would be impossible.

    Improved time to value

    Enterprises rely on the time required to transform an idea into something valuable. With its agile-based development procedures, DataOps lowers lead time. The amount of time spent waiting between stages reduces as well. Furthermore, the technique of producing and releasing solutions in tiny chunks allows solutions to be applied gradually.

    If companies use a slow process for developing data solutions, they may end up with shadow IT. Other departments create their own solutions without the consent or cooperation of the IT department.

    DataOps can speed up development by providing faster feedback to organizations through sprints. At the end of every sprint, there is a sprint review, which allows data consumers to provide continuous feedback. This feedback also adds clarity by allowing it to guide development and promote a solution that the data consumer desires.

    Career advancement in DataOps

    DataOps is a fast-expanding field of expertise. Experts in the data analytics and operations arena who are ready to learn how to design and manage DataOps procedures will have excellent career rewards.

    They have the potential to become the leaders of the next generation of data teams, setting the bar for data practices for at least the next decade. Furthermore, an innovative and fast-developing company that removes repetitive and tiresome business procedures will have higher employee satisfaction and retention.

    Improved customer service

    Companies that effectively implement customer experience initiatives, according to Gartner‘s research, start by concentrating on how they gather and evaluate consumer data and feedback. DataOps allows organizations to supply desired services and commodities to consumers when they need them the most, and as quickly as feasible.


    Please enter your comment!
    Please enter your name here