IT Governance

The Act of Self-Service with Governance

Many organizations understand the need for leveraging the massive data available to them. Still, they run into an obstacle like maintaining old leftover data while adopting IT-driven data transformation. In this article at Datanami, the author explains a competent way to backup old data. The IT teams can segregate the transactional information in a data centre, strictly governed and accessed by selected team members.

Where’s the Gap?

The data transformation tools need technical expertise, which is not available sometimes. During the requirements change, the IT division must adjust the extract, transform, and load (ETL) processes that are viable for delivering the business outputs. However, if the data volumes explode, and data complexity and opportunity increases, the same strategy may not remain viable.

Moreover, the IT teams may not respond fast enough to the business requests to give new datasets in response to the fast-changing requirements. So, the effort data transformation data for the business swipes away the precious time required to monitor data security and governance.

IT cannot fulfill the fast-changing business needs while the businesses will not wait to gather the required data. Hence, the data remains unused, and a vast prospect remains amiss.

Need for New Approach

DataOps is an ideal approach to governance by establishing data operations and embracing a shared platform to collaborate data workers, and IT teams to chase a common goal. Organizations need to adapt this process to empower their data workers with self-service agility.

Data workers must explore and refine raw data while analyzing, developing, and extracting the value of data already accessible to the organization. Also, they must maximize security, manage access, and monitor data in pipelines. Install a shared platform for collaborative governance where data workers can access valuable information. Also, the IT teams can automate and control data in the pipeline to maintain scalable yet efficient processes.

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