Data governance is an outline of business data analytics. Organizations can set rules for different data associated with customer behavior, views, shopping style, etc. The aim of data governance helps to consistently gain access to reliable data before the report is used to gain competitive insights or performance assessment. The reasons for data governance in modern organizations are –

  • High volume data from multiple sources can result in data inconsistencies.
  • Need for data access policies.
  • Avoid poor quality data use.
  • Common data language for cross-enterprise data analysis.
  • The requirement for improved organizational metadata.
  • Increase in data democratization and self-service analytics at the enterprise level.

On-premise IT infrastructure is becoming costly and complex. It needs high skilled manpower. Therefore, organizations are migrating their IT and data controlling functionalities to the cloud. It is a managed deal with low-cost storage, 100% up-time, automated analytics, and Business Intelligence services. Thus, organizations can focus on their core activities without worries about indispensable IT functions. With cloud adoption benefits there are challenges to understand –

  • Great possibility of high volume, velocity, variety, value, and veracity.
  • Increase in external data usage.
  • The complexity associated with data management.
  • Overlap of services & compatibility issues between different vendors.
  • Conflicting priorities of what needs control for effective use and compliance.

Consider these challenges and take help from a data governance consultant at EWSolutions to regulate cloud readiness and current business value. Being proactive helps to mitigate these potential challenges and saves your business time and money.

Data governance best practices in the cloud

  • Set finite time limits for the data lifecycle
  • Retain the security setting and move data to confirm uniform implementation.
  • Keep track of Metadata for an improved data value, which results in rapid data access.
  • Keep track of multiple occurrences of the same data.
  • Develop policies for data integration and transformation.
  • Manage developed data models.
  • All data must have an assigned subject matter expert to ensure balanced risk management.

What about data security in the cloud environment?

Cloud technology adaption brings cost advantages, so organizations are moving their analytics process. Nevertheless, data security is a huge concern for businesses that chose a hybrid or private cloud environment as they are partially shared. No one desires to compromise their valuable data asset.

Cloud-based security when compared to on-site security includes regular virus scans, updated software patches, and physical security appliances at the cloud centers. The majority of cloud security structure has many restrictions on data access usage, control, and security analytics like that on on-site facilities.

The cloud service provider doesn’t control password updates or data access, so your company data is susceptible to external attacks. Therefore, it is the responsibility of the business employers to implement stringent data governance as well as data security practices associated with data assets on the cloud.

Choose cloud vendor carefully

Verify the cloud vendors’ approach towards data governance. A reliable cloud vendor is aware of data governance significance, so offers tools for access control & management, metadata cataloging, data quality, data security, and data assessment.

Data governance cloud adoption ensures a sustainable, scalable, cost-effective, and compliant approach that offers enduring business value!