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Data Governance

4 Key Pillars to Manage Information Assets

Data governance and management is a term that has become more commonplace in recent years. However, many organizations are still struggling with how to implement effective data governance and management strategies. This lack of focus is becoming more and more apparent as the importance of data management continues to grow. Here are the four key pillars that will help you successfully implement your data governance strategy.

Overcoming 9 Data Governance Challenges

Data governance is the process of managing and protecting data throughout its lifecycle. It involves establishing policies, procedures, and standards for how data is collected, stored, used, and shared. This requires systems that are complex to be put in place by several stakeholders across the organization. Many organizations look at selecting the right software to implement a framework.

Forget IT; Think Business Led Data Governance Initiative

A good data governance strategy should benefit all users of your organization’s data—not just those with technical responsibility for it. Recent years have seen the increasing importance of data as a strategic asset, as several companies have used it to unlock and create value. Increasingly, companies are turning to data governance programs as a foundational pillar of their data strategy (like data mesh) to improve their data sets’ quality, consistency, usability, and security.

Data Governance Framework Policy - What Do You Need to Know?

According to IDCs Global Datasphere, 64.2 ZB of data was created in 2020 alone. This number is projected to grow by 23% annually from 2020-2025. Therefore, we need data governance frameworks for efficient data management and control. This will help us extract maximum value out of such high volumes of data. Such frameworks would be required for data integrity, data protection, and data security. Indeed, according to BDO, the average data breach cost has been estimated to be around USD 3.8 million.

What is Data Governance? Accountability and Quality Control in Analytics

Effective control and governance over your data assets is vital for long-term business success. By keeping your data available, reliable and usable for analysis, consumption and sharing, you can ensure data quality, data security and data reliability is consistently met. However, many organizations today struggle to implement governance frameworks over their data, which has once again highlighted the importance of data governance. So, what is data governance?

Episode 3 & 4 | Data Destination & Data Governance | Data Journey

What are data destinations? In a very abstract sense, data destination is another input along the series of process elements in a data pipeline. However, when calling out an element as the destination, it is really seen as the final destination such as a database, data lake or data warehouse. And yet, any element within the data pipeline has aspects of a final destination (and scaling challenges).