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2019 Data Governance Trends You Must Be Aware of

With innovative technologies becoming a norm, it is natural for the industry to come up with new governance frameworks. What are they going to be like? In this article at TDWI, Tracy Ring Cryder gives a glimpse of the 2019 data governance trends that you must be aware of.

The New-Age Data Governance Trends

There has been rapid growth and acceptance of new technologies like RPA and automation in the market. The majority of these technologies are dependent on data. So, you will experience a huge change in the data governance sector.

Insistence on Improving Data Quality:

Your results are as good as the data you have collected. Obviously, analytics plays an important role in it. However, you cannot get a competitive edge if the data provides no valuable insights. If you collect data from incompatible systems, it can be an issue. Also, if your collecting mechanism is outdated or has unclear commands, you will not get the relevant data results. So, data professionals must establish standard governance frameworks for employees, organization, and policies. With a centralized data governance system, you can access data as per your hierarchy. You can also compare and replace existing reports and validate through historical records. A master data management (MDM) application can automate the data collection process.

Changing Talent Acquisition Approaches:

One out of three Americans is freelancing nowadays. A recent study predicts 42 million people will be self-employed by 2020, thrice the current number. This increase in remote employment raises risk in data management, security, and access. To prevent breaches and leakage of sensitive data, new data governance rules should be created around talent acquisition approaches.

RPA, a New Approach to Data Governance:

Since systems and interconnected devices generate a lot of data, organizations may feel overwhelmed while controlling and channelizing the flow. Robotic process automation (RPA) is a new way to improve and establish advanced data governance. You can use the tool to take care of repetitive work like ‘data processing, normalization, and metadata creation or updates,’ etc. With its help, you can regulate reporting, data sampling, and consistency in quality in governance.

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