Solving the Challenges of Data Governance, Post-GDPR

November 10, 2018 0 comments

GDPR, ever-changing legal requirements, security breaches… Data governance is rarely out of the news. It is a philosophy, a process and, increasingly, a software-based standard that both underpins and impacts all other aspects of data-driven business.

A sound data governance process is now at the heart of corporate best practice, customer trust and compliance with local and international law. Without it, the potential consequences are dire: mistakes can be made, personal data can be lost or left unsecured, compliance — both regulatory and legal — can fail. And, research has found, productivity and profit decreased.

The most pressing data governance issue for any organisation of late has been the recent implementation of GDPR (General Data Protection Regulation). We have seen many companies still grappling with its requirements, which have inevitably put a financial price on an organisation’s need for both an efficient and accountable data governance process.

Garth Laird, CEO of ZAP

Making data governance even more of a challenge is the ever-growing amount of data businesses work with. From ERP to CRM to accounts systems, databases and more. Some in the cloud, some on-premise.  Others, a hybrid of the two. Managing all this manually has become a barrier for many companies, as they try to ensure the governance of their business data.

With so much at stake, businesses can use software to improve data processes and deliver better governance. Data management automation software, for example, can improve governance by controlling, auditing and logging all key data management processes, such as data access and collection, unification, integration and preparation.

With ‘manual’ governance, a number of updates to records and files might be needed before data can be moved into a Data Warehouse. And with each update comes the risk of mistakes or delay. In an automated program for data governance, administration time is reduced and this risk of human error is eliminated.

As an aside, I’ve also seen many businesses take the time and expense saved by moving to software-based automation of data processes and redeploy it on faster reporting and better BI analysis.

In today’s intricate world of business intelligence, I believe an automated approach is the key to businesses to achieving well-governed, high-quality data analysis, which adheres to the strong regulations that the likes of the GDPR impose upon businesses today.

 

Author

Garth Laird, CEO of ZAP

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