The challenge of data governance

GDPR, ever-changing legal requirements, security breaches… Rarely is data governance out of the news. It’s both a philosophy, a process and, increasingly, a software-based standard that underpins all aspects of data management.

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

“When data becomes a disaster — superfluously siloed, geographically redundant, overrun with entry errors — it’s a nightmare for IT and customer service and everyone else. (And) what if the consequences were not just lost time, revenue, and morale? What if poor data management also cost €20 million, or four per cent of annual global turnover? Such are the stakes of the new GDPR…”

IT Pro, Data management in the age of GDPR

Data governance principles and policies

The most pressing data governance issue for any organization — and a classic illustration of the business-wide ramifications of governance in general — is GDPR. The General Data Protection Regulation — examined in detail in ZAP’s GDPR white paper — is the EU’s radical and far-reaching data protection legislation that comes into force in May 2018. And it puts a financial price on an organization’s need for both an efficient, accountable data governance process and a sound data management system in general:

“When data becomes a disaster-superfluously siloed, geographically redundant, overrun with entry errors-it’s a nightmare for IT and customer service and everyone else,” explains IT Pro’s Data management in the age of GDPR. “(And) what if the consequences were not just lost time, revenue, and morale? What if poor data management also cost €20 million, or four percent of annual global turnover? Such are the stakes of the new GDPR…”

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Automated data governance

The more that manual labor is removed from the process of data governance, and the more that software/technology-enabled automation is implemented, the more efficient and sophisticated data governance becomes.

ZAP Data Hub automates, controls, audits and logs all aspects of data governance and security, covering everything from password and access control to reconfiguring mismatched data definitions. Enterprise-class controls set security permissions, regulate access and protect data at any level of granularity, while data governance is controlled at four separate levels: user, resource, warehouse data and cell data. Data lineage is governed separately, with history tracking, auditing and monitoring also included.

Automated, software-based data governance is not only a more efficient alternative to manual labor (with all its inherent cost implications, time drain and risk of human-error) it’s also an easy-to-implement, cost effective solution for the many businesses who have no data governance in place at all. Database Trends and Applications’ How to Meet Ever Changing Data Governance Standards sets out key steps which concur with ZAP’s approach:

  • Governance roles: data owners and custodians
  • Policies on accountability and responsibility
  • Metadata standards
  • Control and audit processes
  • Measures and evaluations
  • Monitoring efficiency of controls over time
  • Adaptability and change management

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Data governance for Business Intelligence

Avoiding human error, avoiding customer complaints, data loss or indeed avoiding legal action… Data governance is often framed in the context of taking steps to avoid the worst. But a strong, cohesive, automated and sophisticated system brings with it many proactive, positive benefits, too.

Automated, self-service governance of the data feeding Business Intelligence and analysis systems can increase profits by reducing administrative and maintenance costs and operational expenditure. Aberdeen Group research confirm this, and its connection to data integration, nothing that “organizations that have implemented data governance tools and integrated their master data management and ERP systems saw a 20% reduction in operational costs and 22% reduction in administrative costs achieved as a result of their ERP implementation.”

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