After embarking, implementing, or completing the GRC management, the key to success lies in the belief that it is a journey and an ongoing process. One of the missing elements of GRC is the IT and Governance structure of your databases and data management systems. Knowing the IT and Governance structure will provide the framework to make them work together to boost process and integration efficiencies.
Most companies want to complete, resolve and find solutions to IT and data problems immediately. The initial phase of data implementation requires any organisation to take it slow and avoid the troubles and pitfalls despite the pressure from the organisation to meet compliance deadlines and timely demands. It is best to proceed to know the entire data privacy, protection IT security and GRC (including GDPR) process with a roadmap and framework that will direct you on the right path based on a previous blog in this newsletter
Growing Data Requires Better Data Management
According to multiple surveys, the world of structured data is growing by over 40% yearly. However, unstructured data is at 80%, and global data is expected to touch 60 zettabytes by 2023. Managing this massive volume of information requires the treatment of big data, and, in many cases, GDPR compliance knowledge can do wonders for a business. However, the volatility of big structured data cannot be ignored, as the road from adoption to action is difficult.
Therefore investing in big data because of arbitrary data and GDPR management can result in a huge mess (read fines). Avoid the non-compliance option by avoiding some of the common mistakes in this 10-step checklist (the last five in the December newsletter) and get the full potential of significant data implementation as data is the new black
- The absence of data governance officers to manage the data organisation
The responsibility lies with the organisation to ensure that a practical data governance framework is in place to keep the complete life cycle of the data. Take inspiration from the GRC framework to oversee proper data administration. Give the CTO or CISO the authority to seek answers from all involved to ensure complete control over the implementation process.
- Pay attention to data architecture
Besides the investment in state-of-the-art technology with periodic reviews to ensure integration between architecture methodology and other essential processes like portfolio management
If you use fewer resources and are not entirely committed towards it, the value derived will be less.
- Treating data governance as a project
Do not treat data governance initiative as a project because it is dynamic, ever-changing and has many touch points. Instead of traditional project management, use IT or data governance programs that define a series of project streams that focus on one key area. Know the data flow and data governance as a continuous process.
- Do not ignore the data quality
Data integrity, consistency and accuracy determine the success of any data governance initiatives. As business decisions are data-driven, data quality determines good or bad choices. Structured, correct and trustworthy data ensures informed business decisions are made.
- Avoid the silo approach in data governance
The data governance program limited to a particular business unit may help that unit. However, data sharing occurs across business groups and data sets. Ensure that data governance is successful by treating the data as an organisational asset (the new black). A “think globally, act locally” approach.