Enabling compliance with intelligent data governance

Security system of padlock in network space.

By Moti Uttam, Managing Director (Malaysia), of Hitachi Vantara

Malaysian has been on a fast track to embrace AI and big data with the support of the Government agencies. The move though not at its optimum state is crucial to assist companies gain in-depth insight into the variables that can impact their industry and business.

The growing interest in data storage, processing and machine learning is proving to be eminent especially in the current situation where businesses are trying to transform the way they do business. Answers to pertinent questions like what can we continue to sell?, who do we sell it to?, how do we bring it to them?, where can we sell it? can be answered alongside the managing a remote workforce with data insights.

While the focus remains on compiling, analyzing and leveraging on data, there is much left to be done in the area of data governance. The conversation primarily extends to the Personal Data Protection Act 2010 (PDPA) only, which takes care of permissions, accuracy of data, duration of storage, usage of data, security of the data and restrictions to share these data in a commercial environment.

However, there are data governance considerations and responsibility that need to be borne by the company itself in managing the valuable information within their systems. A robust, intelligent data governance model can deliver many benefits to companies and enables data accessibility, data confidence and understanding, and data activation. Some key benefits are:

1) Data consistency – this ensures completeness and accuracy. These are the foundations of trusted data and the basis for continually improving process models. Consistency allows data categorization and classification that can aid all business decisions.

2) Proactive data quality checks- this ensures data alignment. With intelligent data governance, the common problems that arise from disjointed data points and siloed data repositories can be addressed in an automated fashion. This approach generates actionable insights as it examines how well data adheres to defined quality and governance rules.

3) Data alignment- this is critical for regulatory and compliance responsibilities. Intelligent data governance standardizes data quality standards, which reduces the risks and unplanned costs associated with basing decisions on misleading data. It also ensures accurate and timely adherence to regulatory and compliance requirements.

4) Confusion over data meaning and clarity is removed. Data confusion is a data governance problem. The data is incomplete or the processes supporting the data do not do enough to balance the rigors necessary for completeness at the speed of business.

5) Analysis and decisions are based on well-defined and accurate data. Intelligent data governance guides the structure and flow of data through the information supply chain — especially during analytics processes. Governance ensures that your data capture mechanisms are set up to collect what data you need. It establishes alignment between the
tactics of the lines of business and your organization’s larger strategic goals. Fact-based decisions become real-time events throughout the organization.

6) Intelligent data governance is key to ensuring data veracity, which in turn builds the confidence needed by the users of that data to achieve the real-time goal for decision making.

7) Data confidence encourages the sharing of insights. An organization that has a strong datacentric culture will only be able to encourage information and insight sharing if the data is complete and accurate. Intelligent data governance is much better for business because it not only meets these challenges, but also requires that data and insights be shared throughout the organization.

8) Intelligent data governance fosters collaboration and establishes accountability. Managing and controlling the use and proper maintenance of data based on a standardized set of rules or policies eliminates inefficiencies in the system. This approach boosts collaboration between units and fosters a greater degree of accountability regarding who is responsible for data.

9) Data is kept clean and relevant based on its referential value. The amount of data stored doesn’t matter if it’s relevant to the business and devoid of inaccuracies. An intelligent data governance approach makes everyone stewards of the data, responsible for keeping it in good shape.

10) Intelligently governed data gives you a competitive advantage. Whether data is centralized or dispersed throughout the organization, when it is effectively managed and controlled, the process of gaining valuable insights and unlocking new opportunities is easier to achieve.

At Hitachi Vantara, data management is done differently. While we believe that a robust data storage is empowering, we are also firm about ensuring the responsibility of how this data is used with our intelligent governance solutions through the Hitachi Content Platform. Our intelligent data governance solutions are included on a single platform that extends across private and public cloud, reducing the cost and complexity of data governance and compliance reporting.

 

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