Helping companies to set guidelines for data governance is one of the topics discussed in a meeting held recently by the newly established Institute of Big Data Governance.
Based on my experience, it’s not easy to encourage full data usage inside companies. It’s even harder if data security is involved.
Even the US government has been encountering data security issues. Indeed, good data governance is critical.
Over the last decade, big data development has encountered numerous problems, including the difficulty in data transfer, data quality, data abuse and privacy concerns.
There are a number of possible factors that led to such issues:
1. Different systems are planned and built separately, thereby presenting problems on the completeness and accuracy of data.
2. There are no unified data rules and models. Different sections in an organization have their own interpretations.
3. The absence of clearly defined responsibilities and authority to govern people involved in the data management process.
4. There is no robust management system covering the full life cycle of data management, from updates to maintenance, backups and erasures.
A feature of big data, e.g., having multiple sources, further compounds these issues.
To get it right, companies should first grasp the full picture, and thoroughly understand how data is produced, collected, stored and used.
Companies also need to find out exactly how the existing system of data standards and compliance works, and how data privacy and data quality issues are being handled.
Data strategy is set to play a bigger role in a company’s overall strategy planning. Data governance should align with corporate strategy, corporate culture and business needs.
This article appeared in the Hong Kong Economic Journal on Feb 20
Translation by Julie Zhu
[Chinese version 中文版]
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