ESSENTIAL READS FOR DATA GOVERNANCE PROFESSIONALS

Staying informed is crucial for professionals at all levels. The following curated list of books offers invaluable insights for those looking to master the art of data governance.

“The Chief Data Officer Handbook for Data Governance” by Sunil Soares

In recent years, the Chief Data Officer (CDO) role has become increasingly crucial in data-driven organizations. However, CDOs often lack a clear roadmap for success. Sunil Soares addresses this gap with his comprehensive guide, “The Chief Data Officer Handbook for Data Governance” (ISBN: 9781583474174).

This practical handbook offers CDOs valuable insights on:

  • Managing data effectively
  • Leading data governance teams
  • Maximizing the value and usability of organizational data

For CDOs looking to enhance their impact and contribute significant value to their companies, this book serves as an indispensable resource.

“Data Governance: How to Design, Deploy, and Sustain an Effective Data Governance Program” by John Ladley

Despite being published in 2012, John Ladley’s “Data Governance: How to Design, Deploy, and Sustain an Effective Data Governance Program” (ISBN: 9780128158319) remains a cornerstone text for those new to data governance.

Ladley, a veteran thought leader in Enterprise Information Management, provides:

  • A comprehensive overview of the data governance lifecycle
  • Step-by-step guidance for implementing data governance programs
  • Real-world case studies
  • Detailed data governance frameworks

This book is particularly useful for managers seeking a practical approach to establishing data governance within their organizations.

“Data Governance: The Definitive Guide” by Evren Eryurek, Uri Gilad, et al.

As companies increasingly migrate data to the cloud, a holistic approach to data governance becomes essential. “Data Governance: The Definitive Guide: People, Processes, and Tools to Operationalize Data Trustworthiness” (ISBN: 9781492063490) by Evren Eryurek, Uri Gilad, Valliappa Lakshmanan, Anita Kibunguchy, and Jessi Ashdown offers a comprehensive look at maintaining data integrity in the modern landscape.

This guide covers a wide range of topics crucial for ensuring data trustworthiness:

  • Data governance strategies
  • Benefits and challenges of cloud migration
  • Techniques for improving data quality
  • Data protection measures
  • Methods for data democratization

By addressing the people, processes, and tools involved in data governance, this book equips readers with the knowledge to navigate the complexities of modern data management.

DEMYSTIFYING DARK DATA: THE UNTAPPED POTENTIAL

As the world becomes increasingly digitised, organisations are generating more data than ever before. But did you know that up to 80% of that data remains untapped? This structured/unstructured, unprocessed data is known as dark data, and it has the potential to be a goldmine of insights for organisations.

What is Dark Data?

Dark data refers to data that organisations generate but don’t use. This data is typically unstructured and stored in various formats, such as emails, documents, images, videos, and social media posts. It’s often ignored because it is difficult to process and analyse, requiring advanced analytics tools and techniques to extract meaningful insights. However, with the right approach, dark data can be a valuable source of information that can help organisations make better decisions and gain a competitive advantage.

Where is Dark Data Found?

Dark data can be found in many areas of an organisation, including customer feedback, product reviews, employee emails, and social media mentions. By analysing this data, organisations can uncover hidden patterns and insights that can help them improve their products and services, enhance customer experiences, optimise operations, and reduce costs.

Dark Data in Action

Dark data can be used in virtually any industry to improve business outcomes. For example, an FMCG company can analyse customer reviews on social media and product forums to identify common complaints or issues. This data can be used to improve product design, customer service, and marketing strategies. Similarly, a healthcare organisation can analyse patient data to identify potential health risks, improve treatment plans, and optimise resource allocation.

Analysing dark data requires a different approach than traditional structured data analysis. Machine learning and artificial intelligence can be used to process large amounts of unstructured data and extract meaningful insights. This technology can be used to categorise data, identify patterns and anomalies, and extract sentiment from text and other data.

How to Leverage Dark Data?

To leverage dark data effectively, organisations need to establish a data strategy that includes data governance, data quality, and data privacy. They need to ensure that the data they collect is accurate, complete, and secure, and that they comply with regulatory requirements. Additionally, organisations need to invest in the right tools and technologies to extract insights from dark data.

There definitely some challenges with dark data is to extract valuable insights from it, but there are strategies you can use to put it in action:

  1. Identify your goals: Before you begin to analyze your dark data, it is essential to identify your business goals. Understanding what you want to achieve will help you determine what data to focus on and what insights you need to extract.
  2. Collaborate across teams: Dark data is often spread across different departments within an organization. Collaboration across teams can help you identify opportunities for using this data and uncover insights that might have been missed.
  3. Make your data consumable: Once you have identified the data you need, the next step is to make it available. This doesn’t mean that you need move your data in a single location as there are plenty efficient architectures to prevent data duplication. Making your data available in an agile and flexible way, will enable you to process and analyze it more efficiently.
  4. Use data analytics & AI/ML: The right tools can help you mine valuable insights from your dark data. There are various tools available, from simple data visualization software to sophisticated machine learning algorithms.
  5. Implement data governance: Finally, it is essential to have proper data governance in place to ensure that your dark data is used appropriately. This includes establishing data quality standards, data retention policies, and data security protocols.

Conclusion

Dark data represents a vast untapped resource for organisations seeking to gain a competitive advantage. By analysing this data, organisations can uncover valuable insights that can help them make better decisions and improve their operations. With the right strategies and technology in place, organisations can demystify dark data and unlock its full potential. It’s time to start exploring the dark data lurking within your organisation and turn it into a competitive advantage.

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