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Youโ€™re about to discover a completely new way of thinking about data in your company: the Data Democracy. In this ebook series:

 ๐Ÿ”Ž   I explain why you need a data democracy, what a data democracy is, and how to obtain it. Then, I delve into the causes of the absence of data democracies in companies, and what you can do about it.

 ๐Ÿ˜ฑ   You will learn about the frightening alternatives to a data democracy (e.g. data tyranny, data meritocracy, data technocracy, etc.). The most tragic part is that you probably find yourself entangled in one or more of these data governance horror regimes.

 โœ…   You will finally learn the reality of the data government you find yourself in. I will help you get out. I will help you build a data democracy.

Ole Olesen-Bagneux

Please note that Ole's ebook series will be progressively released in chapter form. Sign up for free to receive your personal access to the ebook portal by e-mail. You'll also be notified each time a new chapter is released, so there's no need to sign up again!
Sign up here to get free access to the ebook series โœ๏ธ


Data Quality usually refers to a companyโ€™s ability to ensure the longevity of its data. At Zeenea (a data catalog provider), we believe Data Quality is ensured through the 9 following dimensions - all essential to extract value to your company:

๐Ÿ”ธ Completeness

๐Ÿ”ธ Accuracy

๐Ÿ”ธ Validity 

๐Ÿ”ธ Uniqueness

๐Ÿ”ธ Consistency

๐Ÿ”ธ Timeliness

๐Ÿ”ธ Traceability

๐Ÿ”ธ Clarity

๐Ÿ”ธ Availability

We will detail these dimensions with the help of a simple example in part one. We will then elaborate on how Data Quality management is an important challenge for organizations seeking to extract maximum value from their data.

We will also draw parallels between these different Data Quality dimensions and the different risk management phases to overcome - identification, analysis, evaluation, and processing. This will enable you to hone your risk management reflexes by tying in Data Quality improvement processing to a company objective (and evaluating the ROI on each quality dimension).

Once we have established the main features of an enterprise Data Quality management tool, we will detail how a Data Catalog - though not a Data Quality tool - can contribute towards Data Quality improvement (through the clarity, availability, and traceability dimensions mentioned above).

About the author

Ole Olesen-Bagneux is a globally recognized thought leader on data catalogs and enterprise data management. He has written 'The Enterprise Data Catalog' published by O'Reilly. He holds a Ph.D. from the University of Copenhagen, in Library- and Information Science. His expertise of data management and -mesh is that of a specialist, a leader and an architect. After a rich experience as Enterprise Architect with GN Store Nord, he recently joined Zeenea as Chief Evangelist.