Data Readiness and Quality: The Big New Challenges for all Companies

We live in a digital age which is increasingly being driven by algorithms and data. All of us, whether at home or work, increasingly relate to one another via data. It’s a systemic restructuring of society, our economy and institutions the like of which we haven’t seen since the industrial revolution. In the business world we commonly refer to it as digital transformation.

In this algorithmic world, data governance is becoming a major challenge. Data is fueling the entire trasformative process which means good data quality is vital. Without it, we could find ourselves running into problems of process execution and bad customer service.

This chart illustrates this new landscape. Business relies on technology, processes and people. Data governance lies at the heart of these interactions. It is the cog in the wheel which makes everything else go round. If it has a problem, the entire system breaks down.

All of this is very easy to say, in theory, but what does it mean and how will we deal with it in practice?

The standard definition of data governance refers to the ability to manage every aspect of enterprise data including integrity, security, availability and usability. Data sources are everywhere, in many formats and many standards. We need to extract and elaborate insights that feed daily enterprise decisions.

I’m currently conducting research with Talend (NASDAQ: TLND), a global leader in data integration, to investigate how companies can harness the benefits of a comprehensive data governance strategy in an extended scenario where data drives business decisions. If those decisions are bad it means poor outcomes, higher costs and lower revenue.

During our collaboration, I discovered many aspects of the data governance framework that ambitious companies need to refer to and many real-life case studies of companies that rely on data governance as a strategic asset. As usual, I like to look at how data governance is being applied in the real world. So, let’s go through it industry by industry.

EURONEXT is a European stock exchange that combines five stock exchanges (Netherland, Belgium, Ireland, Portugal and France) and deals with more than 100TB of transactions. You can imagine the huge data problem they are dealing with.

To analyse all that data, they had to wait six to twelve hours after closing. Using Talend Big Data and Talend Catalog, they boosted their performance while respecting integrity, availability and, most importantly, this highly-regulated market.

UNIPER is a global energy provider that generates, markets and trades energy on a large scale.