For CDOs, a centralized data strategy is to enable an enterprise to fully exploit data and analytics. To get to that point some essential capabilities are required.

• First, the enterprise must be able to identify, combine and manage multiple sources of data.
• Second, it must build the right analysis models for predicting and optimizing outcomes.
• Third, management must possess the will to transform the organization to understand how to leverage and convert the data and analytics models into decisions that improve business outcome.

In addition, certain prerequisites help clearly define the strategy for how to use data and analytics. The following offers 5 tips on how to do that.

This is a recap of Stibo Systems’ webinar “How to meet and sustain the GDPR requirements using data governance” where The Data Governance Coach, Nicola Askham, shares insights into the relationship between data governance and data protection, including the General Data Protection Regulation (GDPR). You can listen to the full 30-minute webinar on-demand anytime you want.

Just a few years ago, the discipline of data protection was mainly about securing who had access to your data and ensuring the data did not fall into the wrong hands. Data governance, on the other hand, was mainly about managing your data and improving your data quality. Despite what many people think, data governance and data protection have never been the same thing, and the line between the two disciplines used to be very clear. But now, Data Governance Coach Nicola Askham does not see this line existing anymore. Instead, we have a relationship between data governance and data protection where they work together and complement each other. What happened?

Data is a powerful business enabler. You can use it to improve customer engagement, reduce time to market and increase sales—that is, if you get it into the hands of the right people, when and where they need it.

Unfortunately, we all know that data can easily fall into the hands of the wrong people. With a data-driven business environment comes an increased risk of data breaches, cyber attacks, phishing and more. If your data is fragmented and being distributed across many different systems and applications, the risk only increases.

Effective data management can help keep your data out of reach from anyone not authorized to view, edit or compromise it in any way, making it easier for you to manage data security and data control.

Here is how Master Data Management supports your data security efforts.

Master Data Management is commonly known as a way to achieve data truth. The ultimate goal being to provide the end user with a "trusted single version of the truth" from which to base decisions, according to Wikipedia’s definition of MDM.

By having all information in one place, it is easier to manage and thus easier to improve its quality and coherence. In other words; you just need “the single data view”, then connect the outside world to the MDM solution to get instant access to good data. Right?

Well, not always…

When it comes to governance, your first thought is probably government. But the term can also mean management or control through overarching rules – so laws, guidelines, and the creation of specific structures. The goal of structured data management is to ensure the availability, usability, integrity, security and confidentiality of information. No one disputes its value, and it has also been featured in previous blog posts and webinars.

So, data governance is nothing new – but many companies are only just getting around to it. But here's why they shouldn't wait any longer:

We’re more than halfway into the year 2017. And what better time to take a look at what you – our readers – have found to be the most interesting topics and blog posts during these first six months. Maybe you’ve missed one of these great posts? This is your chance to (re-)read them. These are the five most viewed posts:

Just a year from now the European Union's General Data Protection Regulation (GDPR), that aims to strengthen data protection for individuals, will come into force. It will affect all companies inside and outside of Europe that are storing and managing personal data of European citizens.

The objective of data governance is to provide insights into the availability, usability, integrity, security and privacy of data. As the amount of data organizations handle grows, establishing efficient data privacy policies and processes is critical. Furthermore, data privacy must be embedded in new systems and crafted onto existing legacy systems and networks. But privacy is far from just about software and hardware. It’s very much about people.

Whether their customers are individuals or global enterprises, all industries now face a range of challenges and opportunities presented by a ‘digital-first’ world. As a consequence, traditional companies are looking for ways of complementing and differentiating their product-based business models with value-based services.  A recent Frost & Sullivan estimation foresees that 70 percent of Fortune 500 companies are expected to develop new business models that provide product-as-a-service.

Data Governance. It’s kind of like going to the gym. You know it’s really good for you, but you just don’t do it (Sorry Nike!). The same applies for many organizations today when it comes to data governance. They know that it can add real value to their business, but despite that, it is and always has been difficult to sell internally. Concepts such as technical and business-related metadata, data quality, information models and data ownership often lack funding for implementation.