Data Governance and IT

So far I have argued that data is an asset, and therefore needs an organization dedicated to its management as well as an executive accountable for leveraging its value. Traditionally, IT and the CIO have filled this need. Why change? After all, IT stands for Information Technology, and information is just another word for data.

IT is responsible for a significant set of capital assets. These include hardware ranging from IoT sensors to cell phones, laptops, servers, and mainframes. IT is also responsible for software assets running on all of this hardware, and networking to tie them all together. Maintaining these assets and ensuring that they are meeting the needs of the business is a large and complex undertaking.

These hardware and software assets are continually acquiring, transmitting, transforming, storing, and reporting data, so it is easy to view data as just one more aspect of the IT assets. However, data is independent of any particular hardware platform. It can be copied and stored virtually anywhere. It can be printed on paper and stored in filing cabinets. Conceptual data architectures and logical data models are representations of data independent from any particular implementation. Databases and file formats are technology dependent, but the data they store exists independent of technology.

You could argue that the processes instantiated in software also exist independently from any technical implementation. This is true to a large extent. But the algorithmic elements that are technology independent are just the yin to data’s yang. They provide a definition of the data by describing the transformations required to derive it. So when we speak of data as an asset, we need to include the data’s definition in terms of transformations and derivations from other data. But this doesn’t change the technology independent nature of data.

This distinction between data assets and IT assets is also reflected by the skillsets necessary to manage each. IT, i.e. the Information Technology organization, must have the technical skills to support and maintain hardware, software, and networking assets. This includes, by the way, Database Administrators, Storage Engineers, and Network Engineers who manage the technology storing and transmitting data. But there is another set of skills necessary to optimize the value of the data assets. These are the fields of Data Governance, Data Management, and Data Architecture. This is why enterprises need a Chief Data Officer and a Data Governance organization. The CIO, or perhaps more accurately, the CTO, should focus on supporting technology assets. And let the CDO focus on monetizing the data asset.