Data governance is a two-tiered approach to managing data security and management. It's the design and application of policies that ensure the quality of your data while also adhering to data handling and distribution legislation.
Put another way, you handle data with the software tools, guidelines, and networks in the enterprise. Data governance refers to the overarching framework that incorporates these (and more) measures according to the law. It involves the need to formalize terms and formats that describe your data to ensure fidelity over time and workflows based on strict rules of use and access.
Instituting data governance can solve problems around data discovery such as:
- Repurposing and making use of unstructured data
- Data cleansing, including removing unused tables in database files
- Integration technologies to fold into other systems.
Learn more: Data Governance Best Practices
Data Governance Imperatives
We all use data from different sources in different ways that's saved in different formats for different software applications. Inconsistencies arise, and without an overview of your data management they might never be resolved. In addition to embarrassment, poor data management can cost you money, complicating data integration programs and compromising business development reporting and opportunities. Without data governance, such issues might even go undetected for years.
There's also a legal imperative. Not having good quality data can put you out of step with compliance regulation, making it harder to meet service-level agreements (SLAs) and may even lead to prosecution.
The most sweeping data governance law thus far is the European Union's 2016 General Data Protection Regulation, which gives EU citizens unprecedented access and control over their data.
One of the GDPR's central fulcrums was seen as the right to be forgotten, where everyone has the right to erasure of personal data under a raft of conditions and circumstances. That imposes a monetary cost on the enterprise in the form of a program to repurpose data for customer access and removal, and steep fines for non-compliance.
Also read: How to Comply with GDPR
Benefits of Data Governance
Data governance is intended to break down barriers. Different stores of data can all combine to make business and workflows within the enterprise and between companies smoother, more efficient, and more secure.
As a company grows, disparate systems handle and process data by different departments, and at a certain level of staff numbers or revenue it can become unwieldy. Transactions are processed and business is conducted in something of a vacuum, with no centralized management environment.
The point of data governance is to bring all those systems and all that information into line, so everyone across the enterprise can engage with any other department or system; and, often with stakeholders outside as well. Management gets a clearer, at-a-glance picture of the health of the entire digital asset base and can be assured they comply with regulation that affects their sector or geographic region.
Other benefits of data governance will follow:
- It will cost less to manage and use data.
- The quality of your data will make it a more valuable asset in itself. For example, if you have data-sharing agreements with other businesses or business units.
- It will be easier to investigate for analysis, be it revenue-generating or otherwise.
Data governance will also give you and your enterprise better decision-making power about the directions of your organization. Following the data tells the story of what's going on with supply and income unimpeded.
Also read: Tools to Better Manage GDPR
Getting Started with Data Governance
Different business units in the enterprise will have different views on how their information is stored, used, and accessed, so implementing data governance is like launching a rocket — most of the hard work will come as soon as you pull the trigger, but it will get easier as you pick up speed.
The data governance plan ultimately has to come from the top, but it mustn't be simply edicts on how things will be done. Instead, it should be based on engaging with and listening to department heads about their needs and goals. They're the ones that use the information, after all, so they'll know the best methods to wrangle it. The job of the data governance committee or officer is to massage those needs to comply with the policies and legislation data governance sets out.
Selling data governance to company leadership can be a challenge, including corporate boards who might not be clear on its business value. Data governance isn't simply a reactive process because of laws and rules. It should be proactive, to take advantage of newer and expanded revenue streams.
Examples of how your enterprise missed the boat on important opportunities can also be helpful; such information highlights how unstructured, insecure, siloed, and bad quality data might negatively impact your business.
It's a new world where networks are so pervasive that data travels everywhere and fulfil endless purposes. With so much of it being processed even without human input, we need a clear way forward to manage and disseminate data. Data governance is the answer.