Much as a librarian is responsible for organizing a large collection of books, organizations must have a set protocol for managing the information they collect when doing business. Not being able to find or protect data makes for a dangerous precedent.
While companies might hire someone with a library science degree to help them organize large amounts of data, that is only a part of what is needed. The process of maintaining the integrity of your data, protecting it and making it available as needed, requires a plan of action. That plan is called data governance.
Regardless of the size of your business, or whether your work is digital, analog or a combination of both, the good health of your enterprise depends on the high quality of your data.
What Is Data Governance?
Data governance provides an organization with a plan to make sure that its data is available, usable, consistent and secure. This includes creating processes that provide accountability to make sure data management is effective. This means that the data is not corrupted, and it can be used by everyone in the organization.
Overseeing these processes is a person who is called the data steward, who makes sure the established guidelines are being followed. This person will also monitor the process and suggest improvements as needed, often with the help of a project management software for information technology.
Data governance is holistic in that it involves the people, processes and information technology department of an organization. It is tasked to create a consistent use of data across the whole enterprise. To do this, data governance implements practices to make sure the data is managed as an asset and is made into meaningful information.
Data Governance Goals
There are many goals that are defined through data governance and travel over all points of the business. The larger goal is helping those in the organization accept the process of data governance. Some of the steps that lead to that are outlined below.
Good data governance will help with decision-making. It will make decision-makers more confident because they are basing decisions on consistent and reliable data.
There can also be the risk of regulatory infraction. Fines of such a nature can only be avoided when there’s transparency in the data to help steer the organization on the right side of what could be complicated legal boundaries.
One of the main goals of any data governance plan is security. That includes defining and verifying the requirements for data distribution policies, but also maintaining vigilance against outside cyber-attack, inside equipment failure or crashes that could compromise sensitive data. This should all go into a business continuity plan, which no company should be without.
It’s no secret that data can be monetized, and data governance helps to make the most of that potential income. There’s always a potential for the data of one’s company to make money, and that potential is more likely realized via effective data governance.
To ensure that the data is being governed to support these goals and others, there must be accountability. Systems don’t just turn on and work without oversight. There must be someone who is designated to manage, monitor and report on the quality of information.
Data must be managed to achieve any goal. Therefore, having a data governance plan in place helps to give supervisors the means to deliver on whatever goals the organization has decided upon. Naturally, any data governance plan should be efficient. This avoids having to tread the same road twice, or reworking something that has not been completely thought through.
Having data available to all who need it in an organization will also make for better, more productive employees. The less hurdles they must clear, and the more secure and accurate the data, the better the work that results from it.
In data governance, there should also be a baseline to measure against. Without a baseline, any reference is not anchored to context and therefore cannot be useful in terms of coming up with improvements. A good way to think of data governance is to liken it to quality control, both of which can play an important role in total quality management.
Data governance is a discipline that helps companies assess, manage, use, monitor, improve, maintain and protect data. Data governance has its own intrinsic goals to decide on an agreed-upon rights and accountability of information-related processes.
Implementation of Data Governance
The first step in implementing data governance in any organization is deciding on the owner of the process, the custodian who will oversee it, otherwise known as the data steward. This person or team will help define processes to store, archive, back up and protect the data from either internal issues, theft or attack.
A set of standards and procedures are developed to figure out how the data is used by authorized personnel. Also, a set of controls and audit procedures are put in place to make sure oversight is ongoing and compliant with company and governmental policy.
An Ongoing Process
Data governance isn’t a one-time solution, but a process that is constantly being monitored, reported on and improved to stay updated with technological, regulatory and industry standards.
In order to accomplish all this, a team is assembled to implement policies and procedures for handling data. The team can be made up of a variety of individuals, from business managers to data managers as well as other staff and even relevant end users.
Key Elements of Data Governance
Data governance essentially stands on four pillars. Think of these as the four steps towards getting a data governance plan implemented, managed and in a state of continuous renewal.
The data steward is mainly responsible for making sure that the quality of data remains high, which means accurate, accessible, consistent, complete and updated. The data steward doesn’t have to be an individual, but a team assigned with the task of maintaining the data governance.
The team is usually made up of database administrators, business analysts and other personnel who understand the context of data within the organization. The data steward works with people who manage the overall data life cycle to make sure the data conforms the organization’s data governance policies.
Data quality is the driver for most data governance tasks. Quality means accuracy, completeness and consistency over the whole data structure of the organization. Part of data quality is data scrubbing or data cleansing, which identifies, correlates and removes duplicated data.
To maintain the data quality of any data governance plan requires data editors, data mining tools, data differencing utilities, data linking tools, workflow and project management tools.
Master Data Management
To ensure the consistent use of data across an organization, especially a large one, there must be a master data management plan, which is a comprehensive way to link all critical data to a common point of reference. This adds to the quality of the data and streamlines data sharing throughout the organization.
Data Governance Use Cases
Organizations aren’t static; they often merge or acquire other entities and financial and regulatory changes. All of these will impact data governance as they can threaten the integrity and security of data. Therefore, the need to constantly be monitoring, reporting on and improving data governance is crucial.
Data is the life blood of any organization. It must be cared for securely but also shared within the proper channels easily. That’s a complex project, one that needs tools up to the task. ProjectManager.com is a cloud-based project management software that allows you to plan, track and report on your data governance. Try it today for free with this 30-day trial.