The incredible amount of data that is available to organizations offers many ways in which they can improve their products and processes. Using the information wisely can result in competitive advantages that allow a company to dominate its market. Turning the raw material of big data into viable business intelligence is the goal of data analysts and scientists.
When working with data, it soon becomes apparent that it is not a one-size-fits-all type of concept. It comes in many diverse forms that need to be incorporated into your business environment. Data generated from a social media site, a customer database, and online surveys may all need to be used to drive a marketing campaign. In some cases, multiple departments need to collaborate on plans using the same data sources and need to see and describe this information in the same way.
Data governance is a method with which organizations can get a handle on their data so it can be used more effectively. But not all enterprises have taken the appropriate steps to institute a data governance program. This failure may wind up being more expensive than they suspect.
What is Data Governance?
Data governance can be defined as the overall management of an organization’s data to ensure its availability, usability, integrity, and security. The goal is to maintain the consistency and trustworthiness of data throughout an enterprise. As the volume of data and its importance to business continues to increase, attaining this goal becomes more critical to the company’s success.
One of the impediments to developing viable data governance is the fact that there is no magic bullet or simple solution available. Coordinating how information is used by different departments can be a complicated undertaking and demands an iterative approach that incorporates all associated stakeholders. Developing the rules and processes required to control an organization’s data resources may require instituting new roles and responsibilities for individuals and the adoption of previously unused technical tools.
The Risks of Lax Data Governance
From a logical perspective, it makes sense to say that a company should have an overall consistent method of handling its data. But there are concrete reasons that make it more essential than an abstract concept to be discussed by its executive team. There are serious ramifications to neglecting data governance that should be compelling more organizations to take it seriously. An underlying factor that affects the whole data landscape is the emphasis on data privacy and the governmental regulations that have sprung up around the world to address these concerns.
- Identifying malicious activity affecting enterprise data is one of the most critical reasons for a strong data governance program. Data breaches caused by unauthorized access to a company’s sensitive data can result in serious financial penalties being levied by regulatory agencies. Additionally, the negative public relations consequences can cause long-term damage that exceeds the initial fines.
- Common terminology surrounding its data resources is instrumental in an enterprise’s automation initiatives. Poor quality data will hinder the ability to implement automated systems. Inconsistent data may limit the utility of automation efforts to certain areas of the business over others based on the definitions used to develop the systems.
- Staying relevant in an increasingly competitive marketplace is another important reason for data governance. Companies need to be able to quickly react to changing market forces and customer trends throughout an organization. Having the sales, marketing, and production teams speaking the same language goes a long way toward developing rapid responses and addressing the needs of the business. Seeing the data in different ways cannot be a good thing when trying to come up with coordinated business plans.
Building a Data Governance Program
The development of a viable data governance program requires that all stakeholders speak a common language regarding the organization’s data assets. This implies a collaborative effort across the enterprise to identify its information resources and the individuals or teams responsible for it. It’s a complex task that demands the right software tools to perform efficiently.
IDERA’s ER/Studio Enterprise Team Edition is a tool that fosters collaboration across your organization during the construction of an enterprise data model. It assists in developing the common data language that is crucial when instituting data governance. It supports a wide range of database platforms so it can be used as a bridge between the diverse systems that make up most computing environments. The tool allows you to define naming standards, create data dictionaries, and perform analysis to determine where any logical entities are used in physical data models.
Many companies are still lagging in their efforts to address data resources. They do so at their own risk and may well rue the day that they put the importance of their data assets on the back burner. For those enlightened executives who see the utility in giving data the important attention it deserves, ER/Studio can help them on the path to implementing effective data governance.