Zephyrnet Logo

Generative Data Intelligence

Big Data

How to Become a Data Governance Specialist – DATAVERSITY

Republished By Plato
Republished By Plato

Date:

Views: 170
data governance specialistdata governance specialist

A Data Governance specialist is responsible for deploying and enforcing policies and procedures that ensure data is used and maintained properly. Some organizations confuse the title “Data Governance (DG) Specialist” with the title “Data Governance Manager.” The DG specialist is not a member of upper-level management and does not dictate policy. This person, however, must still have good communication skills, as they may be asked for feedback by managers, and guidance by staff. The primary responsibility of the Data Governance specialist is to promote efficient, accurate records, and effective information management throughout the organization. Additionally, this person may act as a liaison between work teams and data support teams.

Data Governance is a form of Data Management that focuses on the ability of organizations to ensure that Data Quality is excellent throughout the lifecycle of the data. The basic fundamentals of Data Governance include usability, consistency, availability, data security, and data integrity.

Implementing a DG program establishes the processes needed to ensure effective Data Management and accountability throughout the organization. A good Data Governance program will include a governing body/council, a documented description of DG procedures, and a plan to incorporate those procedures.

Generally, a DG specialist will have a bachelor’s degree in a field related to computers (information technology, computer science) and one to four years of experience. However, a combination of computer and communication skills is needed for this position. Lots of technical experience can stand in for a bachelor’s degree, but the lack of a degree will limit chances for advancements and promotions.

Some employment advertisements will require a Data Governance and Stewardship certification. The certification process typically requires a degree, attending a workshop, a test, and a fair amount of experience. Certification can be difficult to get, in part because there are very few organizations offering it. This requirement may be an unrealistic expectation on the part of the employer, particularly for non-management positions.

The Data Governance Specialist’s Responsibilities

The Data Governance specialist will evaluate concerns in governing data, including problem definitions, opportunity and solution recommendations, and root cause analysis. Examples of a DG specialist’s responsibilities include:

  • Maximizing the income potential of data
  • Increasing confidence and consistency in the quality of data
  • Eliminating or minimizing rework
  • Minimizing the risk of regulatory fines
  • Optimizing staff effectiveness
  • Working with data security

GDPR and Data Governance

The introduction of the General Data Protection Regulation (GDPR) has dramatically changed how companies now handle data. The guidelines of the General Data Protection Regulation describe how data should be handled all across Europe. Its purpose is to protect the rights and privacy of European citizens. The GDPR and Data Governance go hand in hand, with a strong DG program providing the data visibility and categorization that are necessary for GDPR compliance. And it will help in finding and prioritizing security risks and make the verification of compliance by GDPR auditors much easier. If an organization is doing business in Europe, management, administration, and staff need to become educated on GDPR issues so that compliance is built in at a cultural level.

An organization implementing a good Data Governance program and the supporting technology can use their current computer architecture and data assets while ensuring GDPR compliance. The importance of data lineage cannot be overstated in the context of GDPR. Consider the European citizen’s Right to Be Forgotten as an example. Compliance with the GDPR requires a method for locating all the data in an individual’s personally identifiable information (PII) as well as any cross-referenced information that can used with other data points to create a PII file.

Challenges in Data Governance

One major problem facing businesses that have decided to install a DG program is the discovery that raw data is generally not analysis-ready. Their data is often poorly organized, unstructured, and stored in a variety of separate databases. Data Governance cannot progress smoothly and efficiently without cleaning and normalizing the data. Installing a new Data Governance program may require significant manual labor, but after a uniform system is established, new, incoming data should automatically be sent to the appropriate location.

Data silos are another problem for Data Governance. Data can be locked away, and only accessible to certain teams or individuals. Different departments may operate using entirely different systems, and these departments may have no understanding of the data they are storing nor the potential value it has. Data Governance provides a framework that allows access to this data and breaks down those silos. Additionally, some departments may attempt to “hide” their silo from the Data Governance program.

Best Practices in Data Governance

Though Data Governance has become a focus for several organizations, there has been some frustration with DG implementations that did not return the anticipated results. A well-designed DG program, implemented with the help of a Data Governance specialist, includes long-term planning, a list of staff using the data, a governing council, and clearly defined procedures. The transition to a Data Governance program should include creating comprehensive metadata management to locate and use the data. Some best practices are listed below to help avoid commonly experienced problems:

  • Think big picture, but start off small: Data Governance involves people, processes, and technology. These three factors are important when planning and implementing the program. It is important to start at the beginning with an understanding of long-term goals. The most efficient plans start with the people (and communication of the goals), move to the process, and then plan the technology – with each component in the plan building on the evolving structure. The right people will work effectively with both the process and the technology. After identifying the needed staff, clearly define a DG program, and implement the technology that is needed.
  • It is important to measure progress, and “advertise” the changes and improvements to the staff.  Changes should be measured and monitored from the start, and on a consistent basis. These measurements will prove there is overall progress and improvement. The measurements can be used for comparisons, assuring the process is actually working – in both practice and theory.
  • Communicate frequently. Effective and consistent communication is important in most business operations. It is a useful way of educating staff on the changes taking place. Explain to the staff the opportunities and benefits that improved Data Quality will bring the organization. Bulletin boards and emails can reinforce the information that was shared verbally. By explaining the increased opportunities, staff will understand the need for change.

Much of Data Governance is actually about changing habitual behavior. When changes are made, it is common for a team to be assembled to execute the project. A Data Governance program must be presented as a practice and not a project. Projects have start and end dates. A practice, on the other hand, is woven into the organization with changes in behavior. The Data Governance program should not be treated as a project, but as the evolution of the work culture. Data Governance specialists are at the center of such work.

Image used under license from Shutterstock.com

spot_img

Latest Intelligence

spot_img

Copyright @ 2024 Plato Technologies Inc.