(February 19, 2024) Data Governance: They call this the age of “big data,” but sometimes it seems like the age of “bad data.”
An IBM study found that one in three business leaders do not trust the data they use to make decisions. The study estimated that the annual cost of poor data quality is $3.1 trillion in the U.S. alone. Gartner researchers estimate that poor data quality costs organizations $12.9 annually on average.
Poor data quality isn’t just an enterprise IT problem. It affects organizations of all sizes. By undermining decision-making processes, poor data impacts all business operations — from sales and marketing to budgeting and distribution. The scope of the problem expands exponentially as organizations implement artificial intelligence solutions.
A big part of the problem is that we’re inundated with data but haven’t developed the processes or organizational structure to verify its accuracy or value. That’s the role of data governance.
What Is ‘Bad Data’?
Poor data quality results from multiple factors. It may be inaccurate, incomplete, inconsistent, or improperly formatted. Data may also be outdated, duplicated, or unnecessary. A Veritas study found that one-third of data that is processed and stored is redundant, obsolete, or trivial. Over half is “dark” data of unknown value.
Data quality issues disrupt workflows and reduce operational efficiency. Productivity is lost when employees must identify and resolve inaccuracies. Employees may even lose trust in the data, limiting the organization’s ability to automate processes. Decisions based on bad data may result in financial losses and opportunity costs.
Poor data integrity creates another set of issues. Data may have been tampered with or manipulated, or it may be biased, prejudiced, or anomalous. Data integrity problems can be difficult to identify and result in especially bad decisions, particularly when AI is used. Such problems also increase the risk of legal or regulatory liability.
What Is Data Governance?
Data governance is a framework of accountability for data quality. It starts with understanding the impact of bad data on organizational processes and establishing standards for data quality across the organization. The objective is to develop consistent processes for collecting, handling, storing, and retaining data to ensure that it’s standardized and coherent.
Effective data governance recognizes that “perfect” data is unattainable, so it’s also important to define what’s “good enough.” It also recognizes that data quality is not a one-time event. Data should be audited, validated, and cleaned regularly. Outdated and unneeded data should be archived or purged according to retention policies.
Data governance is a subset of an overarching data management strategy, which includes all the processes related to creating, acquiring, maintaining, and using data. It encompasses not only data quality but storage, access, security, and backup. It also includes processes for archiving or purging outdated or unneeded data according to retention policies.
Developing a Data Governance Program
Organizations of all sizes must develop a comprehensive data governance framework to ensure the availability, accuracy, integrity, and security of their information assets. It is important to understand up front that this involves more than installing some software and watching it work.
A sound data governance program requires a framework for identifying who owns and is accountable for data assets. The program should include procedures for storing, archiving, backing up, and securing data. It should also clarify who should have access to data and for what purpose and ensure that compliance requirements are met.
Working with a managed services provider (MSP) can benefit organizations looking to establish a data governance framework. Qualified MSPs have expertise in data storage, backup, access controls, and regulatory compliance requirements. A third-party provider also brings an objective perspective and can help develop a strategic approach that cuts across organizational boundaries.
ABOUT MAINSTREAM TECHNOLOGIES
Mainstream Technologies delivers a full range of technology services in Arkansas and the surrounding region including managed technology services and consulting, custom software development, and cybersecurity services. We also offer industry-leading data center services in our Little Rock facilities. Established in 1996, Mainstream has earned a reputation for delivering quality, reliable, and professional technology services for public and private-sector customers across the United States.
Jeff Pracht
IT Business Development Manager
(479) 715-8629 Office
(501) 529-0008 Mobile
