Data Governance, Data Quality Issues, and the Cost of Dirty Data

Data Governance, Data Quality Issues, and the Cost of Dirty Data

Data governance enables positive business outcomes by aligning people, processes and technology to ensure consistent, proper handling of enterprise data.Outlined below are the three core business practices that form the trifecta of enterprise data governance that helps businesses maintain order, clarity, and trust in their operations.

 

Data Governance Principle, EnforceEnforce: paired with a clipboard icon, underscoring the importance of implementing and upholding policies that ensure regulatory compliance. This practice is crucial for businesses to operate legally and ethically, often involving detailed oversight and adherence to established standards and laws.

 

Data Governance Principle, StandardizeStandardize: denoted by a bar chart icon. This points to the need for uniform business terminology and the transformation of reports. Standardization is key to maintaining consistency, reducing misunderstandings, and enhancing efficiency within business operations. It allows for coherent communication across various departments and among stakeholders.

 

Data Governance Principle, EnsureEnsure: indicated by an icon with directional arrows, represents the commitment to maintaining data availability and quality. Reliable and high-quality data is fundamental for informed decision-making, strategic planning, and the continuity of business operations. This involves establishing robust systems and processes that safeguard data integrity, accessibility, and security.

 

Can you afford the cost of dirty data? 

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Businesses have witnessed an unprecedented surge in the volume of corporate data since 2015, with an astounding average annual growth rate of 40%. However, amidst this data explosion, a troubling trend has emerged - approximately 20% of the average database is contaminated with what is commonly referred to as "dirty data." This term encapsulates a range of data quality issues, from inaccuracies and inconsistencies to information that is improperly sourced or recorded within the database.

The ramifications of neglecting to address dirty data can be far-reaching and severe. Distorted analytics, flawed decision-making processes, and a general hindrance to the efficiency and success of business operations are just a few of the potential consequences. The financial implications of failing to rectify this issue cannot be understated.

While it may be tempting to overlook the impact of poor data management, the costs incurred are undeniable. Consider this scenario: with an average cost of $100 per dirty record and a database containing 100,000 records, the financial burden of harboring bad data can accumulate significantly over a five-year period. It is imperative for businesses to recognize the importance of enterprise data governance and invest in measures to ensure the integrity and quality of their data assets.

 

Harness the Value in Your Organization's Data

By creating a structured system for your company to utilize the data, you can achieve a faster outcome of projected trends and insights that can change your business dramatically. Not everyone needs to be a data scientist to understand the impact of any new data entering your records. Garnering control of data governance in your organization is essential for maximizing the value of your data assets. 

When it comes to enterprise data governance, a systematic and strategic approach is essential for ensuring the integrity and utility of an organization's data assets. This involves a spectrum of activities, including:

  • Clarifying ownership, responsibilities, and data roles, such as appointing data stewards who oversee data quality and integrity.

  • Developing robust Business Processes for Issue Management, Enhancement Requests, Change Management, and strategic Data Architecture planning to ensure a streamlined data management approach.

  • Defining, reporting, and tracking Data Quality of Key Data Assets to ensure that your data is accurate, reliable, and consistent.

  • Standardizing reports, transformations, and calculations to promote uniformity and enhance data interpretation across the organization.

  • Ensuring data consistency across organizational platforms to facilitate seamless data integration and decision-making processes.

By implementing these practices, your organization can establish a strong foundation for effective data governance, enabling you to harness the full potential of your data and drive strategic business outcomes.

 

Uncovering the Impact of Disorganization and Redundancy

Research reveals that Data Citizens are wasting vast amounts of time, effort, and money navigating through a tangled web of disorganized, chaotic data landscapes. This jungle of data is overrun with inconsistencies, inaccuracies, and outdated information, creating a daunting challenge for those seeking to extract valuable insights. To compound this issue, the presence of data duplicates further complicates the data ecosystem, leading to confusion and inefficiencies.

Over a quarter of their valuable time is consumed by the arduous task of sifting through this data quagmire in search of the information necessary to fulfill their job responsibilities. A staggering 40% express feelings of being overwhelmed by the sheer volume of data, making it a daunting task to locate the specific information they require. More than half of the data gathered turns out to be irrelevant to their initial search query, highlighting the struggle to pinpoint relevant and accurate data. Additionally, 40% admit to relying on incorrect information at least once a week, underscoring the urgent need for a more streamlined and efficient data governance program as part of an organization's overall data strategy.

 

Over 25% of their time is spent searching for info needed to do their jobs. About 40% complained of being overwhelmed with info –finding it difficult to find the right info amongst the clutter.
Greater than 50% of the info gathered was irrelevant to their original search request. 40% admit to using wrong information at least once a week.

 

In light of these challenges, it is evident that businesses must prioritize the implementation of robust enterprise data governance measures to address the complexities of their data landscape effectively. By embracing data governance principles and leveraging modern data management tools, organizations can streamline their data processes, enhance data quality, and unlock the true potential of their data assets. With the right approach to data governance, businesses can navigate through the data jungle with confidence, clarity, and efficiency, paving the way for data-driven decision-making and sustainable business growth.

 

Tailoring Data Governance: Understanding and Enhancing Data Knowledge Across Diverse Business Landscapes

Not every company is in the same place when it comes to the knowledge of data that they may have. That is why there are so many various solutions and tools, like a data catalog or data dictionary, to how a business can begin to improve their understanding. Addressing the scope of the ways of improving data governance, research and advisory firm Gartner organizes the tactics as distributed, deliberate, centralized, and emergent. 

 

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Achieving Data Nirvana, where the right people, processes, data, timing, and technology align seamlessly, hinges on making agile data governance a central pillar of your modern data stack. Let SME Solutions Group lead you on the journey to data enlightenment and optimization.

 

 

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