What is Data Integrity?
Confidence is everything. In successful businesses, it comes from the ability to make clear, timely decisions based on trusted data. But data is complicated, and 84% of CEOs are concerned about the integrity of the data they base decisions on. This is despite significant investments their businesses have made in managing data more effectively.
When data is difficult to find, flawed, or misunderstood, it disrupts business. Decisions are made on instinct alone or not at all, destroying value. That’s why businesses need data integrity. But what exactly is it? Many proposed definitions focus on data quality or its technical aspects. But organizations must approach data integrity from a broader perspective.
Data with integrity is trusted because it has maximum accuracy, consistency, and context. It is available whenever and wherever it’s needed, empowering organizations to make fast, confident decisions that can help you add, grow and retain customers, move quickly and reduce costs, and manage risk and compliance.
Data integrity is not just about accuracy and consistency, which are key data quality characteristics. It is also about data having rich context. In the case of customer data, for example, it means understanding what drives purchasing behavior. It’s about understanding demographics, lifestyle, and critical events impacting consumer needs. It’s also about location, knowing where your customers live, work, and play.
Data integrity also requires the entire tapestry of data sources throughout an organization to be woven together so that business users can develop a complete and meaningful picture of the things that matter most to them. That requires data integration to unlock the information stored in siloed systems.
Data quality issues often present a significant challenge to data integrity. Inaccurate, non-standardized, and incomplete data diminishes the potential of business analytics, artificial intelligence, and machine learning, even in a best-case scenario. In the worst case, it renders results invalid. A sound data integrity strategy includes data quality solutions capable of standardizing and validating data, identifying gaps or discrepancies, and data observability capabilities to uncover data anomalies and trigger workflows and processes to correct those errors at scale.
Finally, data integrity requires a practical framework for data governance to oversee all other aspects of integrity and ensure the organization complies with best practices for security and privacy and all necessary regulations.
The journey to data integrity begins with business value
Data integrity is not a binary all-or-nothing proposition, and it’s a journey that will look very different from one organization to another. There is no one-size-fits-all approach. The data integrity journey often begins with initiatives around specific projects, where the impact of data integrity efforts is readily visible, and its results deliver business value across many different teams across the organization.
For example, improving the customer experience might begin with breaking down the silos between mainframe systems, digital marketing automation, and CRM and ensuring that all systems using data are kept current with changes to transactional systems. That effort may reveal data quality issues that must be addressed, correcting system discrepancies, identifying anomalies, and proactively managing quality going forward. Finally, the project team may identify a need for external data sets to enrich the company’s internal customer data with demographic, lifestyle, and geospatial information — all of which provide essential context.
Or a data integrity initiative may begin with the need to establish policies for safeguarding customer information, controlling unauthorized access to data, and documenting compliance with all relevant privacy and data sovereignty regulations. The solution, data governance, will also enable you to answer essential questions about your data usage, impact, and lineage. A data governance initiative may lead you to identify and address data quality issues — and so the data integrity journey continues, increasing confidence in data across your organization and producing more accurate, informed decisions and reporting.
Starting your data integrity journey with the right tools
The Precisely Data Integrity Suite delivers value at every step along the data integrity journey, regardless of how your company may choose to approach it. The Precisely Data Integrity Suite enables your business to build trust in its data through market-leading data integration, data observability, data governance, data quality, geo addressing, spatial analytics, and data enrichment capabilities. These core capabilities deliver value at each step on your journey to data integrity – data that is accurate, consistent, and filled with context.
The Precisely Data Integrity Suite contains everything you need to deliver accurate, consistent, contextual data to your business – wherever and whenever it’s needed. Learn more
In a recent IDC survey of 310 business and data analysts, nearly half of the respondents indicated a general lack of trust in data quality, and 56% indicated a lack of trust in the results of data analysis. This lack of trust is not the source of the problem – it is a symptom of the data. Data integrity provides a firm foundation for data analytics and confident actions. Accuracy and consistency in data, enhanced with context through location and enrichment, can help companies achieve data integrity
Over two virtual days, Trust ‘23 – the Data Integrity Summit, brought together global data leaders, analysts, and experts to share trends, challenges, and opportunities happening in the industry. And great news, all of the content is now available on demand! Learn more.