There is no single, industry-wide definition of data integrity. However, one possible paraphrase is that it is about trust in the information that executives use to make decisions. This means having accurate, consistent, and complete datasets. It also means understanding the overall context of the information, enhancing it with data enrichment, and complementing it with location intelligence.
There are four pillars of data integrity: integration, data quality, data enrichment, and location intelligence. All four are essential, but for many organisations, integration is the foundation without which the other three pillars cannot reach their full potential. Integration ensures that data can be synchronised across multiple platforms, information is up to date, and relevant data can be brought together to deliver its maximum value in conjunction with advanced analysis methods.
The Hard Way Of Integration
Two decades ago, integration was much more complicated than it is today. Application programming interfaces and access protocols were much less standardised. Even today, creating point-to-point integration between two or more business applications can be expensive and time-consuming to develop and maintain and support.
This effort grows exponentially as the number of connections within a company grows. It’s hard enough to connect two systems (a CRM system and an ERP application) in which information updates need to be detected. This is followed by mapping and conversion and finally synchronisation, either in real-time or batch mode. Reliable mechanisms for error detection and guidelines for correction are essential and must re-enter the changes that caused the errors.
There are additional challenges for organisations with mainframe systems due to the disparities between the file formats and structures used by such methods and the file formats used in modern computing systems, including the cloud.
If everything is set up from scratch, connecting just two systems is already a lot of work. Having the exact mechanisms for integration between three different applications increases the scale and complexity of the project. Each additional connection point complicates things considerably.
When an application changes (for example, changing a CRM system), the integrations need to be redesigned or rewritten to match the difference. Mergers and acquisitions result in a company-wide reconfiguration.
Enterprise-Wide Integration: Done Right
At a certain point, developing and controlling point-to-point integrations becomes too cumbersome. Organisations using multiple systems need a solid plan for enterprise-wide integration. You need an automated approach that easily adapts to change and allows administrators to quickly and easily design data pipelines, place them anywhere, and reconfigure them without disrupting operations.
Integration guarantees consistency across many systems within an organisation. It ensures that data “tells the truth, the whole truth and nothing but the truth” in every information system throughout the enterprise.” When users find this form of consistency and completeness in all the applications they need, they have data integrity.
How Data Integration Increases Company Value
In the end, it’s all about increasing the company’s value. Integration makes it possible to standardise data across multiple systems and enrich it with third-party information to improve the depth and importance of insights. The integration enables companies to develop a comprehensive, 360-degree view of customers and perform more extensive analysis based on this information. This leads to new insights and better business decisions.
For example, suppose an insurance company can understand critical moments in the lives of its policyholders, such as the birth or graduation of a child. In that case, the insurance company can adapt to clients’ individual needs by selling new products or anticipating potential Termination and how to avoid them before they happen.
At the same time, serving the individual customer is far better when all of their contracts, calls, purchases, and other activities are in an everyday context – mainly when that information is scattered and fragmented.
At its core, it’s about avoiding data silos. Effective enterprise integration is about doing it at scale and recognizing that the integration needs to keep pace as things change. Recent events have prompted companies of all sizes to refocus on agility. Enterprise-wide integration provides this skill by making it possible to build products once, place them anywhere, and adapt to changing circumstances.
Data integrity resulting from this integration also drives agility, allowing for trusted analytics. When leaders look at the big picture, they can be better prepared to act quickly in unexpected changes when they understand what’s happening both inside and outside the organisation.
