PQI more valuable than its individual components

With terabytes of data moving through companies today, effective business intelligence (BI) is achievable through systems that can support such masses of data, and BI software that turns this data into valuable information. However, any attempt to improve your business using BI tools is useless if your data is not correctly profiled, is of poor quality, or you suffer from integration issues.

It is generally accepted that companies embarking on BI initiatives, or those wanting to enhance the value they receive from their existing BI tools, must ensure the necessary systems integrate smoothly with each other to enable the rapid movement of data between and through them, and that the data exchanged between them is of the right quality.

Poor quality data can result in ill-informed business decisions, poor customer relationship management (CRM), and regulatory non-compliance, while inadequate integration can weaken BI systems, and increase the cost of performing BI.

Although companies are beginning to understand the need to profile their data, ensure high data quality, and enable integration, most are doing these as three separate projects. The business can achieve more value if companies approach profiling, quality and integration (PQI) as a single project.

The value of BI systems relies heavily on the quality of a company`s data.

Charl Barnard, GM, Knowledge Integration Dynamics

As a key element of data cleansing, data profiling enables companies to understand their data, and the processes of how it is compiled and acquired. It is an analytical process, which creates metadata from existing content and provides insight into the business logic behind data construction.

Companies are faced with overcoming the challenges of their data being trapped in silos of disparate, proprietary systems; the exponentially increasing amount of data being stored in these systems; and the inaccuracy of much of this data.

The key to data profiling is that it does not change the data in a company`s databases. Rather, it discovers what data actually resides in each column and row, and creates a map for the business to follow.

The value of BI systems relies heavily on the quality of a company`s data. Data is becoming more complex, with companies collecting and retaining mounds of data, from customer, product, warehouse and financial data, to partner, vendor, supplier and employee data.

However, more often than not, this data is of poor quality. As Gartner research shows, in the financial services sector alone, more than three-quarters of companies make decisions based on poor data. Its research also indicates that more than 25% of critical data used in large companies is flawed. Flawed data corrupts and undermines almost every IT and BI project.

Corporate data is a key strategic asset and the goal of data quality management is to provide the foundation for creating information and knowledge. The benefits of good-quality data include cost savings; improved decision-making; better customer service; improved chances of marketing success; new opportunities to cross- and up-sell; improved forecasting accuracy; smoother operations and supply chain management; and regulatory compliance.

The information that runs a business resides in different formats across countless systems, from enterprise resource planning (ERP), to CRM, financial management, and customised in-house systems.

However, if these systems cannot communicate with each other or share data, the value they hold for the business is limited, and the less capable they will be to cater to the individual information needs of users, regardless of how well profiled the data is, or of its quality.

Profiling, quality and integration make up the cornerstones of the PQI triangle. If one of them is removed, that triangle no longer exists, and the effectiveness of PQI in enhancing a company`s BI initiatives is reduced. Applying PQI as a collaborative effort, rather than performing profiling, quality assurance and integration on their own, enables a company to successfully turn its data into an asset that can be leveraged.