In this post we want to introduce you to an innovative concept – that of the exception control system. The exception control system allows you to be more precise with your data management, adding an extra layer of rules and policies that is specific to handling anomalies. The idea behind this concept is that data anomalies management can also be used for improving procedures. By knowing where the anomalies are, you can learn to either prevent them from occurring or be aware of when they can occur and be prepared to take the required steps to handle them. This will result in overall improvement of business practices.
TripleCheck is designed to help you create an exception management procedure. For example: by monitoring anomalies within your source systems data, which are connected to your customers and suppliers, you can make sure you are working only with the best suppliers and manage your customers optimally. By monitoring anomalies within the company you can make sure they do not reoccur, or ensure that you react quickly when they do happen, thus improving your own procedures and enhancing the quality of your product and service.
A BI system is designed to provide your business the possibility to review and analyze your data. A data exception control system does more than that, it presents the so called “wrong” data, showing you the exact place where improvement can be made – taking your BI the extra mile and expediting business growth.
The difference between BI and exception control platform
There are four (4) major differences between a BI system and a data anomalies based exception management system:
Scalability: Gathering all data anomalies and problems in one unify place allows grouping them by business impact categories and prioritizing between problems, giving the company a comprehensive view of all the issues. Minimizing the impact of data anomalies by using exception management enables enhanced scalability of the source data systems supporting business growth.
Efficiency: An exception control and management system presents every exception immediately when it occurs on the main dashboard. You do not need to look for these issues in specific reports. Companies will know on the spot what their important data anomalies and problems are. Transitional BI systems only present the data when they are asked to do so. The same data will be presented repeatedly according to the query. The exception management system presents an accurate data anomaly report in real-time and allows for approving/ marking “wrong” data, so that the true data anomalies can be dealt with and the repeated data review process is avoided.
Velocity and Cost: ETL and BI development is time consuming and expensive. Using the data warehouse with best practice requires an ETL process, BI end user layer administration, cube process, reports and dashboards. Moving the data requires extensive development and comprehensive quality checks. With an exception control system, most of the specific data problems and anomalies can be detected without the need to move irrelevant data, and by the business users.
Reciprocity: Funny as it sounds, BI systems are also data source systems for an exception control system. Every movement of data can cause data anomalies and can create new data problems. For example, dimensions or facts that were not updated due to technical error. An exception control system will analyze the difference before and after loading/ moving the data.
Exception management facilitates business growth
With an exception control system you can make sure that your data source systems are clean and healthy. You know that you monitor and control data anomalies and other data problems to improve both your data base and the quality of your product or service. You now know that you can rely on your data to be more accurate, you can improve your procedures and make enhanced business decisions. With an exception management solution you are continuously supporting data scaling without creating new data problems, thus facilitating efficiency and business growth.
We invite you to learn more about data inaccuracies and data anomalies, and the impact they have on your business decisions in our previous posts.