Introduction

Today, business decisions are based on vast amounts of data, making quick access to data crucial for making the right decisions at the right time. The advent of big data and the explosion of data sources provide organizations and data scientists with a wealth of information. However, extracting meaningful data is still a problem, which makes data aggregation important. How important? let’s find out.

A process in which data is searched, gathered, and presented in a summarized, report-based form, data aggregation helps organizations to achieve specific business objectives or conduct process/human analysis. A step that occurs between data and analysis, data aggregation employs several different tools to search for and collect data. Data aggregation is a critical part of effective data management and here are the reasons why.

What Makes Data Aggregation Important

While organizations understand the importance of data analysis and data quality, they often overlook data aggregation in data management. This can be detrimental. For example, various financial instabilities that occurred during the recession and in other times of economic downturns, have proven risk aggregation to be one of the weakest links in the technology and risk architecture of most companies.

The above hinders the efficient and effective risk-based decision making that allows organizations to improve their responses to both internal and external catastrophe. For this reason, financial institutions—especially banks, are advised to aggregate risks across various spectrums.

This means that the risks dealt at individual levels, such as credit risk for trading, must be measured, monitored and supervised across business lines and possibly legal entities. Put simply, organizations must aggregate and analyze all risks to determine the total its total enterprise risk. This is the key to effective risk management.

In addition to risk management, data aggregation can help in Key Performance Indicators (KPI) reporting. Data aggregation minimizes the number of rows to be queried to obtain the KPI values. This dramatically reduces the time required to refresh the KPI dashboards, which in turn reduces resource consumption and end user wait time.

Here, data aggregation consolidates vast amounts of detailed data into higher levels of dimension hierarchies. For instance, store each individual transaction is no longer required. You can simply group large sets of transaction rows, based on the transaction type and the month they occurred, into just a few rows. This makes it easier to manage data.

Choosing an Effective Data Aggregation Solution

Since 90% of all reports contain aggregate information, implementing a data aggregation solution can help you generate significant performance benefits, while allowing to enhance your data analysis and reporting capabilities. But, how do you choose an effective aggregation solution? By looking for the following seven qualities in the solution:

  • Enterprise class solution that can support dynamic business environments
  • Flexible architecture
  • Superior performance including speed, quality and responsiveness of the application
  • Scalability
  • Fast implementation
  • Efficient use of hardware and software resources
  • Cost effectiveness

Conclusion

Where can you find such a data aggregation or data management solution? You can truly find it with us and our proven field-tested solutions. Contact us today for more information.