Accruing large amounts of data and the need for streamlined examination of that data—in terms of efficiency, analysis/recovery speeds, and accuracy, etc.—are on a collision course. The move from process-centric to data- and memory-centric computing is already having an impact on current computing trends. This change bodes a completely new approach to understanding data sets and requires new capabilities to perform fast, efficient data analysis. It will also mean new hardware and software resources as well as efficient tagging capabilities.

Although big data has definitely been over-hyped, companies will soon make smarter decisions by using analytics to comb through huge amounts of, for example, financial data using XBRL tagging. Instead of making hypotheses, performing analyses and reaching conclusions that are often wrong, financial business users can use data tagging tools such as DataTracks UK managed iXBRL tagging services to gain a quick understanding of where decision drivers lie in large data sets.

“Our tagging software has been upgraded to ensure consistency between XBRL tags chosen for comparable data between current year and last year.  This feature improves the accuracy of iXBRL tagging,” said Sneha Rajagopal, vice president of Global XBRL Services. The company is a worldwide leader in preparation of financial statements in XBRL and iXBRL formats for filing with regulators, and the company DataTracks UK is part of DataTracks Global.

XBRL tagging is the process by which any financial data is denoted with the most appropriate element in an accounting taxonomy (a dictionary of accounting terms) that best represents that data. In terms of large amounts of data, financial information can be quickly extracted using XBRL and iXBRL tagging formats into financial models in spreadsheets without having to worry about what the information represents or spending time reading and keying-in data.

eXtensible Business Reporting Language (XBRL) has emerged as the most widely accepted form of disseminating financial information thanks to sponsorship by a consortium of security regulators, stock exchanges, financial publishing houses, accounting organizations and corporations. Businesses will be more able to take advantage of big data due to advances in analyzing and XBRL processing of large financial-based datasets. For companies who are currently suffering from data overload, these abilities will present huge opportunities for succeeding against their competitors. Similarly, for workers in the IT field, there is a clear opportunity to capitalize on big data processing.