Efficient XBRL Data Analysis
Leverage an innovative and cost-effective, XBRL storage model that can help your organization to analyse and extract XBRL data in a simple way.
Analyse your XBRL reports the simple way with the XT Database
The XBRL standard was initially designed to enable standardised business information exchange. However, as the amount of XBRL data being requested has expanded and the volume of reports has grown, regulators have wanted an easy to use system to analyse the data, while enterprises have wanted to consolidate regulatory reports, set up Dashboards and benchmark themselves using XBRL data.
Typical approaches mean shredding the XBRL data to store it in a SQL database, which removes the semantic layer provide by XBRL and requires significant cost effort to maintain.
XT Database was developed to store XBRL documents with the XBRL taxonomy definitions in a standard SQL database and to enable the data to be analysed and reported on using standard SQL-based tools. In addition, it can provide a robust platform to enable XBRL data to be extracted to an independent data warehouse or custom reporting systems.
The Two Faces of the XT Database
The Base Tables
XBRL reports and the relevant XBRL taxonomies are stored in a unique database schema that can represent the complexity of any XBRL taxonomy but also stores each XBRL fact as a simple row in the relational database.
The Reporting Tables
The 'extractor' filters the XBRL base data into the Reporting tables, a flattened version of the schema, that can then be analysed without any knowledge of XBRL structures or from where the data can be readily extracted.
Example analysis using XT Database
Our partners have used the XT Database to produce some very impressive reports and Dashboards, per below
Simple Dashboards produced without major effort.
Reports of any type to meet the users needs.
Alternative XBRL Database Solutions
Today, there are two main alternative approaches to storing and analysing XBRL data.
Adopted for the Oracle Database XBRL Extension, this approach allows for the rapid loading of XBRL documents. To enable query performance over a range of documents, the database vendor needs to provide a mechanism to generate indexed relational views from the XBRL Taxonomy.
Big Data (noSQL)
The growing availability of noSQL databases that can handle a wide range of data types provides another potential platform for the effective analysis of XBRL data. The Big Data approach offers simple load mechanisms, document management, semantic search and, ultimately, a platform for greater use and applicability of XBRL data.
Need help deciding which approach is right for you?
Our consultants can find or tailor a solution for your unique XBRL data storage and analysis requirements. Contact us or learn more about the XT Database below.