XBRL-formatted SEC data is highly detailed because the US GAAP Taxonomy used by public companies to report, gives them the flexibility to select the most appropriate concepts to accurately capture their financial statement data. This “atomic” level of reporting provides analysts and investors the ability to break data down to its component parts, and aggregate them back up into the reporting framework that best meets their analytical needs.
This process, called standardization or “normalization”, structures as-reported data in accordance with a set of norms, set by the user of the data, in order to reduce data redundancy and improve data integrity, so that all the data looks and reads the same way across records in a relational database. Normalization can also be described as aggregating facts reported by various companies into a single line item so that all the companies can be compared.
This session will help analysts, data scientists, accountants, and finance professionals get the most out of working with the vast amount of as-reported XBRL data now available. This is the first in a multi-part series that will include instruction and case studies on how to effectively harness the power of structured data.