Sinara’s Universal Data Extractor (UDE) is a highly configurable software application that allows both financial market data providers and data consumers to identify and extract key data items from a variety of data sources such as news stories (e.g. LSE’s RNS), spreadsheets or PDFs.
Although many sources and news feeds are making increasing use of tagging and metadata through schemes such as XML, XHTML, etc, most data items in such sources are still often in free text within the body of the document.
UDE utilises advanced technology and intelligent algorithms to perform a deep level of data extraction from such content. UDE can be tailored to individual customer requirements, making it a useful tool for a range of data extraction requirements.
For example, many financial data vendors need to gather and process a wide variety of source data in order to produce their own data products. This source data can be delivered in a number of formats (e.g. text, flat files, data feeds, PDF documents, XML, etc). The task of identifying and extracting the key information from these sources can be both time-consuming and costly.
- UDE can be configured to extract specific data fields from the source data
- Produce the core data in a single format required by the vendor
- The UDE output can then be exported into the vendor’s own workflow systems to verify the content before passing into their own products.
News-based content is also an increasingly important part of trading strategies, which are often influenced by news stories such as results announcements:
- UDE will be of benefit to hedge funds, traders or broker/dealers who want to use such content to enhance the performance of their automated trading algorithms.
- UDE can extract important data from these announcements quickly and accurately, to make key values (e.g. turnover, profit, dividend payments, etc) available to a client’s trading algorithms.