Barclays Research Open Sources Alt Data Tools

Barclays Research Data Science have released their first open-source code tools to help users query the most popular financial research databases according to a story in MarketsMedia news. Ryan Preclaw, head of research investment sciences and Adam Kelleher, chief data scientist for research at Barclays investment bank, said in a report that analysts are using diverse data sources alongside traditional financial data such as filings, earnings call transcripts, which requires them to use modern technology for data analysis. “A single project might require SQL queries, boto get requests, Spark read operations, manipulating local excel sheets, and more,” they said. As a result, Barclays’ research data science team built a tool for themselves to make it more efficient to use a new data set, which they said has been a major contributing factor to more-than-linear rate of productivity growth with time. “When we work with a new data set, usually as part of a research project, we encapsulate the ETL (extract, transform, load) code and add it to the tool,” they added. “This makes it a push-button capability that is ready the next time we need to use it.” Subsequently, they can usually perform the same operation with only a single line of code. Barclays believes these tools will be useful for others who do financial research as they create higher quality control for queries and enable reproducibility by standardizing pre-processing on broadly available data sets. The tool is designed to abstract data sources from the end user and to present a standardized interface for working with financial data through a data access layer and an API layer.