Having Fun with Opait Report Miner
Step One: Acquiring Data Files
We used publicly available quarterly reports from the Home Depot Website for the years 2013-2015. One PDF report for each quarter (10-Q and 10-K), for a total of 12 documents. Each report had standard financial tables such as Cash Flows, Balance Sheets, Profit & Loss Statements and so on.
Step Two: Defining Data Model
We opened 2013-Q1 report in Opait Report Miner, located the Cash Flow table and drew two selection rectangles (rubber bands) to tag the specific table for extraction.
Step Three: Building the Model
We used the Opait Report Miner automation API to run this model against all 12 quarters, picking a single column from each, and building a 12 columns data table. We then plotted the Net Earnings values for each quarter:
Home Depot business is indeed seasonal with maximum earnings during Summer building months. It also has a growing trend on a year by year basis. All this insight from drawing two rubber bands! The power of RPA at work.
Data mining can be simple and fun!
Opait Software specializes in high quality extraction of structured data such as fields, tables, sections and paragraphs from unstructured documents in many file formats. Automatic identification and extraction of tabular data, as well as, tagging and filtering NLP elements of PDF documents allows advanced analytics, RPA automation and semantic search using data trapped in PDF and other unstructured documents. These data-mining products are particularly suited to financial modeling and analytics. Automatic processing of statements, remittances, bills, financial reports and contracts are some applications of this technology.