The demand for automating day-to-day procedures is growing daily. On top of that, billions of bytes of data, multiple data sources, and hours of manual work put into sorting it all out, make these procedures hugely complex and time consuming.
Since January 2018, the Data Visions Team at Siemens has been developing analytical ‘products’ to support the Digital Industries (DI) strategy and drive a data citizen approach for future collaboration - preparing for the time when data science will eventually become a commodity. The team has made it possible for not only data scientists to work with data, but also data citizens – those charged with pulling insights out of data – to make decisions and drive change.
Today at Siemens over 3,500 data citizens globally are working better and more independently with data using KNIME Analytics Platform and other integrated software. KNIME has also become an invaluable tool for Robotic Process Automation (RPA), by completely automating many mundane, manual tasks. This has freed up lots of time to work on other areas of the business.
One of the more recent projects that the Data Visions team got involved in, was automating competitive analyses using financial statements from the internet. The projects’ objectives were to search for financial reports on company websites, extract relevant financial statements out of the PDF reports, and transform the statements into a structured format and prepare an internal report. From a business perspective, the requirements were to:
Previously, the user did a manual website check of the competition with (often) incomplete information. The repetitive task of analyzing competitors was repeated every quarter in a manual and time-consuming process: search competitor website for PDF, extract relevant information, prepare finance report, send to management. The Siemens Data Visions team built a process using KNIME Analytics Platform to automate this entire process. A KNIME workflow, built by a team of data scientists, crawls the competitor’s website and downloads financial reports as PDFs. This step is repeated automatically across different websites. The same KNIME workflow then applies data mining, classifies document types, and extracts values out of the PDF. Then using the KNIME Integration with Tableau, a report is created and published in an interactive dashboard. Here, the end user can simply open the dashboard and view the results. KNIME has saved this person approximately 30 hours every quarter. That time is now spent on valuable tasks such as analyzing and interpreting the aggregated statements.