Overview In every industry today—finance, retail, government, tech, even small business—the real insight often isn’t found in dashboards or formal reports. It lives out in the open: in news headlines, discussion threads, product reviews, and social media conversations. If you can gather that information and understand the tone behind it, you get a clearer picture of what people are thinking long before the trend becomes obvious. That’s the value of combining web scraping  with sentiment...

Overview This solution reads SAP’s built-in DVM statistics (from /SDF/DVM_* tables) using ABAP, exports the data to CSV, and feeds it into a Python analytics engine for: Predicting table growth (using Linear Regression) Detecting anomalies (via Z-Score) Recommending archiving or retention actions Visualizing everything in a Streamlit dashboard PART 1 — ABAP Extractor (ZDVM_EXPORT) Purpose Export SAP DVM statistics (table sizes, growth) from Solution Manager or connected systems to CSV....

Extending SAP Joule with prescriptive intelligence. When SAP Joule  appeared, it gave supply-chain teams a new kind of visibility — the ability to talk  to their data.A planner can simply ask: “Which materials in US01 haven’t moved for 180 days?”“What’s the stock value by age band?” and Joule answers instantly from live SAP tables.That’s powerful — but it’s only the first step. AIS-IO™ (Inventory Optimizer)  picks up where Joule leaves off.It adds predictive insight and optimization,...