Unit 6 Project: PowerBI Lab Project Reason In this fingers-on lab, you would possibly put collectively what you’ve learned about synthetic intelligence (AI) and analytics to interchange recordsdata. You’ll exhaust Energy BI to load, rework, and visualize recordsdata, then elaborate insights the exhaust of developed AI visuals. This project helps you hide your ability to: Dispute statistical and analytic ways to uncover change recordsdata. Earn and elaborate insights, developments, and anomalies. Communicate recordsdata-pushed suggestions via decided, interactive visualizations. Associated Abilities Loading, cleaning, and transforming recordsdata in Energy BI. Constructing calculated columns and measures (as an instance, earnings margin, growth rates). The exhaust of AI-enhanced visuals: Key Influencers, Decomposition Tree, Anomaly Detection, and Q&A Visuals. Designing an interactive, legit dashboard that communicates insights successfully. Writing short fable explanations that elaborate your findings. Dataset and Resources Data to make exhaust of: sales_data_sample.csv Walkthroughs / Tutorials (optional but if truth be told helpful): Influencers Decomposition Tree Anomaly Detection Key Influencer Visible (Video) Microsoft Study: Decomposition Tree Anomaly Detection (Video) Q&A Visuals (Video) What You’ll Develop Step 1: Data Ingestion and Preparation Open Energy BI Desktop and import the dataset (sales_data_sample.csv). Evaluation your recordsdata and beautiful any issues: repair recordsdata kinds, rename columns, and achieve decided that that date and class fields are formatted accurately. Variety calculated columns or measures to add change that system (as an instance, Profit Margin = Profit / Revenue or 365 days-over-365 days Enhance). Build your file recurrently as you’re employed (YourLastName_U6.pbix). Step 2: Earn Your AI Visuals Key Influencers Visible Resolve one critical metric (as an instance, Gross sales, Revenue, or Profit). Dispute the Key Influencers visible to identify which factors most strongly affect that metric. Evaluation the outcomes and hide which classes or fields force efficiency. Decomposition Tree Visible Add a Decomposition Tree to your portray. Dispute it to crumple your chosen metric (e.g., Gross sales) by reasonably a couple of classes equivalent to Living, Product Category, or Time Period. Allow users to uncover the strategies interactively by drilling down into particulars. Anomaly Detection Variety a time-sequence visible (line or space chart). Note anomaly detection to spotlight ordinary spikes, drops, or deviations. Perceive which events or time sessions level to anomalies and hypothesize doable causes. Q&A Visible (Natural-Language Exploration) Add the Q&A Visible to your dashboard. Check it by typing a couple of pure-language questions, as an instance, “What product class had the bottom sales final quarter?” Be definite that your dataset is successfully-labeled so queries return meaningful answers. Step 3: Variety Your Dashboard Combine all four visuals (Key Influencers, Decomposition Tree, Anomaly Detection, Q&A Visible) correct into a single, beautiful dashboard format. Add titles, legends, labels, and quick annotations so each visible is easy to love. Dispute consistent colours and formatting to accomplish your dashboard legit and decided. Step 4: Define Your Insights In a snappy summary (approximately one web exclaim of notes or text box within your Energy BI portray): Notify at the least three key insights from your visuals (e.g., factors that force sales, surprising developments, or anomalies you chanced on). Sign what these findings would possibly presumably mean for a change option maker. Counsel one or two easy, recordsdata-pushed suggestions based entirely totally on your diagnosis. Submission Pointers Post one Energy BI (.pbix) file. Contain your visuals and short fable interpretations. Contain the common dataset (sales_data_sample.csv). Build your file as: LastName_FirstName_U6_PowerBI.pbix.
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