{ "item_title" : "Python-Enhanced FP&A Systems", "item_author" : [" Danny Munrow", "Hayden Van Der Post "], "item_description" : "Reactive PublishingPython-Enhanced FP&A Systems: End-to-End Automation for Forecasting, Budgeting, and Executive Reporting delivers a complete, modern blueprint for transforming the finance function from manual, spreadsheet-driven workflows into a high-velocity, data-driven operating engine. Designed for analysts, managers, directors, and CFOs who want to build real automation capability, this book shows exactly how to integrate Python into every stage of the FP&A lifecycle to unlock speed, accuracy, and strategic insight.This is a systems-engineering guide for finance. You learn how to architect automated forecasting models, streamline budget cycles, connect Python to Excel and enterprise data sources, eliminate repetitive tasks, and generate CEO-ready reporting packages with a single command. Each chapter walks through practical frameworks, real code examples, and reusable automation templates that immediately reduce manual workload while improving analytical depth.You will build:- Automated forecasting engines that update in real time- Dynamic budgeting workflows that compress month-long processes into hours- Integrated data pipelines linking Excel, SQL, ERP systems, and Python- High-clarity dashboards and executive reporting artifacts- Scenario and sensitivity models engineered for speed and repeatability- Governance and audit controls for scaling automation across finance teamsWhether you are modernizing FP&A in a growing company or reinventing enterprise-level finance operations, this playbook shows the exact path to engineer durable, scalable, and intelligent financial systems. It empowers finance leaders to move beyond static spreadsheets and build a future-ready FP&A ecosystem, one that delivers faster decisions, stronger forecasts, and materially higher business value.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/9/79/827/829/9798278292227_b.jpg", "price_data" : { "retail_price" : "44.99", "online_price" : "44.99", "our_price" : "44.99", "club_price" : "44.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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