Late Payment Prediction in Dynamics 365 Business Central — PickAClass

Late Payment Prediction in Dynamics 365 Business Central

Learn how to configure and use predictive models to forecast unpaid sales invoices and optimize your collection strategies.

⏱ 1 jam 41 min 📚 10 pelajaran 🎧 Versi audio

Tentang kursus ini

Unpaid invoices and delayed payments can severely disrupt your business's cash flow. Understanding how to leverage predictive technology helps you anticipate payment delays before they impact your bottom line. This text-based course guides you through utilizing the Late Payment Prediction capabilities within Dynamics 365 Business Central. You will learn how to set up the system, interpret model outputs, and establish proactive collection workflows. What you'll learn: Understand the fundamental concepts of predictive analytics in modern cloud ERP systems; Configure the Late Payment Prediction extension within your environment; Analyze historical transaction data to ensure high-quality inputs for machine learning; Build and train custom predictive models tailored to your specific customer payment patterns; Interpret prediction results on sales documents to make informed credit decisions. We begin with foundational terminology and setup requirements before walking through practical scenarios and model customization. Through clear written explanations and structured exercises, you will gain the confidence to manage these predictive tools effectively. This course is designed for finance professionals, ERP administrators, and business analysts who are new to predictive features in Dynamics 365 Business Central, with no prior data science experience required. Start reading today to transform your collections process with data-driven insights.

Apa yang anda dapat

  • 📜 Sijil tamat
    Tambah ke profil LinkedIn anda
  • 💬 Tutor AI peribadi
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  • 🎧 Termasuk versi audio
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  • ♾️ Akses seumur hidup
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  • 📱 Telefon atau komputer
    Berfungsi di mana-mana, mana-mana peranti
  • 💸 Pulangan 30 hari
    Tanpa soalan
  • Pendek dan fokus
    1 jam 41 min kandungan praktikal

Ulasan

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