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AI-Driven Financial Dashboards with Power BI

Build Predictive Dashboards from Real-Time Financial Data

  • Duration

    15 Hours

  • Schedule

    15 – 17 July 2025
    09.00 – 15.00 WIB

  • Habitare

    Jl. H. R. Rasuna Said No.Kav.20, Karet Kuningan, Kecamatan Setiabudi, Jakarta Selatan 12940

  • Investment

    Rp. 5.550.000

WORKSHOP STARTS IN

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Overview

This 15-hour hands-on workshop is designed for finance professionals and analysts seeking to build real-time, AI-enhanced dashboards. Using live data from Sectors, participants will master Power BI from data connection to AI-driven insights. They will gain foundational understanding of artificial intelligence, access real financial data via API, clean and model datasets, build impactful visualizations, and integrate both built-in AI features and predictive models using Python and Azure ML. No prior coding or API experience is required.

Course Syllabus

  • Clarifying What AI Is vs. Common Misconceptions
  • Evolution of AI: From Rule-Based to Generative AI
  • AI vs. Machine Learning vs. Deep Learning vs. LLMs
  • Real-World AI Use Cases in Financial Services
  • How AI Fits in Power BI: An Overview
  • The Role of BI in Finance
  • Power BI Platform Overview
  • Visual Language and Financial Data Cues
  • Getting Started with Power BI Desktop
  • APIs for Beginners: What and Why?
  • Overview of Sectors.app as a Financial Data Source
  • Connecting Power BI to Sectors API via Power Query
  • Handling Authentication and Parameters
  • Refreshing API Data Securely
  • Power Query Editor for Finance
  • Cleaning and Restructuring Financial Tables
  • Handling Periodic Data and Units
  • Advanced Transformations (Merging, Pivoting)
  • Revenue and Profit Analysis (Bar/Column Charts)
  • Time-Based Trends (Line and Area Charts)
  • Expense and Segment Breakdown (Pie/Donut/Treemap)
  • Geo Maps for Regional Financial Data
  • Table and Matrix for Financial Reports
  • Customizing Combo Charts for KPI Comparison
  • Bookmarks, Tooltips, Drill-through for Financial Context
  • Introduction to DAX Calculations
  • Common Financial Metrics (YoY, MoM, Margins)
  • Calculated Columns vs. Measures
  • Using Quick Measure for Business Logic
  • Key Influencers: What Drives Financial KPIs?
  • Decomposition Tree: Root-Cause Analysis
  • Natural Language Queries with Q&A
  • Smart Narratives and Anomaly Detection
  • Interpreting Smart Narratives for Stakeholders
  • Anomaly Alerts in Revenue & Expense Fluctuations
  • Ethical Considerations in AI Explanations
  • Merging Narrative AI with Visualization Context
  • Why Python in Power BI?
  • Installing Python Environment
  • Configuring Python in Power BI Desktop
  • Python Package Management
  • Preprocessing Financial Data using Python
  • Building Simple Predictive Models (e.g., Forecasting)
  • Running Python Scripts in Power Query
  • Embedding Python Outputs in Dashboards
  • What is Azure ML and How it Works
  • Connecting Azure ML to Power BI
  • Running Prediction Endpoints in Power Query
  • Embedding Results in Dashboards
  • Layout Principles for Finance Use Cases
  • KPI Cards and Interactions
  • Actionable Insight vs. Data Overload
  • Applying Financial Color Standards
  • Report Deployment via Power BI Service
  • Optimizing DAX and Queries for Speed
  • Data Governance: Row-Level Security
  • Usage Monitoring and Access Control

Course Receivables

  • Lecturer’s Notes

    Including Course Books (PDF), HTML files, course transcripts (if any).

  • Highly-accelerated Learning

    Learn under the assistance of mentorship of our lead instructor and a band of qualified teaching assistants throughout each course.

  • Certification of Completion

    Show current employer hat you’ve completed the course with a signed certificate of completion.

  • Quality Learning Environment

    We pay meticulous attention to the logistical details of our workshops: quality audio and visual setups, comfortable sitting arrangements, and small group size.

  • Refreshments & Coffee Break

    In our commitment to delivering a premium experience, we collaborate with leading catering services in Jakarta. Our aim is to ensure that all participants are served delectable lunches and revitalizing coffee breaks.

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ABOUT THIS SERIES

Courses in this series cater to a diverse audience: from casual learners and working professionals to those venturing into data science and machine learning without a programming background.

We recognize that many students may not have prior expertise in statistics, mathematics, or algebra. Therefore, our courses are designed with a gentle learning curve, placing a strong emphasis on hands-on experience and individualized instruction. Our dedicated team of instructors and teaching assistants ensure personalized guidance every step of the way.

Teaching Methodology

Students work through tons of real-life examples using sample datasets donated by our mentors and corporate partners. We believe in a learn-by-building approach, and we employ instructors who are uncompromisingly passionate about your growth and education.

YOUR INSTRUCTOR

Muhammad Dzaky Jayalaksono
Business Intelligence Instructor at Algoritma Data Science School

Dzaky has a strong understanding and proficiency in platforms for business analytics, enabling valuable insights for data-driven decision-making. As a detail-oriented professional, He possesses the technical thinking skills to identify innovative solutions for business problems and is deeply committed to the company’s advancement. Orchestrating the end-to-end business intelligence process from defining the business problem to conducting thorough analysis, visualizing insights, and deploying impactful dashboards. Bring a comprehensive skill set to drive the entire lifecycle of business intelligence. He is motivated to continuously learn and grow, keep collaborating, and provide exceptional abilities to drive success.

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Get In Touch

PT. Algoritma Data Indonesia.
RDTX Square, 9th Floor. Setiabudi, DKI Jakarta 12930.
Office: 0816-692-471
Email: community@algorit.ma

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