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Data Analysis And Visualization Fundamentals Micro-Credential


ICEIx

IDR 1,419,379.20

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Program Overview:

Data has become a critical asset to nearly every organization. The powerful insights that data analysis and visualization provide is transforming the way organizations operate and how decisions are made. This presents a growing demand for Data Analysts, and the U.S. Bureau of Labor Statistics projects a growth rate of 20% in the data analytics industry until 2028.

The 3-Course Data Analysis and Visualization Fundamentals program enables you to take the first steps towards understanding the essentials of data analysis, and provides the technical skills, knowledge, tools, and hands-on practice experience to begin your career path in data analytics and becoming an industry expert. NO prior programming knowledge or any data analytics knowledge is required.

Target Audience:

  1. Fresh graduates seeking careers in data analytics or business intelligence
  2. Working professionals aiming to upskill or transition into data-related roles
  3. Entrepreneurs and business owners who want to leverage data for decision-making
  4. Educators and researchers who need data-driven insights for academic or institutional projects
  5. IT and non-IT professionals who want to collaborate effectively in data-driven environments

What you'll learn

  1. Define Data Analytics and the key steps in the Data Analytics process.
  2. Describe the key components of a modern data ecosystem.
  3. Discover the various career opportunities available to Data Analysts.
  4. Describe the steps you need to take to extract raw data from disparate sources, transform raw data into analytics-ready data, and load data into data repositories for use in analytics and reporting.
  5. Describe the process, tools, and techniques required for data wrangling, data cleaning, data mining, and data visualization.
  6. Perform data wrangling, data cleansing, and data analysis tasks using spreadsheets like Microsoft Excel.
  7. Analyze data using filter, sort, and pivot features within spreadsheets like Microsoft Excel.
  8. Design data visualizations using charts, graphs, and plots with tools like Microsoft Excel.
  9. Design and create dashboards in a cloud platform using Cognos Analytics.

Benefits of The Program:

  1. Gain practical, industry-relevant skills through hands-on projects and exercises
  2. Build a competitive advantage in the job market with an in-demand data analytics skill set
  3. Prepare for future-ready careers by mastering tools and methods used by data professionals

Potential Career Pathways:

  • Data Analyst — Transform raw data into actionable business insights
  • Business Intelligence Analyst — Develop dashboards and reports for decision-makers
  • Data Visualization Specialist — Present complex data through clear and impactful visuals
  • Operations Analyst — Optimize business processes using data-driven strategies
  • Marketing or Customer Insights Analyst — Leverage analytics to understand consumer behavior and market trends
  • Junior Data Scientist (Entry-Level) — Contribute to predictive modeling and advanced analytics projects 

Courses in this program

Course NameCourse InstitutionDuration 
Data Analytics Basics for EveryoneIBM15 HoursView Course
Analyzing Data with ExcelIBM15 HoursView Course
Data Visualization and Building Dashboards with Excel and CognosIBM12 HoursView Course

 

Important!

After completing your payment, you will receive an email notification within 24 hours with instructions to begin your course. If you do not receive the notification within this timeframe, please contact the Course Instructor at [email protected].

Duration : 6 Month (starts when the transaction is successful)

  1. Course Number

    MCDATA2
  2. Enrollment Start

  3. Enrollment End

    Dec 30, 2025
  4. Class Start

  5. Class End

    Dec 31, 2025
  6. Estimated Effort

    42 Hours
  7. Language

    English
  8. Course Type

    Self Paced
  9. Quota

    None
  10. Price

    IDR 1,419,379.20
  11. Level

    Beginner
  12. Micro-Credential Data Analysis
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