What's In It For Me
This course will provide learners with the knowledge which will allow them to reapply their knowledge gained in the course if they choose to go into this career path of Data Intelligence using other platforms such as Qlik Sense, Tableau, Microsoft Power BI or even Python and R.
Course Overview
This course is the foundation course for data analytic, designed for Excel learners who would like to know more about what is data analytics and what are the steps and milestone that is involved. Learners would be using one of the applications that they are familiar with, that is Microsoft Excel to walk through the different milestone in a project cycle to have an idea of what is involved.
Learners will familiarize themselves with terms such as Big Data, Data collection, ETL, Relationship, Data Visualization etc using features such as Data Validation, Power Query and Pivot Table to ingest the data.
Who Should Attend
This course is intended for anyone who wants to take the data analysis technologies in Excel beyond formulas and add more advanced capabilities such as dashboards, hierarchies, and relationships.
Course Duration
2 Days / 14 Hours
Course Outline
Ensuring the Data Quality
- Writing of formulas in Data Validation
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- Countif
- Text Functions
Exploratory Data Analysis
- Understand your data
- Data Type Used
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- Discrete and
- Continuous
Working with Dynamic Table
- Create Data Tables
- Understand how it can be used
Data Preparation
- Perform ETL using Microsoft Power Query
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- Extract
- Transform
- Load
Data Visualization
- Creating Dashboard using Pivot Table
- Understand the limitation of Pivot Table and Charts
Hierarchies
- Hierarchies
- Time Data
The Excel Data Model
- Using an Excel Data Model
- External Data
Explore an Excel Data Model
- Add Multiple Tables
- Create Relationships
- Add External Data
Certification Obtained and Conferred by
Awarded NTUC LearningHub Certificate of Completion
Categories
More Information
- (Local Institution) NTUC LearningHub
Takashi
December 6, 2019 at 12:23 pmwell thought out course. Learning a lot of data analyzing tools.