Hybrid Training

Data Analyst Training

This training helps individuals learn how to make more effective and efficient data-based decisions.

Make use of Data Masters’ expertise and gain valuable analytical skills that will facilitate your daily work.

Start:

September 2024

Duration:

16 weeks (91 hours)

Schedule:

Two classes per week
(17:30-20:00) 

Workshops:

Every other Friday
(17:30-20:00)

Price:

Early Bird Price:
36.000 MKD

Regular Price: 
39.000 MKD

Training Description

The training begins with an introduction to data types in MS SQL Server and learning the syntax for creating, updating, and deleting data.

It continues with reading, understanding, analyzing, and preprocessing the same data in Python. 

The training is completed with a descriptive visualization of the performed analyses in Microsoft Power BI.

At this training, you will gain experience through the workshops, where you will apply the data analysis techniques you learned in the classes to scenarios from real-life projects. You will work with data sets adjusted for making business decisions or performing financial analysis, enabling you to acquire skills you can apply directly in your field.

Modules

Introduction to SQL

  • Introduction to databases
  • Introduction to MS SQL Server 
  • Creating and importing spreadsheets
  • Sending queries to the database
  • Transforming and interpreting results
  • Merging tables by key
  • Selecting columns
  • Filtering rows
  • Aggregate functions
  • Sorting and grouping
  • ETL (Extract, Transform, Load)

Data Processing
with Python

  • Introduction to Python programming
  • Data types 
  • Uploading, collecting, and analyzing data with Python
  • Data structures
  • Manipulating data structures
  • Functions
  • Libraries for analysis and visualization

Data Visualization with Microsoft Power BI

  • Using the Power BI tool for data visualization
  • Understanding Power BI Desktop and its components
  • Connecting Power BI to different data sources
  • Data models
  • Working with different data model views
  • Combining graphs in a dashboard
  • Creating calculated columns and metrics
  • Building relationships between different tables
  • Creating a report with different interactive visualizations 
  • Executing Python scripts directly in Power BI

This training is suitable for you if you work in/have knowledge of:

  • Banking
  • Corporate Finance
  • Financial Consulting
  • Accounting
  • Insurance
  • Investment Funds
  • Audit or Supervision
  • Actuarial Science
  • Budgeting
  • Creating and Delegating Reports
  • Sales and Revenue Projection
  • Growth and Cost Evaluation
  • Project Management
  • A Business in the Marketing, Import/Export, Customs, Transport, Construction, Healthcare, and Manufacturing Fields
Academy Students
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Student Domains
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Successful Career Switches and Upgrades
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Student Testimonials

Our Goal is to Teach You How To:

Martina Naumovska, co-founder of the Academy
and partner at Data Masters

„From our experience so far, everyone who decided to improve their career did not regret the decision. Investing in yourself and your future is the best gift you can give to yourself. We as Data Maters are ready to selflessly transfer our knowledge and guide our students to achieve their goals.“

Examples of Case Studies Included in the Training

Creating a Dashboard for Credit Portfolio Analysis

Interest rate movement by product (car loans, housing loans, consumer loans) over different time periods

Loans that have been liquidated early (according to the current balance and years of repayment)

Participation of products in the credit portfolio in different periods

Credit risk exposure analysis

Credit portfolio performance in a given period of time

Quality and value of collaterals

Diversification of the portfolio according to customer segmentation (job position, experience, residence)

Relations between collateral value and other variables

Collateral risk assessment

Calculating net interest income for different time intervals

Creating a Dashboard for Wholesale Business Analysis

Participation of products in the total portfolio across different time periods

Correlation between sales trends and other variables

Forecasting client purchasing power

Constant product inventory monitoring

Determining discounts for different procurement categories

Maximizing the profitability of a wholesale company

Gross profit monitoring by month, product, and region

Monitoring inventory and its life cycle in real-time

Discount distribution by categories and their effect on gross profit

Product KPIs (Key Performance Indicators)

Take the First Step
Toward Your New Future