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From A to

Data Analyst

Generate your own data talent by elevating potential candidates with no knowledge in data into data professionals with up-to-date core data skills and tools.
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The Program

Audience

All

Duration

3 Months

Format

On-Site / On-line

Size (up to)

20 Participants

Our Vision

Solve the talent shortage and improve organizational processes by training the next generation of data and business analysts in state-of-the-art methods and tools.

Desired
Outcomes

Master Data Analysis processes from A to Z

Use up-to-date tools and methods to uncover business insights

Apply data best practices to increase data accessibility for all stakeholders

The Program

Audience

All

Duration

3 Months

Format

On-Site / On-line

size (up to)

20 Participants

Our Vision

Solve the talent shortage and improve organizational processes by training the next generation of data and business analysts in state-of-the-art methods and tools.

Desired
Outcomes

Master Data Analysis processes from A to Z

Use up-to-date tools and methods to uncover business insights
Apply data best practices to increase data accessibility for all stakeholders
1

Data Analysis Process

SEE DETAILS 

2

Google Sheets

SEE DETAILS 

3

SQL

SEE DETAILS 

4

Data Storytelling & Visualization

SEE DETAILS 

5

Choose from:

A

Power BI

SEE DETAILS 

B

Tableau

SEE DETAILS 

6

Python for Analytics

SEE DETAILS 

7

Final Project

SEE DETAILS 

Data Analysis Process

See details

Google Sheets

See details

SQL

See details

Data Storytelling & Visualization

See details

Power BI

See details

Tableau

See details

Python for Analytics

See details

Final Project

See details
get in touch

Our Partners and Customers

Our Partners
& Customers

Testimonials

“Measuring the data mindset before and after the Data Literacy Training with Elevation has shown a clear increase in the data driven mindset. The blended sessions were tailored to our needs and met our goals.”
Ebony MorczinekCEO Europe Marley Spoon
Ebony Morczinek
“Measuring the data mindset before and after the Data Literacy Training with Elevation has shown a clear increase in the data driven mindset. The blended sessions were tailored to our needs and met our goals.”
Ebony MorczinekCEO Europe Marley Spoon
Ebony Morczinek

FAQ

Can you customize training for my company?
Each organization and business is different, so pre-packaged training programs don't work for everyone.
Therefore, we offer two types of customizations:
1. industry-specific customization.
2. organization-specific customization. Make sure you ask about it.
How do you deliver your training?
Every organization has its own unique learning environment, and we support all of them:
In-person (at any location designated by you)
vs. Online (via Zoom or Microsoft Teams)
vs. Hybrid Instructor-led vs. self-paced using our learning system vs. hybrid
How many participants can attend the same course at once?
Our professional experience suggests that a cohort of participants should be no more than 20 to ensure an effective learning process. 
When there are more than 20 participants, we offer a teacher assistant (TA).
Do you offer interactive training?
Definitely!
Our approach to learning and evolving is based on experience and hands-on practice.
Who teaches your courses?
Elevation-certified instructors have proven experience and are professionals with proven expertise.
What will the participants leave with?
During each course, we provide takeaways with a summary. Furthermore, Elevation learning system content is available for 6 months after course completion.

Contact info

Copyright 2024 © All rights Reserved.
Design by Elevation

data skills

Data Analysis Process

prerequisites

No prior knowledge is required

Format

Online / Face to Face / Hybrid

Duration

20 Hours

Data Analysis Process

prerequisites

No prior knowledge is required

Format

Online / Face to Face / Hybrid

Duration

20 Hours

A deep dive into the data analysis working methods, split into phases. Participants will learn how to collect requirements, prepare and cleanse data and start to analyze.

Overview

This course aims to provide practical working methods of Data Analysts / Business Analysts. During this course, the participants will review case studies and practice best practices.

Desired Outcomes

  • Identify the analytical needs
  • Execute data analysis processes professionally

Outline

Intro to Data Analyst Role (1.5h)

  • Get familiar with the data analyst role in organizations, required skills and its interfaces

Requirements Collection (1.5h)

  • Practice how to identify the “need” instead of reacting to the “want”

Data Cleansing Process (4h)

  • Identifying the proper source for analytical needs
  • Analyzing the limitations of the available data
  • Identifying data issues in raw data and how to handle them according to best practices
Basic Statistics
(5h)
  • Basic terminology (average, median, percentile, mode, standard deviation, variation)
  • Basic Probability
  • Distribution
  • Additional concepts (Correlation, statistical significance, representative sample, trendlines, average dangers)

Critical Thinking & Data Analysis (8h)

  • Introduction to Critical Thinking
  • Critical Thinking Process
  • Core skills in critical thinking
  • Data Analysis types and methods (descriptive, diagnostic and predictive)
A deep dive into the data analysis working methods, split into phases. Participants will learn how to collect requirements, prepare and cleanse data and start to analyze.

Overview

This course aims to provide practical working methods of Data Analysts / Business Analysts. During this course, the participants will review case studies and practice best practices.

Desired Outcomes

  • Identify the analytical needs
  • Execute data analysis processes professionally

Outline

Intro to Data Analyst Role (1.5h)

  • Get familiar with the data analyst role in organizations, required skills and its interfaces

Requirements Collection (1.5h)

  • Practice how to identify the “need” instead of reacting to the “want”

Data Cleansing Process (4h)

  • Identifying the proper source for analytical needs
  • Analyzing the limitations of the available data
  • Identifying data issues in raw data and how to handle them according to best practices
Basic Statistics (5h)
  • Basic terminology (average, median, percentile, mode, standard deviation, variation)
  • Basic Probability
  • Distribution
  • Additional concepts (Correlation, statistical significance, representative sample, trendlines, average dangers)

Critical Thinking & Data Analysis (8h)

  • Introduction to Critical Thinking
  • Critical Thinking Process
  • Core skills in critical thinking
  • Data Analysis types and methods (descriptive, diagnostic and predictive)
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data tools

Google Sheets (optional)

prerequisites

Previous experience using basic computer applications

Format

Online / Face to Face / Hybrid / Self Learning / Self Paced

Duration

25 Hours

Google Sheets (optional)

prerequisites

Previous experience using basic computer applications

Format

Online / Face to Face / Hybrid / Self Learning

Duration

25 Hours

Participants will learn Google Sheets functionalities and capabilities on two levels:

  • Fundamentals for first-time users
  • Upskilling and advanced techniques

Overview

Using the most fundamental analytical tool – Google Sheets.

Desired Outcomes

Learn the main capabilities of Google Sheets and how to apply them in the real world.

Outline

Fundamental (8h)

  • Introduction to Google Sheets
  • Working with Rows, Columns, Cells, and Sheets
  • Basic Formulas and Functions
  • Formatting Tables & Cells

Advanced
(14h)

  • Analyzing Data in Google Sheets:
    • Sorting
    • Filtering
    • Data Validation
    • Pivot Tables
    • Lookups
  • Data Visualization: Charts & Graphs
  • Advanced Formulas: Conditionals, SUMIF, Nested Functions
  • Using AI in Sheets
Participants will learn Excel / Google Sheets functionalities and capabilities on two levels:
  • Fundamentals for first-time users
  • Upskilling and advanced techniques

Overview

Using the most fundamental analytical tool – Google Sheets.

Desired Outcomes

Learn the main capabilities of Google Sheets and how to apply them in the real world.

Outline

Fundamental (8h)

  • Introduction to Google Sheets
  • Working with Rows, Columns, Cells, and Sheets
  • Basic Formulas and Functions
  • Formatting Tables & Cells

Advanced
(14h)

  • Analyzing Data in Google Sheets:
    • Sorting
    • Filtering
    • Data Validation
    • Pivot Tables
    • Lookups
  • Data Visualization: Charts & Graphs
  • Advanced Formulas: Conditionals, SUMIF, Nested Functions
  • Using AI in Sheets
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data tools

SQL

prerequisites

Previous experience using basic computer applications

Format

Online / Face to Face / Hybrid
/ Self Paced

Duration

30 Hours

SQL

prerequisites

Previous experience using basic computer applications

Format

Online / Face To Face / Hybrid

Duration

30 Hours

Participants will learn Structured Query Language (SQL), broken down from beginner to advanced levels:
  • Basic concepts and queries
  • Advanced analytics and optimizations

Overview

Using SQL, the most commonly used capability in data analysis, to extract and analyze data.

Desired Outcomes

Be able to analyze and extract data using SQL.

Outline

Fundamental
(20 h)
  • Intro to SQL
  • Filters and sorts
  • Scalar Functions
  • Aggregation and Basic Analysis
  • Relationships
    • Join Types
    • Union Types
    • Except / Minus
Advanced
(10 h)
  • Subqueries
  • Views
  • Analytical Functions
Participants will learn Structured Query Language (SQL), broken down from beginner to advanced levels:
  • Basic concepts and queries
  • Advanced analytics and optimizations

Overview

Using SQL, the most commonly used capability in data analysis, to extract and analyze data.

Desired Outcomes

Be able to analyze and extract data using SQL.

Outline

Fundamental (20h)

  • Intro to SQL
  • Filters and sorts
  • Scalar Functions
  • Aggregation and Basic Analysis
  • Relationships
    • Join Types
    • Union Types
    • Except / Minus
Advanced (10h)
  • Subqueries
  • Views
  • Analytical Functions
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Next

data skills

Data Storytelling & Visualization

prerequisites

Data Analysis skills

Format

Online / Face to Face / Hybrid

Duration

12 Hours

Data Storytelling & Visualization

prerequisites

Data Analysis Skills

Format

Online / Face To Face / Hybrid

Duration

12 Hours

Practice crafting a compelling data story, based on narrative and data visualization best practices, enabling the participants to deliver effective messages in various contexts.

Overview

Transform data into a convincing narrative:
  • Less is more
  • Crafting the story and visualizations
  • Delivering the most-effective message

Desired Outcomes

  • Be aware of the power of storytelling
  • Craft a compelling story based on data
  • Build an accurate visualization
  • Build practical dashboards

Outline

Data storytelling (9h)

  • Crafting Your Story – how to identify the narrative based on data analysis as the backbone of the story
  • From Data to Story – Plan your story details to support the narrative
  • Delivering Data Stories – know your audience, match the timing and the platform etc.
Visualization
(3h)
  • Visualization as a Data Storytelling Tool – why there cannot be data storytelling without visualization
  • Data visualization principles – best practices of data visualization
  • Dashboards – do’s and don’ts
Practice crafting a compelling data story, based on narrative and data visualization best practices, enabling the participants to deliver effective messages in various contexts.

Overview

Transform data into a convincing narrative:
  • Less is more
  • Crafting the story and visualizations
  • Delivering the most-effective message

Desired Outcomes

  • Be aware of the power of storytelling
  • Craft a compelling story based on data
  • Build an accurate visualization
  • Build practical dashboards

Outline

Data storytelling (9h)

  • Crafting Your Story – how to identify the narrative based on data analysis as the backbone of the story
  • From Data to Story – Plan your story details to support the narrative
  • Delivering Data Stories – know your audience, match the timing and the platform etc.
Visualization (3h)
  • Visualization as a Data Storytelling Tool – why there cannot be data storytelling without visualization
  • Data visualization principles – best practices of data visualization
  • Dashboards – do’s and don’ts
Previous
Next

data tools

Power BI

prerequisites

Previous experience working with basic computer applications

Format

Online / Face to Face / Hybrid / Self Learning

Duration

25 Hours

Power BI

prerequisites

Previous experience working with basic computer applications

Format

Online / Face to Face / Hybrid / Self Learning

Duration

25 Hours

Fundamental functionalities and visualizations with Microsoft’s famous data analysis and reporting tool, including Power Query.

Overview

Using Power BI’s fundamental capabilities.
Power BI is one of the most used analytical tools and has led the Gartner Magic Quadrant for years.

Desired Outcomes

  • Apply Power BI’s data analysis and visualization capabilities
  • Use Power BI with confidence

Outline

Fundamental (25h)

  • Introduction to Power BI
  • Building Visualizations
    • Building Charts
    • Building non-charts visuals
    • SLicers and Filters
  • Data Preparations & Publish
    • Data Modeling Concepts
    • Fundamentals of Power Query
    • Share and Publish report

Fundamental functionalities and visualizations with Microsoft’s famous data analysis and reporting tool, including Power Query.

Overview

Using Power BI’s fundamental capabilities.
Power BI is one of the most used analytical tools and has led the Gartner Magic Quadrant for years.

Desired Outcomes

  • Apply Power BI’s data analysis and visualization capabilities
  • Use Power BI with confidence

Outline

Fundamental (25h)

  • Introduction to Power BI
  • Building Visualizations
    • Building Charts
    • Building non-charts visuals
    • SLicers and Filters
  • Data Preparations & Publish
    • Data Modeling Concepts
    • Fundamentals of Power Query
    • Share and Publish report
Previous
Next

data tools

Tableau

prerequisites

Previous experience with basic computer applications

Format

Online / Face to Face / Hybrid / Self Learning

Duration

25 Hours

Tableau

prerequisites

Previous experience with basic computer applications

Format

Online / Face To Face / Hybrid / Self Learning

Duration

25 Hours

Fundamental functionalities and visualizations with one of the leading data analysis and reporting tools.

Overview

Using Tableau capabilities for data analysis and visualization. Tableau is one of the most popular analytical tools and has led the Gartner Magic Quadrant for years.

Desired Outcomes

  • Apply Tableau data analysis and visualization capabilities
  • Use Tableau with confidence

Outline

Fundamental (25h)

  • Introduction
  • Data Management
  • Data Organization
    • Tour of Shelves
    • Default Properties
    • Filters
    • Groups & Sets
    • Sorting
    • Hierarchies & Folders
    • Other Organization Options (bins, keep/exclude, aliases)
  • View Types (Bar Chart, Line Chart, Heat Map, Scatter Chart and others)
  • View Customizations (Title & Caption, Labels, Shapes, Format and more)
  • Basic Calculations
    • Types of Calculations
    • Getting Started with Calculations
    • Row-Level vs. Aggregate Calculations
    • Data & Calculation Types
    • Null Values Calculations
    • Parameters
  • Dashboards
    • What are Dashboards?
    • Dashboard Objects
    • Filters in Dashboards
    • Dashboard Action Filters
    • Dashboard Extensions

Fundamental functionalities and visualizations with one of the leading data analysis and reporting tools.

Overview

Using Tableau capabilities for data analysis and visualization. Tableau is one of the most popular analytical tools and has led the Gartner Magic Quadrant for years.

Desired Outcomes

  • Apply Tableau data analysis and visualization capabilities
  • Use Tableau with confidence

Outline

Fundamental (25h)

  • Introduction
  • Data Management 
  • Data Organization
    • Tour of Shelves
    • Default Properties
    • Filters
    • Groups & Sets
    • Sorting
    • Hierarchies & Folders
    • Other Organization Options (bins, keep/exclude, aliases)
  • View Types (Bar Chart, Line Chart, Heat Map, Scatter Chart and others)
  • View Customizations (Title & Caption, Labels, Shapes, Format and more)
  • Basic Calculations
    • Types of Calculations
    • Getting Started with Calculations
    • Row-Level vs. Aggregate Calculations
    • Data & Calculation Types
    • Null Values Calculations
    • Parameters
  • Dashboards
    • What are Dashboards?
    • Dashboard Objects
    • Filters in Dashboards
    • Dashboard Action Filters
    • Dashboard Extensions
Previous
Next

data tools

Python for Analytics

prerequisites

Previous experience with basic computer applications

Format

Online / Face to Face / Hybrid
/ Self Paced

Duration

50 Hours

Python for Analytics

prerequisites

Previous experience with basic computer applications

Format

Online / Face To Face / Hybrid

Duration

50 Hours

An in-depth course in Python’s state-of-the-art data analysis capabilities. Participants will learn basic programming and Python concepts, and move on to Pandas for data analysis and visualization (both beginner and advanced functionality).

Overview

Python and its “pandas” data analysis library are leading tools for data analysis and visualization. Learn to use them, from basic skills to completing complex analyses.

Desired Outcomes

Learn to write basic Python scripts, as well as execute standard and complex analysis and data visualization using “pandas” library.

Outline

Python & Development Fundamental (15h)
Intro to Python, Conditions, Lists, Strings, Loops, Functions, Dictionaries, Lambda Functions. Map, Filter, I/O: User Input and Output, Tuples, Sets.
Pandas
Beginner
(15h)
  • Setup, Jupyter Notebook
  • Files, Dataframes, and Indexing
  • Sorting & Filtering
  • Descriptive Statistics
  • Missing Values
Pandas
Intermediate
(10h)
  • Pivoting
  • Grouping & Aggregating
  • Merging & Concat
  • Data Visualization
Pandas
Advanced
(10h)
  • Using SQL in Pandas
  • Time Series Analysis
  • Intro to NumPy
  • Connecting Flights Mini Project
An in-depth course in Python’s state-of-the-art data analysis capabilities. Participants will learn basic programming and Python concepts, and move on to Pandas for data analysis and visualization (both beginner and advanced functionality).

Overview

Gain the capability to use the Python programming language, the newest tool for data analysis and visualization, from basic skills to executing complex analyses.

Desired Outcomes

Learn to write basic Python scripts, as well as execute standard and complex analysis and data visualization using “pandas” library.

Outline

Python & Development Fundamental (15h)
Intro to Python, Conditions, Lists, Strings, Loops, Functions, Dictionaries, Lambda Functions. Map, Filter, I/O: User Input and Output, Tuples, Sets.

Pandas Beginner (15h)

  • Setup, Jupyter Notebook
  • Files, Dataframes, and Indexing
  • Sorting & Filtering
  • Descriptive Statistics
  • Missing Values

Pandas Intermediate (10h)

  • Pivoting
  • Grouping & Aggregating
  • Merging & Concat
  • Data Visualization

Pandas Advanced (10h)

  • Using SQL in Pandas
  • Time Series Analysis
  • Intro to NumPy
  • Connecting Flights Mini Project
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Next

data skills

Final Project

prerequisites

Completion of a Data Academy course

Format

Self Paced/ Office Hours / Hybrid

Duration

4 Hours

Final Project

prerequisites

Completion of a Data Academy course

Format

Self Paced / Office Hours / Hybrid

Duration

4 Hours

Practice a real life data analysis use case, while applying all learned skills and tools.

Overview

Experience a real live data analysis work by applying all skills and tools learned during the journey.

Desired Outcomes

Answer business questions by applying the skills and tools obtained during the data analyst journey.
*The final project can be completed by individuals or groups of up to five team members.

Outline

Project Intro
  • Introduce the business scenario that the project is based on
Datasets
  • Introduce the dataset
    (based on SQL Server DB or Excel/CSV file)
  • ERD (Entity Relationship Diagram)
  • Meaning of each field in each table
Data Analysis Use Cases
  • Analyze realistic business questions, using the skills, knowledge, and tools obtained during the course

Presentation (Optional)

  • Presentation of the project in a formal forum
Practice a real life data analysis use case, while applying all learned skills and tools.

Overview

Experience a real live data analysis work by applying all skills and tools learned during the journey.

Desired Outcomes

Answer business questions by applying the skills and tools obtained during the data analyst journey.

Outline

Project Intro
Introduce the business scenario that the project is based on.
Datasets
  • Introduce the dataset (based on SQL Server DB or Excel/CSV file)
  • ERD (Entity Relationship Diagram)
  • Meaning of each field in each table
Data Analysis Use Cases
  • Analyze realistic business questions, using the skills, knowledge, and tools obtained during the course

Presentation (Optional)

Presentation of the project in a formal forum.

*The final project can be completed by individuals or groups of up to five team members.
Previous

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