Data Journey

for Professionals

Elevate your talents to data mastery. Participants will gain up-to-date knowledge, tools and capabilities, enabling them to integrate data best practices into their day-to-day work.

The Program

Audience

All

Duration

3 Months

Format

F2F / Remote

Sessions

Live

Size (up to)

20 Learners

Our Vision

Increase the impact of your data professionals, turning them into data experts who will become key role players in organizational decision making.

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

F2F / Remote

Sessions

Live

size (up to)

20 Learners

Our Vision

Increase the impact of your data professionals, turning them into data experts who will become key role players in organizational decision making.

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

Skills

Data Analysis Process

Data Storytelling & Visualization

Data Modeling
& Architecture

Machine Learning Concepts

Tools

Excel /
Google Sheets

Power BI

Tableau

SQL

Python for Analytics

Our Partners and Customers

Our Partners
& Customers

Testimonials

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.

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

Overview

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

Desired Outcomes

  • Identify the analytical needs
  • Execute data analysis processes professionally

Outline

Requirements Collection (1h)

  • Practice how to identify the “need” instead of reacting to the “want”
Data Preparation (5h)
  • 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)
Analyzing Data (9h)
  • 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 data analysis working methods, split into phases. Participants will learn how to collect requirements, prepare and cleanse data, and start to analyze.

Overview

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

Desired Outcomes

  • Identify the analytical needs
  • Execute data analysis processes professionally

Outline

Requirements Collection (1h)
  • Practice how to identify the “need” instead of reacting to the “want”
Data Preparation (5h)
  • 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)
Analyzing Data (9h)
  • Introduction to Critical Thinking
  • Critical Thinking Process
  • Core skills in critical thinking
  • Data Analysis types and methods (descriptive, diagnostic and predictive)

data skills

Data Storytelling & Visualization

prerequisites

Data Analysis skills

Format

Online / Face to Face / Hybrid

Duration

14 Hours

Data Storytelling & Visualization

prerequisites

Data Analysis Skills

Format

Online / Face To Face / Hybrid

Duration

14 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
  • Be able to make your dashboards practical and easy to read by its users

Outline

Data Storytelling
(11h)
  • 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 – knowing your audience, matching the timing and the platform, and more
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
  • Be able to make your dashboards practical and easy to read by its users

Outline

Data Storytelling (11h)

  • 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 – knowing your audience, matching the timing and the platform, and more
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

data skills

Data Modeling & Architecture

prerequisites

Data Analysis skills and experience with SQL

Format

Online / Face to Face / Hybrid
/ Self Paced

Duration

12 Hours

Data Modeling & Architecture

prerequisites

Data Analysis skills and experience with SQL

Format

Online / Face To Face / Hybrid

Duration

12 Hours

Master the core elements of data architecture, including various data flows and architecture types/concepts, as well as how to design scalable data solutions, based on case studies.

Overview

A comprehensive look into data flow and its impact on insights:

  • High-level data structure
  • ETL / ELT Processes
  • Data architecture types
  • Best practices for planning and designing scalable data solutions

Desired Outcomes

  • Familiarity with the technical data ecosystem
  • Identify data issues and limitations sourced from the architecture and data flow
  • Design data models to suit analytical needs
  • Amend existing data models, based on analytical needs

Outline

Data Ecosystem (4h)
  • High Level Data Flow – understanding the complex route the data takes, from its entry point until it reaches the analysis platform
  • ETL / ELT Processes – understand the different processes and how they impact data and its use
  • Data Architecture Types
    • DWH Models
    • Data Lakes
    • Big Data
Data Modeling (8h)
  • Dimensions
  • Facts
  • Start Schema
  • Snowflake
  • Flat Tables
  • Mapping Tables
Master the core elements of data architecture, including various data flows and architecture types/ concepts, as well as how to design scalable data solutions, based on case studies.

Overview

A comprehensive look into data flow and its impact on insights:

  • High-level data structure
  • ETL / ELT Processes
  • Data architecture types
  • Best practices for planning and designing scalable data solutions

Desired Outcomes

  • Familiarity with the technical data ecosystem
  • Identify data issues and limitations sourced from the architecture and data flow
  • Design data models to suit analytical needs
  • Amend existing data models, based on analytical needs

Outline

Data Ecosystem (4h)
  • High Level Data Flow – understanding the complex route the data takes, from its entry point until it reaches the analysis platform
  • ETL / ELT Processes – understand the different processes and how they impact data and its use
  • Data Architecture Types
    • DWH Models
    • Data Lakes
    • Big Data
Data Modeling (8h)
  • Dimensions
  • Facts
  • Start Schema
  • Snowflake
  • Flat Tables
  • Mapping Tables

data skills

Machine Learning Concepts

prerequisites

Data Analysis skills and experience with SQL

Format

Online / Face to Face / Hybrid

Duration

12 Hours

Machine Learning Concepts

prerequisites

Data Analysis skills and experience with SQL

Format

Online / Face To Face / Hybrid

Duration

12 Hours

Under construction.

data tools

Excel / Google Sheets

prerequisites

Previous experience using basic computer applications

Format

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

Duration

30 Hours

Excel /
Google Sheets

prerequisites

Previous experience using basic computer applications

Format

Online / Face To Face / Hybrid / Self Learning

Duration

30 Hours

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 – Excel / Google Sheets.

Desired Outcomes

Apply the main capabilities of Excel / Google Sheets and use them freely.

Outline

Fundamental
(20 h)
  • Overview & Data Types
  • Common Math Operations & Functions
  • Cell Referencing Deep Dive
  • Conditionals
  • Conditional Math Functions
  • Filtering & Sorting Data
  • Removing Duplicates
  • Conditional Formatting
  • Lookups
Advanced
(10 h)
  • Visualizations and dashboards
  • Pivot Tables
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 – Excel / Google Sheets.

Desired Outcomes

Apply the main capabilities of Excel / Google Sheets and use them freely.

Outline

Fundamental (20 h)
  • Overview & Data Types
  • Common Math Operations & Functions
  • Cell Referencing Deep Dive
  • Conditionals
  • Conditional Math Functions
  • Filtering & Sorting Data
  • Removing Duplicates
  • Conditional Formatting
  • Lookups
Advanced (10 h)
  • Visualizations and dashboards
  • Pivot Tables

data tools

Power BI

prerequisites

Previous experience working with basic computer applications

Format

Online / Face to Face / Hybrid / Self Learning

Duration

40 Hours

Power BI

prerequisites

Previous experience working with basic computer applications

Format

Online / Face to Face / Hybrid / Self Learning

Duration

40 Hours

Basic to advanced functionalities and visualizations with Microsoft’s famous data analysis and reporting tool, including Power Query and DAX.

Overview

Using Power BI’s fundamental to advanced 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
(25 h)
  • Report and Visualization builder
    • Building Basic Reports
    • Building Charts
    • Filter & Slicer
    • Drill through
    • Design Options (headers, background etc.)
    • Drill down / Drill up
  • Power Query
    • Manage columns
    • Manage rows
    • Calculated columns in the ETL process
Advanced
(15 h)
  • Data Modeling Concepts
    • Modeling Relationships
    • Calculated Columns & Measures
  • DAX (Data Analysis Expressions)
Basic to advanced functionalities and visualizations with Microsoft’s famous data analysis and reporting tool, including Power Query and DAX.

Overview

Using Power BI’s fundamental to advanced 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 (25 h)
  • Report and Visualization builder
    • Building Basic Reports
    • Building Charts
    • Filter & Slicer
    • Drill through
    • Design Options (headers, background etc.)
    • Drill down / Drill up
  • Power Query
    • Manage columns
    • Manage rows
    • Calculated columns in the ETL process

Advanced (15 h)

  • Data Modeling Concepts
    • Modeling Relationships
    • Calculated Columns & Measures
  • DAX (Data Analysis Expressions)

data tools

Tableau

prerequisites

Previous experience with basic computer applications

Format

Online / Face to Face / Hybrid / Self Learning

Duration

40 Hours

Tableau

prerequisites

Previous experience with basic computer applications

Format

Online / Face To Face / Hybrid / Self Learning

Duration

40 Hours

Basic to advanced functionalities and visualizations with one of the leading data analysis and reporting tools.

Overview

Using Tableau’s capabilities, from fundamental to advanced. 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
(25 h)
  • Data Management – Connecting to Data, Data Preparation
  • Data Organization – Tour of Shelves, Filters & Sorting, Groups & Sets, Hierarchies & Folders
  • View Types & Customization
  • Basic Calculations – Row-Level vs. Aggregate Calculations, Data & Calculation Types etc.
  • Dashboards
Advanced
(15 h)
  • Building and managing data sources
    • Joining tables
    • Live vs. extract connections
    • Editing and filtering connections
    • Unions
  • Workbooks management
  • Permissions and RLS
Basic to advanced functionalities and visualizations with one of the leading data analysis and reporting tools.

Overview

Using Tableau’s capabilities, from fundamental to advanced. 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 (25 h)

  • Data Management – Connecting to Data, Data Preparation
  • Data Organization – Tour of Shelves, Filters & Sorting, Groups & Sets, Hierarchies & Folders
  • View Types & Customization
  • Basic Calculations – Row-Level vs. Aggregate Calculations, Data & Calculation Types etc.
  • Dashboards
Advanced (15 h)
  • Building and managing data sources
    • Joining tables
    • Live vs. extract connections
    • Editing and filtering connections
    • Unions
  • Workbooks management
  • Permissions and RLS

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 (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

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 analyses and data visualization using “pandas.”

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
  • Numpy (Vectoriation)
  • Working with Files, Series, and Dataframes
  • Indexing (searching and retrieving data)
  • Working with missing values
  • Sorting & Filtering
Pandas
Intermediate
(10h)
  • Grouping/Aggregating
  • Pivoting
  • Merging/Concat Data
  • Frames
  • Visualizations
  • SQL & CSV via Pandas
Pandas
Advanced
(10h)
  • Indexing & Slicing Time Series Data
  • Resampling
  • Rolling Statistics
  • Intro to NumPy
  • Course Summary + Certificates
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 analyses and data visualization using “pandas.”

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
  • Numpy (Vectoriation)
  • Working with Files, Series, and Dataframes
  • Indexing (searching and retrieving data)
  • Working with missing values
  • Sorting & Filtering

Pandas Intermediate (10h)

  • Grouping/Aggregating
  • Pivoting
  • Merging/Concat Data
  • Frames
  • Visualizations
  • SQL & CSV via Pandas

Pandas Advanced (10h)

  • Indexing & Slicing Time Series Data
  • Resampling
  • Rolling Statistics
  • Intro to NumPy
  • Course Summary + Certificates

data skills

Data Storytelling & Visualization

prerequisites

Data Analysis skills

Format

Online / Face to Face / Hybrid

Duration

14 Hours

Data Storytelling & Visualization

prerequisites

Data Analysis Skills

Format

Online / Face To Face / Hybrid

Duration

14 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
(11h)
  • 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