Data Analytics
- Description
- Curriculum
- Reviews
- Grade
Certified Data Analytics Training
With every day that passes, more and more businesses are discovering how important data is to making better decisions and improving their ventures, so the demand for individuals who can properly analyze data has skyrocketed. So, if you are looking to build a career in this thriving field, you are in the right place.
At Clarion College, we train aspiring data analysts on the tools and skills needed to use data to positively improve businesses. Our curriculum is robust and up-to-date, our tutors are knowledgeable and experienced, and we offer both online and physical courses so you can choose which one best suits you.
What you’ll learn
Month 1: Foundations of Data & Spreadsheets
Objective: Build strong foundational data skills, understand the role of spreadsheets in cleaning, analyzing, and visualizing data.
- Week 1: Introduction to Data Analytics
Learning Outcomes: Understand data roles, analytics lifecycle, and common industry tools - Week 2:: Spreadsheet Basics
Learning Outcomes: Work with rows, columns, formats, filters, and data validation - Week 3: Functions & Formulas
Learning Outcomes: Use IF, VLOOKUP, INDEX-MATCH, SUMIFS, TEXT - Week 4: Pivot Tables, Charts, Dashboards
Learning Outcomes: Create pivot tables, slicers, charts, and interactive dashboards
Month 2: Data Management with SQL
Objective: Query, join, and aggregate data using industry-standard SQL for insights and reporting.
- Week 5: SQL Basics
Learning Outcomes: SELECT, WHERE, ORDER BY, LIMIT - Week 6: Aggregations
Learning Outcomes: COUNT, SUM, AVG, MIN/MAX, GROUP BY, HAVING - Week 7: Joins & Subqueries
Learning Outcomes: INNER, LEFT, RIGHT, FULL joins, subqueries - Week 8: Window Functions & CTEs
Learning Outcomes: RANK, ROW_NUMBER, LEAD/LAG, CTEs
Month 3: Data Visualization with POWER BI
Objective: Create automated and interactive dashboards with clean, well-modeled datasets.
- Week 9: Getting Started
Learning Outcomes: Load & clean data using Power Query Editor - Week 10: Data Modeling
Learning Outcomes: Create relationships, use star schema, set cardinality - Week 11: Visualization
Learning Outcomes: Use KPI cards, bar/line charts, slicers, drill-through - Week 12: Publishing & Automation
Learning Outcomes: Publish dashboards, set refresh schedule, manage roles
Month 4: Business Problem Solving & Communication
Objective: Connect data analysis to business outcomes. Improve storytelling, clarity, and usability of dashboards and reports.
- Week 13: Framing Business Problems
Learning Outcomes: Define analytics questions from vague requests. - Week 14: Statistical Analysis
Learning Outcomes: Understand the role of descriptive statistics in data analysis. - Week 15: Data Storytelling
Learning Outcomes: Tailor reports to decision-makers using visuals and insights - Week 16: Data Privacy, Security & Ethics
Learning Outcomes: Know basic guidelines from GDPR, HIPAA, NDPR, etc.
Month 5: Capstone Project
Objective: Apply all tools and concepts to create an end-to-end, real-world dashboard project that includes automation and stakeholder-ready outputs.
- Week: 17
Activity: Proposal & Dataset Selection
Learning Outcomes: Choose dataset and define project scope - Week: 18
Activity: Data Cleaning & Exploration
Learning Outcomes: Perform cleaning in spreadsheets and/or SQL - Week: 19
Activity: Dashboard Development
Learning Outcomes: Build Power BI report with meaningful visualizations and publish - Week: 20
Activity: Presentation & Feedback
Learning Outcomes: Communicate results, receive critique, finalize
Outcome
Participants will complete the program with:
-
A published Power BI dashboard
-
A GitHub or Notion portfolio
-
Reusable SQL scripts
-
CV + LinkedIn tailored for global analytics jobs
-
Hands-on experience in solving real-world problems with data
-
1
Module 1 Intro: Foundations of Data & SpreadsheetsI'm excited to guide you through the start of your journey into the dynamic world of Data Analytics. As a data professional, I know that success in this field isn't about memorizing complex code; it's about mastering the core process and the fundamental tools that let you turn raw numbers into strategic business decisions.
This module, Foundations of Data & Spreadsheets, is your launchpad. We'll start with the essential theory including the roles, the lifecycle, and the mindset, before diving into the most universally used data tool in the business world: Microsoft Excel.
-
2
Welcome to Week 1: The Data Analyst Mindset
This week, we're laying the foundation for your entire career in data. We won't be opening a single spreadsheet yet; instead, we're focusing on the conceptual blueprint that guides every successful analysis. It's like drawing up architectural plans before laying bricks. The blueprint ensures that the structure will be sound once you start building.
As a seasoned data professional, I can tell you that the most effective analysts are the ones who understand the why and the process just as well as the how. This week's goal is to establish that critical understanding.
-
3
Week 1.1: Defining the Raw Material: What is Data?
-
4
Week 1.2: The Analytical Blueprint: The Data Lifecycle
-
5
Week 1.3: The Professional Landscape: Roles, Responsibilities, and Tools
-
6
Week 1.4: The Analyst Mindset: Learning How to Learn
-
7
Week 1 Assessment: Introduction to Data Analytics Fundamentals -
8
Week 1 Assignment: Introduction to Data Analytics Fundamentals -
9
Week 1 Module Completion and Next Steps
-
10
Welcome to Week 2: Spreadsheet Basics
Last week, we built the foundational knowledge: the "why" and "what" of data analytics. This week, we transition directly to the "how" by mastering the most ubiquitous tool in the business world: Microsoft Excel.
I can authoritatively tell you that Excel proficiency is non-negotiable. It's the first test of data readiness, and a strong analyst must be able to move data quickly and efficiently within a spreadsheet environment. This week is entirely focused on data preparation, the step in the Data Lifecycle that takes up the majority of an analyst's time.
-
11
Week 2.1: Getting Started with Excel: The Foundation
-
12
Week 2.2: Understanding and Formatting Data Types
-
13
Week 2.3: Data Quality: Filtering, Cleaning, and Validation
-
14
Week 2 Assessment: Spreadsheet Basics
-
15
Week 2 Assignment: Introduction to Data Analytics Fundamentals
-
16
Week 2 Module Completion and Next Steps
-
17
Welcome to Week 3: Calculations, Logic, and Lookups
Congratulations on successfully cleaning your first dataset! You now know how to structure and prepare raw data. This week, we transition from preparation to analysis by mastering the powerful tools that perform the heavy lifting: Spreadsheet Formulas and Functions.
As a data professional, I can tell you that functions are the engines of business intelligence. They allow you to rapidly summarize, conditionally calculate, and combine massive datasets, turning static data into dynamic insights.
This week’s focus is efficiency and conditional intelligence. We are moving beyond simple arithmetic to conditional calculations and data integration. You will learn to write formulas that make decisions, summarize data based on criteria, and connect different pieces of information across sheets.
-
18
Week 3.1: The Formulas Tab: Your Calculation Command Center
-
19
Week 3.2: Mathematics & Conditional Logic: Making Data Decisions
-
20
Week 3.3: Data Transformation and Formatting of Time and Text
-
21
Week 3.4: Data Transformation and Formatting of Time and Text
-
22
Week 3 Assessment: Calculations, Logic, and Lookups
-
23
Week 3 Assignment: Comprehensive Sales Analysis & Reporting
-
24
Week 3 Module Completion and Next Steps
-
25
Welcome to Week 4: Pivot Tables & Visual Storytelling
Congratulations! You have completed the full data pipeline: you can clean messy data and calculate complex metrics. This final week of the module focuses on the most critical step in the Data Analytics Lifecycle: Communication.
As a data professional, your brilliant analysis is useless unless you can share its findings clearly. This week, we will master the tools that transform rows of numbers into intuitive insights: Pivot Tables and Visualization.
Our focus is efficiency in summarization and clarity in presentation. You'll learn to use Pivot Tables, the fastest way to group and aggregate data in Excel and combine them with professional chart design principles to build your first analytical dashboard. This is the skill that closes the loop between data and business decision-making.
-
26
Week 4.1: Pivot Tables: Summarization on Demand
-
27
Week 4.2: Data Visualization with Charts
-
28
Week 4.3: Building Interactive Dashboards
-
29
Week 4.4: Excel is a powerful tool: you’ve only scratched the surface
-
30
Week 4 Assessment: Pivot Tables & Visual Storytelling Fundamentals
-
31
Week 4 Final Portfolio Project: Sales Performance Dashboard
-
32
Week 4 Module Completion and Next Steps
-
33
Module 2 Intro: Data Management with SQL
-
34
Week 5: SQL BASICS
-
35
Week 5.1. SQL BASICS: How Data Storage Works
-
36
Week 5.2. SETUP & FIRST STEPS
-
37
Week 5.3. SQL DATA TYPES
-
38
Week 5.4. SELECT Statements
-
39
Week 5.5. FILTERING DATA WITH WHERE
-
40
Assessment: SQL Basics
-
41
Week 5 Project: Chinook Database Exploration
-
42
Week 5 Conclusion: SQL Basics
-
43
Welcome to Week 6: SQL AGGREGATIONS
-
44
Week 6.1. COUNT, SUM, AVG Functions
-
45
Week 6.2. MIN and MAX Aggregate Functions
-
46
Week 6.3. GROUP BY and HAVING CLAUSE
-
47
Week 6.4. Aliasing
-
48
Assessment: Aggregations
-
49
Week 6 Project: SQL Aggregations
-
50
Aggregations: Completion and Next Steps
-
51
Welcome to Week 7: JOINS & Subqueries
-
52
Week 7.1. Inner JOIN
-
53
Week 7.2. RIGHT JOIN
-
54
Week 7.3 LEFT JOIN
-
55
SQL Join Practice Project: Chinook Database
-
56
Week 7.5. FULL OUTER JOIN
-
57
Week 7.6. Subqueries (Nested Queries)
-
58
Week 7: JOINS & Subqueries AssessmentThis quiz is designed to test your understanding of different SQL JOIN types and the application of Subqueries. Scenario Context: Assume you are working with an e-commerce database with two key tables: Customers: (CustomerID, Name, City, FirstOrderDate) Orders: (OrderID, CustomerID, OrderDate, TotalAmount)
-
59
Week 7 Project: Advanced Querying on Northwind
-
60
Week 7 Completion
-
61
Welcome to Week 8: SQL Data Cleaning
-
62
Week 8.1. Common Issues Found in Raw Data
-
63
Week 8.2. Handling NULL Values
-
64
Week 8.3. Handling Strings with TRIM, UPPER and LOWER
-
65
Week 8.4 Working with Dates in MySQL: Analysis and Formatting
-
66
Week 8. Data Cleaning Assessment
-
67
Module 2 Capstone: AdventureWorks Sales Performance Analysis
-
68
Congratulations on Completing Week 8!
-
69
Module 3 Intro: Visualizations with Power BI
-
70
Welcome to Week 9: Getting Started with Power BI
-
71
Week 9.1 Introduction
-
72
Week 9.2. Getting Started
-
73
Week 9.3 Data Cleaning with Power Query
-
74
Week 9.4 Pivot vs. Unpivot (and why)
-
75
Week 9.5 Date & Time Prep
-
76
Week 9: Power BI Assessment
-
77
Week 9. Project
-
78
Week 9 Completion
-
79
Week 10: Data Modelling and Data Analysis Expressions
-
80
Week 10.1. Build a Star Schema
-
81
Week 10.2. Detect Ambiguous Relationships
-
82
Week 10.3. DAX Essentials
-
83
Week 10.4. DAX Deep Dive
-
84
Week 10.5. Building Time Intelligence Measures in DAX
-
85
Week 10: Power BI AssessmentInstructions For each question, read the scenario carefully and select the best option.
-
86
Week 10. Project
-
87
Welcome to Week 11: Visualization
-
88
Week 11.1 From Data to Executive Insight
-
89
Week 11.2 Filtering and Interactivity
-
90
Week 11.3 Power BI Report Design Mastery: Drill-Through and Tooltips
-
91
Week 11.4 Advanced Report Interaction
-
92
Week 11.5 Advanced Visualization Techniques
-
93
Week 11: Visualization Assessment
-
94
Week 11. Completion
-
95
Welcome to Week 12: Publishing and Automation
-
96
Week 12.1 Power BI Service
-
97
Week 12.2 Content Sharing and Access Management
-
98
Week 12.3 Implementing Row-Level Security (RLS) and Configuring Scheduled Data Refresh
-
99
Publishing and Automation AssessmentInstructions Please read each scenario carefully and select the single best option that resolves the described situation or fulfills the stated requirement.
-
100
Week 12. Project
12. Project
Overview
Publish the completed HR Attrition Dashboard to Power BI Service, configure refresh automation, manage security roles, and share the final dashboard with stakeholders.
Instructions
Follow the steps to complete the project:
Step 1: Create a Power BI Service Account
-
Navigate to https://app.powerbi.com
-
Sign in using your Microsoft or organizational account.
-
If this is your first login:
-
Accept the Power BI license agreement.
-
Confirm your region settings.
-
Verify that your account has permission to publish reports.
Step 2: Prepare the HR Attrition PBIX File
Before publishing, download the HR Attrition pbix file and confirm the following inside Power BI Desktop:
-
Ensure the HR Attrition dashboard contains:
-
Executive Summary page
-
Attrition Analysis page
-
Department/Role analysis
-
Validate model integrity:
-
Relationships are correct
-
Measures return correct values
-
Unused columns removed
-
Rename visuals and fields for clarity.
Step 3: Publish the Report
-
In Power BI Desktop click Publish.
-
Sign in if prompted.
-
Select your target Workspace.
-
Click Publish.
After publishing:
-
Navigate to Power BI Service
-
Locate the report and dataset inside the workspace.
Step 4: Configure Dataset Settings
-
In Power BI Service open the dataset settings.
-
Configure credentials for the data source.
-
Verify that the dataset refresh can run successfully.
Step 5: Configure Scheduled Refresh
-
Go to Dataset Settings.
-
Enable Scheduled Refresh.
-
Configure refresh frequency (daily recommended).
-
Set preferred refresh time.
Step 6: Configure Row Level Security
-
Open the dataset in Power BI Desktop.
-
Navigate to Model View → Manage Roles.
-
Create roles such as:
-
HR Manager
-
Department Manager
-
Apply filters to restrict data visibility.
Example: DepartmentManager can only view their department data.
-
Publish updated report.
-
Assign users to roles in Power BI Service.
Step 7: Create a Dashboard in Power BI Service
-
Open the published report.
-
Pin key visuals to a New Dashboard.
-
Name the dashboard: HR Attrition Executive Dashboard
Recommended tiles:
-
Attrition Rate
-
Employees by Department
-
Attrition Trend
-
Top Reasons for Attrition
Step 8: Configure Alerts and Subscriptions
Alerts:
-
Open a KPI tile.
-
Click Manage Alerts.
-
Set thresholds (example: attrition > 10%).
Subscriptions:
-
Click Subscribe on the report or dashboard.
-
Schedule email delivery.
Step 9: Manage Workspace Roles
Assign appropriate roles:
Admin → Full control Member → Edit and publish Contributor → Publish content Viewer → Read-only access
For this project:
HR Executives → Viewer HR Analysts → Member
Step 10: Share the Dashboard
-
Open the dashboard.
-
Click Share.
-
Generate the shareable access link.
Final Submission
You must submit the following compiled in a google/word document:
-
Power BI Service dashboard link
-
Screenshot of scheduled refresh settings
-
Screenshot of workspace roles
-
-
101
Week 12: Completion
-
102
Module 4 Intro: Business Problem Solving & Communication
Welcome to the Business Problem Solving & Communication course! This module is meant to give you all the important skills that are required to navigate complex business challenges and articulate solutions effectively as a data analyst.
-
103
Week 13: Framing Business Problems
-
104
Week 13.1: Define the Core Business Problem (Symptoms vs Root Causes)
-
105
Week 13.2: Translate Stakeholder Requests
-
106
Week 13.3 Build a Problem Brief
-
107
Week 13.4. Building Your Hypothesis List
-
108
Business Problem Solving & Comm. Assessment
-
109
Week 13 Completion
-
110
Week 14. Statistical Analysis
-
111
Week 14.1. Fundamentals of Descriptive and Inferential Statistics
-
112
Week 14.2 Hypothesis Testing (t-tests, ANOVA, Chi-square)
-
113
Week 14.3. Interpreting and Communicating Statistical Results to Business Leaders
-
114
Statistical Analysis Assessment
-
115
Week 14. Completion
-
116
Week 15: Data Storytelling: Turning Insights into Action
-
117
Week 15.1 Tailor Insights to the Audience
-
118
Week 15.2 The Data Analyst as a Business Consultant
-
119
Week 15.3 Design Visuals that Support the Message
-
120
Week 15.4 Produce a persuasive narrative that connects problem to impact
-
121
Data Storytelling Assessment
-
122
Week 15. Completion
-
123
Week 16: Data Privacy, Security & Ethics
-
124
Week 16.1 Basic Principles of GDPR & HIPAA
-
125
Week 16.2 Identify Ethical Risks
-
126
Week 16.3: Build Trust with Dashboards
-
127
Week 16.4: Deliver Compliant Reports
-
128
Data Privacy, Security & Ethics Assessment
-
129
Week 16. Project
-
130
Week 16. Completion
Core Tools: Google Sheets / Excel, SQL (PostgreSQL/MySQL), Power BI
This course is for everyone
