Data Fundamentals

Learn the concepts of Data, how to work with it, and utmostly gleaning the right insights from it for actionable decisions

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Course curriculum

1. Introduction to the Course
2. Course Brochure
3. How to use this Platform
4. Software & Hardware requirements
5. Using our Virtual Training Platforms
6. Your Expectations
7. Ask the Trainer Discussion Forum
1. Introduction
1. Introduction
2. The Kinds of Data Systems
1. Data Storage
2. Types of data storage
3. On-Premises Data Storage
4. Introduction to Cloud Storage
5. Components of On-Premises Data Storage
6. Types of On-Premises Data Storage
7. The Direct Attached Storages (DAS)
8. Network Attached Storage (NAS)
9. The Storage Area Network(SAN)
10. Cloud Storage
11. Cloud Data Systems
12. Examples of Data Storages
1. Introduction
2. Types of Data Structure
3. Relational and Non-Relational Data
4. Data Warehouse
5. Data Lake
6. Data Mart
7. ETL and ELT
8. How to structure your data
9. 7 Golden Rules of Data
10. Data Cleaning
11. Process of Data Cleaning
1. Data Entry
2. Manual Data Entry
3. Automated Data Entry
4. Semi-Manual Data Entry
1. Data Processing
2. Batch Processing
3. Stream Processing
1. Introduction to Data Validation
2. Types of Data Validation
3. Essence of data validation
4. Impact of not validating data
5. What does it mean to validate data
6. Setting up a Data Validation
7. Setting up a List Validation
8. Setting up Error Alerts and Error Options in Data Validation
1. Definition of Data Quality
2. Impacts of corrupted Data
3. Data Corruption
1. Overview
2. Questions to Know What's Relevant - 1
3. Questions to Know What's Relevant - 2
4. Questions to Know What's Relevant - 3
5. Selecting relevant data
1. Concept of Data Governance
2. Element of Data Governance
3. Reasons for Data Governance
1. Introduction to Statistics
2. Collecting Data
3. Organizing Data
4. Analysing Data
5. Interpreting Data
6. Summary
1. Introduction
2. Analytics Workflow
3. Techniques
1. Introduction
2. Definition
3. Choosing Appropriate Visuals
4. Edward Tufte's Quote (Graphical Excellence)
5. Tables or Graphs
6. When to Use Tables
7. When to Use Charts
8. Tables or Graphs - Summary
9. Using Pre Attentive Attributes - Introduction
10. Using Pre Attentive Attributes - Kinds
11. Using Pre Attentive Attributes - Summary
12. Mistakes in Data Visualization - Overview
13. Mistakes in Data Visualization - Clutter
14. Mistakes in Data visualization - Axis Manipulation
15. Mistakes in Data Visualization - Aggressive Use of Pie Charts
1. Visualizing Data like a Pro
2. Introduction to IBCS
3. Unit 1 - Semantic Notation - Other Disciplines
4. Unit 2 - Topics for Semantic Notation in Business
5. Unit 3 - Business notation Manual
6. Unit 4 - Templates for Charts and Tables
7. Unit 5 - Benefits of Standards in business notation
8. Unit 6 - Conceptual, Perceptual and semantic Design
9. Unit 7 - SAY and STRUCTURE
10. Unit 8 - EXPRESS and SIMPLIFY
11. Unit 9 - CONDENSE and CHECK
12. Unit 10 - UNIFY and the IBCS Project
1. Introduction
2. Understanding Context
3. Practical Scenario
1. Introduction
2. 6 Questions You Must Answer a Yes to Before Presenting - 1
3. 6 Questions You Must Answer a Yes to Before Presenting - 2
4. Presentation Styles - Pecha Kucha
5. Planning Your Pecha Kucha Presentation
6. How to create a Pecha Kucha Presentation with PowerPoint
7. Sample Pecha Kucha Presentation
1. Introduction
2. Analyze in Excel
1. Instructions
2. Course Evaluation
3. How to Attach your Certificates to your LinkedIn Profile

About this course

Free
110 lessons
4 hours of video content

Data Fundamentals

Course curriculum

Welcome to the Course

Introduction

Data Systems

Data Storage

Data Structure

Data Entry

Data Processing

Data Validation

Data Quality

Data Relevance

Data Governance

Basic Statistics

Data Analytics

Data Visualization

Report Design Rules

Data in Context

Data Presentation Rules

Data and Harnessing AI

Evaluate the Course

About this course