This plan includes
- Limitedfree coursesaccess
- Play & PauseCourse Videos
- VideoRecorded Lectures
- Learn onMobile/PC/Tablet
- Quizzes andReal Projects
- Lifetime CourseCertificate
- Email & ChatSupport
What you'll learn?
- Why data is the new gold, Data literacy -- What it is, Perspectives, roles, activities, insights, how to use it to solve problems, etc.
- Data Fundamentals, Types, Characteristics, Categories, data based critical thinking, etc.
- Data lifecycle, Operations, Transformations and many other critical concepts with live examples.
- Data Terminology and Concepts
- IT Terminology and Concepts
Course Overview
We are already in the digital revolution, a one-time transformation of every possible aspect of how companies, governments and how even we personally operate.
Pre-requisites
- No prior knowledge required. You will learn everything required
Target Audience
- All Business and Non IT working professional
Curriculum 70 Lectures 06:49:31
Section 1 : Data Literacy and why it is crucial for all working Professionals
- Lecture 2 :
- Why data is the new gold
- Lecture 3 :
- Why low code
- Lecture 4 :
- Data Literacy foundation
- Lecture 5 :
- Activities in Data Literacy lifecycle
- Lecture 6 :
- Different Data Literacy Levels
- Lecture 7 :
- Data Literacy in Technical and Business Domains
- Lecture 8 :
- Role of Data Literacy at different Stages
- Lecture 9 :
- Levels or Types of Analytics
- Lecture 10 :
- What is your Role in Building Analytics?
- Lecture 11 :
- Problem Solving Steps using Data
- Lecture 12 :
- Three main Non Technical Skills for Success
- Lecture 13 :
- 1.13 Thinking Datatically
Section 2 : Data fundamentals, Characteristics, Types, Categories of Data
- Lecture 1 :
- What is Data
- Lecture 2 :
- Data from a Non Technical perspective
- Lecture 3 :
- Data Technical Types
- Lecture 4 :
- Data Categorization
- Lecture 5 :
- Data Characteristics - Format, Velocity, Volume, Methods of Extraction
- Lecture 6 :
- Data Characteristics - Residency, Access, Source Systems, Temperature
- Lecture 7 :
- What are Dimension and Measures ?
Section 3 : Data Sources, Owners, Reporting Requirements, Extraction and Preparation
- Lecture 1 :
- Data Sources
- Lecture 2 :
- Data and Application Owners
- Lecture 3 :
- Data Mapping
- Lecture 4 :
- Reporting Project Requirement Phases
- Lecture 5 :
- Reporting Scenarios
- Lecture 6 :
- Types of Reporting Requirements
- Lecture 7 :
- Sample data - Lets see the real deal
- Lecture 8 :
- Data Extraction methods and Process
- Lecture 9 :
- Data Preparation layer
- Lecture 10 :
- End to End Data movement from Source to a Report
Section 4 : Data Operations and Processes in an Enterprise Reporting Life Cycle with Tableau
- Lecture 1 :
- The life cycle of Data in an Enterprise
- Lecture 2 :
- Analyze Data set and Import to Tableau Public
- Lecture 3 :
- Slicing the Data(reducing rows) with Live examples
- Lecture 4 :
- Dicing the Data(reducing Columns) with Live examples
- Lecture 5 :
- Splitting a Column with Live examples
- Lecture 6 :
- Methods of combining data with Live examples
- Lecture 7 :
- Joins with Live examples
- Lecture 8 :
- Union with Live examples
- Lecture 9 :
- Cleaning Data duplicates, Nulls and more Theory
- Lecture 10 :
- Enrich Data
- Lecture 11 :
- Implement Business calculations with Live examples
- Lecture 12 :
- Aggregation with Live examples
- Lecture 13 :
- Ranking by state, product
- Lecture 14 :
- Hierarchies With level examples
- Lecture 15 :
- What is cube?
Section 5 : Data Terms and Concepts
- Lecture 1 :
- 5.1 The life cycle of Data in an Enterprise
- Lecture 2 :
- 5.2 Data Wrangling
- Lecture 3 :
- 5.3 Data Massaging
- Lecture 4 :
- 5.4 Data Curator
- Lecture 5 :
- 5.5 Data Ethics and Security
- Lecture 6 :
- 5.6 Data Governance and Management
- Lecture 7 :
- 5.7 Data Masking and Anonymization
- Lecture 8 :
- 5.7 Live examples
- Lecture 9 :
- 5.8 What is a Data Warehouse
- Lecture 10 :
- 5.9 What is a Data Mart
- Lecture 11 :
- 5.10 What is a Data Lake
- Lecture 12 :
- 5.11 Hot, Warm and Cold Data
Section 6 : IT/Technology Terms and Concepts
- Lecture 1 :
- 6.1 What is inside a Computer and Server
- Lecture 2 :
- 6.2 How are Enterprise Servers Different
- Lecture 3 :
- 6.3 What are Application, Web and Data Servers
- Lecture 4 :
- 6.4 What is a Hybrid environment (On premise and Cloud)
- Lecture 5 :
- 6.5 What are Development, Test and Production Environments
- Lecture 6 :
- 6.6 What is Hardware, Software and OS virtualization
- Lecture 7 :
- 6.7 What is a Use Case
- Lecture 8 :
- 6.8 What is Normalization
- Lecture 9 :
- 6.9 What is Denormalization
- Lecture 10 :
- 6.10 What are Primary and Foreign Keys
- Lecture 11 :
- 6.11 What is ETL
- Lecture 12 :
- 6.12 What is IoT Data
- Lecture 13 :
- 6.13 Wrap up data and IT
Our learners work at
Frequently Asked Questions
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