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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.
All working professionals irrespective of industry or role, will need Data, IT, Analytical and AI skills to survive and succeed during this and beyond.
Clearly the ones who understand and can use these skills well, will lead the pack with greater opportunities, higher pay packages, benefits and work flexibility.
These skills will be covered in a series of courses. In this course you will learn tool agnostic Data and IT skills on popular enterprise grade tools including Tableau and SAP Lumira
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
Benefits
Enhance your profile and capabilities by acquiring tool agnostic Data and IT skills. You can apply the same concepts and methods across various tool sets, certifications and vendors.
Move from your existing role to a technology enabled role, which is all roles.
Build the foundation to acquire skills for the jobs of the future.
Start your journey to land IT jobs with premium salaries and benefits, Location independence, Flexible work rules
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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