Getting Started with Data Management
What you’ll learn
Get started working with data
Understand big data fundamentals
Explore tabular data with Python
Learn the fundamentals of SQL
Use the ETL workflow for data integration
Requirements
If you know how to install software to your computer, you’re good to go
Description
Data Management is one of the most important competencies your company has. With Digital Transformation at the top of the strategic agenda for many large organizations, Data Governance and Data Management are vital to building a strong foundation for integration, analysis, execution, and overall business value. Business and data professionals are currently facing The Fourth Industrial Revolution’s convergence of megatrends around Customer 360, Artificial Intelligence, Big Data, programmatic marketing, and globalization. To survive these unrelenting business pressures, it’s more critical, and strategic, than ever to put your data to work!In this course, you will learn about the various disciplines of data management. First, you will discover what Data Governance is and why you might want to implement a governance program for your organization, after which you will go through some very basic exploratory Data Analysis using the Python programming language.Next up, you’ll cover basic Database Design, Data Quality essentials, and the fundamentals of the Structured Query Language. Then, you will get hands-on with some rudimentary Data Integration ETL, as well as Big Data with Hadoop.Finally, you will explore the various disciplines in the Data Management space.By the end of the course, you will have a firm understanding of enterprise data management and what the various disciplines do.
Overview
Section 1: The Value of Data Management
Lecture 1 The Value of Data Management
Lecture 2 The Lifecycle of Data
Section 2: Understanding Data Governance
Lecture 3 Why Do We Need Data Governance
Lecture 4 Understanding Data Stewardship
Lecture 5 Implementing Master Data Management
Lecture 6 Developing Data Definitions
Lecture 7 The Importance of Standardization
Section 3: Exploring Tabular Data
Lecture 8 Understanding Tabular Data
Lecture 9 Installing Jupyter Notebook
Lecture 10 Exploring Tabular Data
Lecture 11 Most Common Names in California
Lecture 12 How Frequently Does Your Name Occur?
Lecture 13 Statistical Data Types
Lecture 14 Visualizing Data
Section 4: Relational Database Basics
Lecture 15 Database Management Systems
Lecture 16 The Database Development Lifecycle
Section 5: Improving Data Quality
Lecture 17 Removing Duplicate Data
Lecture 18 Removing Inconsistent Data
Lecture 19 Breaking-down Data into Smaller Components
Lecture 20 Requiring Complete Information
Lecture 21 Designating the Primary Key
Section 6: Database Design
Lecture 22 One to Many Relationship
Lecture 23 Many to Many Relationship
Lecture 24 Integrity Constraints
Lecture 25 Indexing for Performance
Section 7: SQL
Lecture 26 Downloading Oracle XE
Lecture 27 Installing Oracle XE
Lecture 28 Opening the Oracle XE Database
Lecture 29 Connecting to Your Brand New Database
Lecture 30 Oracle Live SQL
Lecture 31 The SELECT Statement
Lecture 32 Restricting and Sorting Data
Lecture 33 Using Single-row Functions
Lecture 34 Aggregating Data with Group Functions
Lecture 35 Displaying Data from Multiple Tables
Lecture 36 Answering Multi-step Questions Using Subqueries
Section 8: Up and Running with Ubuntu Linux
Lecture 37 Downloading Ubuntu and Workstation Pro
Lecture 38 Up and Running with Ubuntu
Lecture 39 Transferring Files Using SFTP
Section 9: Data Integration
Lecture 40 Setting-up Your Postgres Database
Lecture 41 Setting-up Your Postgres Data Sources
Lecture 42 Installing Python and PySpark
Lecture 43 Installing Java and JDBC for Postgres
Lecture 44 Extracting Data
Lecture 45 Transforming Data
Lecture 46 Loading Data
Section 10: Understanding Big Data
Lecture 47 Big Data Overview
Lecture 48 Types of Big Data
Lecture 49 Limitations of Relational Systems
Lecture 50 Introducing Hadoop
Lecture 51 Setting-up Hadoop
Lecture 52 Connecting to Your Hadoop VM
Lecture 53 Issuing SQL Queries through Hive
Section 11: Data Management Careers
Lecture 54 Data Management Roles
Lecture 55 Data Steward
Lecture 56 Data Analyst
Lecture 57 Data Engineer
Lecture 58 Data Architect
Lecture 59 DBA
Lecture 60 Application Developer
Lecture 61 Data Scientist
Anyone seeking a career in data management,Aspiring DBAs, Developers, Data Analysts, Data Scientists and Data Engineers
Course Information:
Udemy | English | 2h 15m | 952.17 MB
Created by: Philip Agaba
You Can See More Courses in the Developer >> Greetings from CourseDown.com