The Nature of Data and Relational Database Design

The Nature of Data and Relational Database Design

This course is part of Database Design and Operational Business Intelligence Specialization

Instructor: Tim Carrington

Access provided by ExxonMobil

6,253 already enrolled

4 modules

Gain insight into a topic and learn the fundamentals.

102 reviews

Beginner level

Recommended experience

7 hours to complete

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

102 reviews

Beginner level

Recommended experience

7 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Create an ERD that shows progression from conceptual to logical to physical design
Conduct a basic descriptive statistical analysis and articulate the findings
Write SQL scripts to create a database and associated tables

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

4 assignments

Taught in English

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This course is part of the Database Design and Operational Business Intelligence Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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There are 4 modules in this course

This course provides a comprehensive overview of data, various data types, design of databases for storage of data, and creation and manipulation of data in databases using SQL. By the end of this course, students will be able to describe what business intelligence is and how it’s different from business analytics and data science, conduct a basic descriptive statistical analysis and articulate the findings, and differentiate between types of statistics. They will also be able to define normalization and ETL, create an ERD that shows progression from conceptual to logical to physical design, define DDL, DML, DCL, and TCL, and write SQL scripts to create a database and associated tables.

Welcome to Module 1: Overview of Business Intelligence! In our first module, we will define business intelligence and differentiate it from business analytics and data science. We will also overview decision support systems and practice working with them through our activity. Finally, we will differentiate between OTLP and OLAP as well as identify the goals of business intelligence through a short quiz.

What's included

7 readings1 assignment1 discussion prompt

7 readings Total 32 minutes

Business Intelligence, Business Analytics, and Data Science 5 minutes
Decision Support Systems (DSS) 3 minutes
BI and Analytics Drivers 3 minutes
A Simple Taxonomy for Analytics 5 minutes
OLTP versus OLAP 3 minutes
Data Warehousing for BI 3 minutes
Supplemental Resources 10 minutes

1 assignment Total 30 minutes

Module 1 Knowledge Check 30 minutes

1 discussion prompt Total 30 minutes

Activity 30 minutes

Welcome to Module 2: Nature of Data & Descriptive Statistics. In this module, we will dive into the types of data, the process of data preparation and descriptive and inferential statistics. We will differentiate between descriptive and inferential statistics as well as structured and unstructured data with a short quiz. Finally, we will use Microsoft Excel Data Analysis Toolpak to conduct a basic descriptive statistical analysis and share our findings.

What's included

1 video4 readings1 assignment1 discussion prompt

Welcome to Module 3: Relational Database Design (ERD and Normalization). In this module, we will define relational databases and overview the process of designing databases. We will differentiate between conceptual, logical and physical design with a short quiz. In addition, we will create an ERD that shows progression from conceptual to logical to physical design through our activity.

What's included

4 readings1 assignment1 discussion prompt

Welcome Module 4: Structured Query Language (SQL) Overview. In our final module, we will overview SQL as well as define Data Definition Language (DDL) and Data Manipulation Language (DML). Through a short quiz, we will define DDL, DML, DCL, and TCL, as well as differentiate between varying MySQL keywords and data types. In our final activity, we will write SQL scripts to create a database and some associated tables. We will then extract and articulate useful information from the data that we can share with fellow students.