This course will expose you to the data analytics practices executed in the business world. We will explore such key areas as the analytical process, how data is created, stored, accessed, and how the organization works with data and creates the environment in which analytics can flourish.
Introduction to Data Analytics for Business
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Introduction to Data Analytics for Business
This course is part of Advanced Business Analytics Specialization
Instructor: David Torgerson
181,297 already enrolled
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Gain insight into a topic and learn the fundamentals.
4.7
(3,133 reviews)
Beginner level
No prior experience required
Flexible schedule
Approx. 11 hours
Learn at your own pace
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What you'll learn
Describe the information lifecycle from events in the real world to business actions
Recognize the types of events and characteristics that are often used in business analytics
Explain how the data is captured by source systems and stored using both traditional and emergent technologies
Gain familiarity with relational databases and learn how to use a simple but powerful language called SQL to extract analytical data sets of interest
Skills you'll gain
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Assessments
4 assignments
Taught in English
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This course is part of the Advanced Business Analytics 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
Welcome to week 1! In this module we’ll learn how to think about analytical problems and examine the process by which data enables analysis & decision making. We’ll introduce a framework called the Information-Action Value chain which describes the path from events in the world to business action, and we’ll look at some of the source systems that are used to capture data. At the end of this course you will be able to: Explain the information lifecycle from events in the real world to business actions, and how to think about analytical problems in that context , Recognize the types of events and characteristics that are often used in business analytics, and explain how the data is captured by source systems and stored using both traditional and emergent technologies, Gain a high-level familiarity with relational databases and learn how to use a simple but powerful language called SQL to extract analytical data sets of interest, Appreciate the spectrum of roles involved in the data lifecycle, and gain exposure to the various ways that organizations structure analytical functions, Summarize some of the key ideas around data quality, data governance, and data privacy
What's included
9 videos3 readings1 assignment2 discussion prompts
In this module we’ll learn about the technologies that enable analytical work. We’ll examine data storage and databases, including the relational database. We’ll talk about Big Data and Cloud technologies and ideas like federation, virtualization, and in-memory computing. We’ll also walk through a landscape of some of the more common tool classes and learn how these tools support common analytical tasks.
What's included
7 videos3 readings1 assignment2 discussion prompts
In this module we’ll learn how to extract data from a relational database using Structured Query Language, or SQL. We’ll cover all the basic SQL commands and learn how to combine and stack data from different tables. We’ll also learn how to expand the power of our queries using operators and handle additional complexity using subqueries.
What's included
7 videos3 readings1 assignment1 discussion prompt
In this module we focus on the people and organizations that work with data and actually execute analytics. We’ll discuss who does what and see how organizational structures can influence efficiency and effectiveness. We’ll also look at the supporting rules & processes that help an analytical organization run smoothly, like Data Governance, Data Privacy, and Data Quality.
What's included
6 videos2 readings1 assignment1 peer review2 discussion prompts
Instructor
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