Analyzing Big Data with SQL

Analyzing Big Data with SQL

Course
en
English
17 h
This content is rated 0 out of 5
Source
  • From www.coursera.org
Conditions
  • Self-paced
  • Free Access
More info
  • 6 Sequences
  • Introductive Level

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Course details

Syllabus

WEEK 1 - Orientation to SQL on Big Data
9 videos (Total 47 min), 5 readings, 2 quizzes

WEEK 2 - SQL SELECT Essentials
16 videos (Total 83 min), 4 readings, 2 quizzes

WEEK 3 - Filtering Data
14 videos (Total 85 min), 6 readings, 2 quizzes

WEEK 4 - Grouping and Aggregating Data
15 videos (Total 82 min), 6 readings, 2 quizzes

WEEK 5 - Sorting and Limiting Data
14 videos (Total 70 min), 1 reading, 2 quizzes

WEEK 6 - Combining Data
12 videos (Total 61 min), 5 readings, 3 quizzes

Prerequisite

To use the hands-on environment for this course, you need to download and install a virtual machine and the software on which to run it. Before continuing, be sure that you have access to a computer that meets the following hardware and software requirements:
• Windows, macOS, or Linux operating system (iPads and Android tablets will not work)
• 64-bit operating system (32-bit operating systems will not work)
• 8 GB RAM or more
• 25GB free disk space or more
• Intel VT-x or AMD-V virtualization support enabled (on Mac computers with Intel processors, this is always enabled;
on Windows and Linux computers, you might need to enable it in the BIOS)
• For Windows XP computers only: You must have an unzip utility such as 7-Zip or WinZip installed (Windows XP’s built-in unzip utility will not work)

Instructors

Ian Cook
Senior Curriculum Developer
Cloudera

Editor

Cloudera

Platform

Coursera is a digital company offering massive open online course founded by computer teachers Andrew Ng and Daphne Koller Stanford University, located in Mountain View, California. 

Coursera works with top universities and organizations to make some of their courses available online, and offers courses in many subjects, including: physics, engineering, humanities, medicine, biology, social sciences, mathematics, business, computer science, digital marketing, data science, and other subjects.

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