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Google BigQuery & PostgreSQL : Big Query for Data Analysis
Quick Facts
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Medium of instructions
English
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Mode of learning
Self study
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Mode of Delivery
Video and Text Based
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Course overview
BigQuery, a petabyte-scale, a moderate enterprise data warehouse for analytics from Google, enables users to process our big datasets dynamically. PostgreSQL is one of the most powerful, open-source relational database systems that has earned its reputation because of its dependability, feature strength, and efficiency Google BigQuery & PostgreSQL: Big Query for Data Analysis online certification is created by Start-Tech Academy, an educational platform serving in more than countries, which is offered by Udemy.
Google BigQuery & PostgreSQL: Big Query for Data Analysis online course is intended for candidates who want to have a thorough understanding of all the theories and techniques in SQL and Google BigQuery that are beneficial for doing data analysis in organizations. Candidates will receive more than 11.5 hours of prerecorded lectures with the Google BigQuery & PostgreSQL: Big Query for Data Analysis online classes, in addition to 7 articles and 5 downloadable resources that cover topics like data analysis, data visualization, SQL commands, subqueries, string functions, mathematical functions, and more.
The highlights
- Certificate of completion
- Self-paced course
- 11.5 hours of pre-recorded video content
- 7 articles
- 5 downloadable resources
Program offerings
- Online course
- Learning resources
- 30-day money-back guarantee
- Unlimited access
- Accessible on mobile devices and tv
Course and certificate fees
Fees information
₹ 3,099
certificate availability
Yes
certificate providing authority
Udemy
Who it is for
What you will learn
Knowledge of data visualization
Sql knowledge
Mathematical skill
Knowledge of google analytics
After completing the Google BigQuery & PostgreSQL: Big Query for Data Analysis certification course, candidates will acquire a comprehensive understanding of the functionalities of PostgreSQL and Google BigQuergy on Google cloud for data analysis and data visualization operations. Candidates will learn about various SQL commands as well as the capabilities of SQL tools like JOINS, GROUP BY, subqueries, views, indexes, pattern matching, string functions, and mathematical functions. Additionally, candidates will learn how to use Google Data Studio.
The syllabus
Introduction
Installation and getting started
- Course Resources
- This is a milestone!
- PostgreSQL and PGAdmin Installation
- If pgAdmin is not opening...
- Setting up BigQuery on Google Cloud Platform
- BigQuery Interface
Fundamental SQL statements
- CREATE
- CREATE in BigQuery
- Exercise 1: Create DB and Table
- INSERT
- INSERT in BigQuery
- Import data from File
- Importing data from File using BigQuery Web User Interface
- File Upload in Google Big Query through Google cloud sdk
- Importing data from Google Drive
- Exercise 2: Inserting and Importing
- SELECT
- SELECT in BigQuery
- SELECT DISTINCT
- SELECT DISTINCT in BigQuery
- WHERE
- WHERE in BigQuery
- Logical Operators - AND, OR, NOT
- Logical Operators in BigQuery
- Exercise 3: SELECT & WHERE
- UPDATE
- UPDATE in BigQuery
- DELETE
- DELETE in BigQuery
- ALTER
- ALTER in BigQuery
- Exercise 4: Updating Table
Restore and Back-up
- Restore and Back-up
- Debugging Restoration
- Creating DB using CSV files
- Data Set creation in BigQuery
- Exercise 5: Restore and Back-up
Selection commands: Filtering
- IN
- IN in BigQuery
- BETWEEN
- BETWEEN in BigQuery
- LIKE
- LIKE in BigQuery
- Exercise 6: In, Like & Between
Selection commands: Ordering
- ORDER BY
- ORDER BY in BigQuery
- LIMIT
- LIMIT in BigQuery
- Exercise 7: Sorting
Alias
- AS
- AS in BigQuery
Aggregate Commands
- COUNT
- COUNT in BigQuery
- SUM
- SUM in BigQuery
- AVERAGE
- AVERAGE in BigQuery
- MIN MAX
- MIN MAX in BigQuery
- Exercise 8: Aggregate functions
Group By Commands
- GROUP BY
- GROUP BY in BigQuery
- HAVING
- HAVING in BigQuery
- Exercise 9: Group By
Conditional Statement
- CASE WHEN
- CASE WHEN in BigQuery
Joins
- Introduction to Joins
- Concepts of Joining and Combining Data
- Preparing the data
- Creating Datasets for Joins in BigQuery
- Inner Join
- INNER JOIN in BigQuery
- Left Join
- LEFT JOIN in BigQuery
- Right Join
- RIGHT JOIN in BigQuery
- Full Outer Join
- FULL OUTER JOIN in BigQuery
- Cross Join
- CROSS JOIN in BigQuery
- Intersect and Intersect ALL
- Except
- EXCEPT in BigQuery
- Union
- UNION in BigQuery
- Exercise 10: Joins
- Quiz
Subqueries
- Subqueries
- Subqueries in BigQuery
- Exercise 11: Subqueries
Views and Indexes
- Views
- Views in BigQuery
- Index
- Index in BigQuery
- Exercise 12: Views
String Functions
- LENGTH
- LENGTH in BigQuery
- UPPER LOWER
- Changing Case in BigQuery
- REPLACE
- REPLACE in BigQuery
- TRIM, LTRIM, RTRIM
- TRIM, LTRIM, RTRIM in BigQuery
- CONCATENATION
- CONCATENATION in BigQuery
- SUBSTRING
- SUBSTRING
- LIST AGGREGATION
- LIST AGGREGATION
- Exercise 13: String Functions
Mathematical Functions
- CEIL & FLOOR
- CEIL & FLOOR in BigQuery
- RANDOM
- RANDOM in BigQuery
- SETSEED
- SETSEED in BigQuery
- ROUND
- POWER
- POWER in BigQuery
- Exercise 14: Mathematical Functions
Date-Time Functions
- CURRENT DATE & TIME
- CURRENT DATE & TIME in BigQuery
- AGE
- AGE in BigQuery
- EXTRACT
- EXTRACT in BigQuery
- Exercise 15: Date-time functions
Pattern (String) Matching
- PATTERN MATCHING BASICS
- ADVANCE PATTERN MATCHING (REGULAR EXPRESSIONS)
- PATTERN MATCHING in BigQuery
- Exercise 16: Pattern Matching
Google Data Studio for visualizing BigQuery Data
Google Data Studio for visualizing BigQuery Data
Bonus Section
- The final milestone!
- Congratulations & About your certificate
Articles
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