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Available Training Rooms

  • PRIVATE BATCH
  • PUBLIC PROGRAM
  • ON DEMAND
  • BLENDED

Course Details

  • Course Overview
  • Skills Gained
  • Who Can Benefit
  • Prerequisite
  • Syllabus

In this 'Data Insight' course, participants will know how to query and process petabytes of data in seconds. Gain knowledge on data analysis that scales automatically as your data grows. This 2 days course will completely train students on how to derive insights through data analysis and visualization using the Google Cloud Platform. The course also features interactive scenarios and hands-on labs where students explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. The course will also cover data loading, schema modeling, querying, performance, optimizing, query pricing, and data visualization.

  • Successfully derive insights from data using the analysis and visualization tools on Google Cloud Platform
  • Interactively query datasets using Google BigQuery
  • Effectively Load, clean, and transform data at scale
  • Visualize data using Google Data Studio and other third-party platforms
  • Distinguish between exploratory and explanatory analytics and when to use these two approaches
  • Explore new datasets and uncover hidden insights quickly and efficiently
  • Optimizing data models and queries for price and performance

This course is intended for the following:

 

  • Data Analysts, Business Intelligence professionals, Business Analysts
  • Cloud Data Engineers who will be partnering with Data Analysts to frame scalable data solutions on Google Cloud Platform

To get the most out of this training, participants should have:

  • Basic knowledge with ANSI SQL

• Introduction to Data on the Google Cloud Platform

• Before and Now: Scalable Data Analysis in the Cloud
o Highlight Analytics Challenges Faced by Data Analysts
o Compare Big Data On-Premises vs on the Cloud
o Learn from Real-World Use Cases of Companies Transformed through Analytics on the Cloud
o Navigate Google Cloud Platform Project Basics
o Lab: Getting started with Google Cloud Platform

• Big Data Tools Overview

• Sharpen the Tools in your Data Analyst toolkit
o Walkthrough Data Analyst Tasks, Challenges, and Introduce Google Cloud Platform Data Tools
o Demo: Analyze 10 Billion Records with Google BigQuery
o Explore 9 Fundamental Google BigQuery Features
o Compare GCP Tools for Analysts, Data Scientists, and Data Engineers
o Lab: Exploring Datasets with Google BigQuery

• Exploring your Data with SQL

• Get Familiar with Google BigQuery and Learn SQL Best Practices
o Compare Common Data Exploration Techniques
o Learn How to Code High Quality Standard SQL
o Explore Google BigQuery Public Datasets
o Visualization Preview: Google Data Studio
o Lab: Troubleshoot Common SQL Errors

• Google BigQuery Pricing

• Calculate Google BigQuery Storage and Query Costs
o Walkthrough of a BigQuery Job
o Calculate BigQuery Pricing: Storage, Querying, and Streaming Costs
o Optimize Queries for Cost
o Lab: Calculate Google BigQuery Pricing



• Cleaning and Transforming your Data

• Wrangle your Raw Data into a Cleaner and Richer Dataset
o Examine the 5 Principles of Dataset Integrity
o Characterize Dataset Shape and Skew
o Clean and Transform Data using SQL
o Clean and Transform Data using a new UI: Introducing Cloud Dataprep
o Lab: Explore and Shape Data with Cloud Dataprep

• Storing and Exporting Data

• Create new Tables and Exporting Results
o Compare Permanent vs Temporary Tables
o Save and Export Query Results
o Performance Preview: Query Cache
o Lab: Creating new Permanent Tables

• Ingesting New Datasets into Google BigQuery

• Bring your Data into the Cloud
o Query from External Data Sources
o Avoid Data Ingesting Pitfalls
o Ingest New Data into Permanent Tables
o Discuss Streaming Inserts
o Lab: Ingesting and Querying New Datasets

• Data Visualization

• Effectively Explore and Explain your Data through Visualization
o Overview of Data Visualization Principles
o Exploratory vs Explanatory Analysis Approaches
o Demo: Google Data Studio UI
o Connect Google Data Studio to Google BigQuery
o Lab: Exploring a Dataset in Google Data Studio

• Joining and Merging Datasets

• Combine and Enrich your Datasets with more Data
o Merge Historical Data Tables with UNION
o Introduce Table Wildcards for Easy Merges
o Review Data Schemas: Linking Data Across Multiple Tables
o Walkthrough JOIN Examples and Pitfalls
o Lab: Join and Union Data from Multiple Tables

• Advanced Functions and Clauses

• Dive Deeper into Advanced Query Writing with Google BigQuery
o Review SQL Case Statements
o Introduce Analytical Window Functions
o Safeguard Data with One-Way Field Encryption
o Discuss Effective Sub-query and CTE design
o Compare SQL and Javascript UDFs
o Lab: Deriving Insights with Advanced SQL Functions

• Schema Design and Nested Data Structures

• Model your Datasets for Scale in Google BigQuery
o Compare Google BigQuery vs Traditional RDBMS Data Architecture
o Normalization vs Denormalization: Performance Tradeoffs
o Schema Review: The Good, The Bad, and The Ugly
o Arrays and Nested Data in Google BigQuery
o Lab: Querying Nested and Repeated Data

• More Visualization with Google Data Studio

• Create Pixel-Perfect Dashboards
o Create Case Statements and Calculated Fields
o Avoid Performance Pitfalls with Cache considerations
o Share Dashboards and Discuss Data Access considerations

• Optimizing for Performance

• Troubleshoot and Solve Query Performance Problems
o Avoid Google BigQuery Performance Pitfalls
o Prevent Hotspots in your Data
o Diagnose Performance Issues with the Query Explanation map
o Lab: Optimizing and Troubleshooting Query Performance

• Advanced Insights

• Think, Analyze, and Share Insights like a Data Scientist
o Introducing Cloud Datalab
o Cloud Datalab Notebooks and Cells
o Benefits of Cloud Datalab

• Data Access

• Keep Data Security top-of-mind in the Cloud
o Compare IAM and BigQuery Dataset Roles
o Avoid Access Pitfalls
o Review Members, Roles, Organizations, Account Administration, and Service Accounts

Audience

  • Business Analyst
  • Business Intelligence
  • Cloud Administrators
  • Data Professionals

Public Program Schedule

Course Name Duration Brochure Location Schedule Enroll
There is no upcoming Public Batch Schedule, you can ask for Private Batch or for On-Demand Learning

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FAQ

  • What is a Google Cloud certification?
  • Why should I get a Google Cloud certification?
  • How long is a Google Cloud certification valid?
  • What is the recertification policy?
  • Why do I need to recertify?
  • How do I pay?
  • What are your cancellation & refund policy?

Google Cloud's certification program gives Google Cloud users, customers and partners a way to demonstrate their technical skills in a particular job role or technology. Individuals are assessed using a variety of rigorously developed industry standard methods to determine whether they meet Google Cloud's proficiency standards.

Google Cloud certifications give you benchmarks for your professional development. They help you gauge your skill set against your peers and demonstrate your value to hiring managers.

Unless explicitly stated in the detailed exam descriptions, all Google Cloud certifications are valid for two years from the date certified. Candidates must recertify in order to maintain their certification status.

Unless explicitly stated in the detailed exam descriptions, all Google cloud certifications are valid for two years from the date certified. Candidates must recertify in order to maintain their certification status and certificate number.

Google technology changes frequently. We require recertification to ensure you're maintaining your skills.

We accept all modes of payment. If you are being nominated by your organization, your organization need to release PO before the course start date. If you are an individual you can pay through credit / debit cards, online transfer (RTGS/NEFT) to our account 7 days prior to the course start date.

  • In a highly unlikely event of cancellation of batch from our end, we shall refund 100% that is paid by you. If client choose to cancel for any reasons, below is the terms.
  • If you cancel or reschedule your registration 5 or more calendar days before the scheduled start date of the class – No cancellation charges
  • If you cancel or reschedule your registration less than 5 calendar days before the scheduled start date of the class – cancellation charges 100% of the course fee
  • If you do not show up for the event, or cancel on the day of the event - cancellation charges 100% of the course fee

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