Description

Duration

3 Days

18 CPD hours

This course is intended for

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

Overview

This course teaches students the following skills:
Derive insights from data using the analysis and visualization tools on Google Cloud Platform
Interactively query datasets using Google BigQuery
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 each approach
Explore new datasets and uncover hidden insights quickly and effectively
Optimizing data models and queries for price and performance

Want to know how to query and process petabytes of data in seconds? Curious about data analysis that scales automatically as your data grows? Welcome to the Data Insights course! This four-course accelerated online specialization teaches course participants how to derive insights through data analysis and visualization using the Google Cloud Platform. The courses feature interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. The courses also cover data loading, querying, schema modeling, optimizing performance, query pricing, and data visualization. This specialization is intended for the following participants: Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform To get the most out of this specialization, we recommend participants have some proficiency with ANSI SQL.

Introduction to Data on the Google Cloud Platform

Highlight Analytics Challenges Faced by Data Analysts

Compare Big Data On-Premises vs on the Cloud

Learn from Real-World Use Cases of Companies Transformed through Analytics on the Cloud

Navigate Google Cloud Platform Project Basics

Lab: Getting started with Google Cloud Platform

Big Data Tools Overview

Walkthrough Data Analyst Tasks, Challenges, and Introduce Google Cloud Platform Data Tools

Demo: Analyze 10 Billion Records with Google BigQuery

Explore 9 Fundamental Google BigQuery Features

Compare GCP Tools for Analysts, Data Scientists, and Data Engineers

Lab: Exploring Datasets with Google BigQuery

Exploring your Data with SQL

Compare Common Data Exploration Techniques

Learn How to Code High Quality Standard SQL

Explore Google BigQuery Public Datasets

Visualization Preview: Google Data Studio

Lab: Troubleshoot Common SQL Errors

Google BigQuery Pricing

Walkthrough of a BigQuery Job

Calculate BigQuery Pricing: Storage, Querying, and Streaming Costs

Optimize Queries for Cost

Lab: Calculate Google BigQuery Pricing

Cleaning and Transforming your Data

Examine the 5 Principles of Dataset Integrity

Characterize Dataset Shape and Skew

Clean and Transform Data using SQL

Clean and Transform Data using a new UI: Introducing Cloud Dataprep

Lab: Explore and Shape Data with Cloud Dataprep

Storing and Exporting Data

Compare Permanent vs Temporary Tables

Save and Export Query Results

Performance Preview: Query Cache

Lab: Creating new Permanent Tables

Ingesting New Datasets into Google BigQuery

Query from External Data Sources

Avoid Data Ingesting Pitfalls

Ingest New Data into Permanent Tables

Discuss Streaming Inserts

Lab: Ingesting and Querying New Datasets

Data Visualization

Overview of Data Visualization Principles

Exploratory vs Explanatory Analysis Approaches

Demo: Google Data Studio UI

Connect Google Data Studio to Google BigQuery

Lab: Exploring a Dataset in Google Data Studio

Joining and Merging Datasets

Merge Historical Data Tables with UNION

Introduce Table Wildcards for Easy Merges

Review Data Schemas: Linking Data Across Multiple Tables

Walkthrough JOIN Examples and Pitfalls

Lab: Join and Union Data from Multiple Tables

Advanced Functions and Clauses

Review SQL Case Statements

Introduce Analytical Window Functions

Safeguard Data with One-Way Field Encryption

Discuss Effective Sub-query and CTE design

Compare SQL and Javascript UDFs

Lab: Deriving Insights with Advanced SQL Functions

Schema Design and Nested Data Structures

Compare Google BigQuery vs Traditional RDBMS Data Architecture

Normalization vs Denormalization: Performance Tradeoffs

Schema Review: The Good, The Bad, and The Ugly

Arrays and Nested Data in Google BigQuery

Lab: Querying Nested and Repeated Data

More Visualization with Google Data Studio

Create Case Statements and Calculated Fields

Avoid Performance Pitfalls with Cache considerations

Share Dashboards and Discuss Data Access considerations

Optimizing for Performance

Avoid Google BigQuery Performance Pitfalls

Prevent Hotspots in your Data

Diagnose Performance Issues with the Query Explanation map

Lab: Optimizing and Troubleshooting Query Performance

Advanced Insights

Introducing Cloud Datalab

Cloud Datalab Notebooks and Cells

Benefits of Cloud Datalab

Data Access

Compare IAM and BigQuery Dataset Roles

Avoid Access Pitfalls

Review Members, Roles, Organizations, Account Administration, and Service Accounts

Course Images

From Data to Insights with Google Cloud Platform

By Nexus Human

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