Course Description
Course Overview
The From Data to Insights with Google Cloud Platform (DIGCP) course is designed to provide individuals with the knowledge and skills necessary to process, analyze, and visualize data using the Google Cloud Platform (GCP) services. This course focuses on the end-to-end data lifecycle, from data ingestion and storage to data processing and visualization, enabling participants to derive valuable insights from their data using GCP’s powerful data analytics tools.
Prerequisites
To enroll in the DIGCP course, participants should have a basic understanding of data concepts and familiarity with GCP fundamentals. Basic knowledge of SQL and data analysis techniques will be beneficial. Participants should also have access to a GCP project or demo environment to practice the concepts covered in the course.
Methodology
The DIGCP course follows a blended learning approach, combining theoretical instruction, demonstrations, discussions, and hands-on labs. Participants will engage in instructor-led sessions where data processing and analysis concepts, as well as best practices for GCP services, are explained. They will also have access to GCP resources and tools to gain practical experience in working with data analytics workflows. The course encourages active participation, discussions, and collaborative problem-solving to reinforce learning.
Course Outline
Introduction to Data Analytics on GCP
Overview of the data analytics process and GCP’s data analytics services
Understanding the data lifecycle and the role of GCP in each stage
Exploring GCP tools and resources for data analytics
Data Ingestion and Storage
Ingesting data from various sources into GCP using services like Cloud Storage, Pub/Sub, and Dataflow
Storing and organizing data using GCP’s data storage services such as BigQuery, Cloud SQL, and Cloud Spanner
Ensuring data reliability, consistency, and security in GCP
Data Processing and Transformation
Processing and transforming data using GCP’s data processing services such as Dataproc and Dataflow
Utilizing data processing frameworks like Apache Beam and Apache Spark on GCP
Implementing batch and real-time data processing pipelines
Data Analysis and Visualization
Analyzing and querying large datasets with GCP’s BigQuery
Performing advanced analytics using SQL and BigQuery ML
Visualizing data and creating interactive dashboards with Data Studio and Looker
Machine Learning for Data Analytics
Introduction to machine learning concepts and techniques
Applying machine learning algorithms and models to analyze data
Utilizing GCP’s machine learning services such as AutoML and AI Platform
Data Governance and Security
Implementing data governance policies and controls
Ensuring data privacy, compliance, and security in data analytics workflows
Monitoring and auditing data access and usage in GCP
Outcome
By the end of the DIGCP course, participants will have:
- Developed a comprehensive understanding of the data analytics process and GCP’s data analytics services
- Acquired practical knowledge in ingesting, storing, processing, analyzing, and visualizing data using GCP tools and services
- Gained expertise in utilizing GCP’s data analytics services for deriving insights from data
- Learned techniques for data governance, privacy, compliance, and security in GCP
- Gained hands-on experience through practical labs and exercises
- Prepared to work with data analytics workflows on GCP and derive valuable insights from data
Labs
The DIGCP course includes hands-on labs that provide participants with practical experience in working with data analytics workflows on GCP. Some examples of lab exercises include:
- Ingesting data from various sources into GCP using Cloud Storage and Pub/Sub
- Storing and organizing data in GCP’s data storage services like BigQuery and Cloud SQL
- Processing and transforming data using GCP’s data processing services like Dataflow
- Analyzing and querying large datasets with BigQuery
- Creating interactive dashboards and visualizations using Data Studio or Looker
- Applying machine learning techniques to analyze data using GCP’s machine learning services
These labs enable participants to apply the concepts learned in the course and gain hands-on experience in working with data analytics workflows on GCP, allowing them to develop practical skills in processing, analyzing, and visualizing data using GCP’s data analytics tools.