Big Data Cloud Analytics with AWS, Azure, and GCP Training

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Unleashing Big Data Insights: Cloud Analytics with AWS, Azure, and GCP

This comprehensive training program on Big Data Cloud Analytics will explore leading cloud platforms such as AWS, Azure, and Google Cloud Platform (GCP). Participants will gain insights into the tools and methodologies for effectively managing and analyzing vast data sets in the cloud. Through hands-on sessions and real-world case studies, attendees will learn how to leverage the unique features of each platform to drive data-driven decision-making and gain competitive advantages in their organizations.

Skills Covered

Amazon Web Services (AWS)

Azure Data Factory

Google Cloud Professional Data Engineer

Data Warehousing

Big Data Technologies

Cloud Architecture

Data Lakes

Mastering Big Data Cloud Analytics: A Deep Dive into AWS, Azure, and GCP

In this in-depth training, participants will embark on a journey through the landscape of Big Data analytics using three of the most popular cloud services: AWS, Azure, and GCP. The course begins with foundational concepts of Big Data, including characteristics, challenges, and the importance of analytics for businesses today. Participants will explore AWS services like Amazon Redshift, Athena, and EMR, learning how to setup data lakes and perform real-time analytics. The training will highlight Azure's capabilities with tools such as Azure Synapse Analytics, allowing participants to manage data in a holistic way and integrate AI-powered analytics. Google Cloud Platform will introduce participants to BigQuery and Dataflow, focusing on serverless data processing and analysis to streamline workflows. Throughout the training, there will be interactive demonstrations and labs to practice the skills and concepts learned. Additionally, case studies from various industries will showcase how organizations have successfully implemented Big Data solutions on these platforms, providing insights into best practices and lessons learned. By the end of this training, participants will be equipped with the skills necessary to leverage big data analytics effectively in a cloud environment, enabling them to make more informed business decisions and gain actionable insights.

Who is this Program Designed for?

Data Engineers

Data engineers will learn to design and implement cloud-based architectures and workflows for managing and processing large datasets efficiently, enhancing their ability to deliver reliable data solutions.

Business Analysts

Business analysts will benefit from understanding how to leverage cloud analytics tools to derive insights and support data-driven strategies, ultimately improving decision-making processes in their organizations.

IT Managers

IT managers will gain knowledge in cloud analytics strategies to support large-scale data initiatives and optimize technology investments, ensuring alignment with business goals and objectives.

Data Scientists

Data scientists will enhance their skills in using cloud services for data exploration and model development, learning to utilize Big Data tools and frameworks for advanced analytics.

What You Will Learn

Introduction to Big Data Concepts

Define key concepts and terminologies related to Big Data analytics in cloud environments.. Explain the importance and benefits of using cloud platforms for Big Data solutions.

Overview of Cloud Platforms for Big Data

Compare AWS, Azure, and GCP in terms of their Big Data service offerings.. Identify use cases where each platform excels in Big Data analytics.

Data Ingestion and Storage Solutions

Utilize different data ingestion strategies using AWS S3, Azure Blob Storage, and GCP Cloud Storage.. Implement best practices for storing large volumes of data efficiently in the cloud.

Data Processing Techniques and Tools

Hands-on experience with data processing tools such as AWS Lambda, Azure Functions, and GCP Dataflow.. Design and build data pipelines for real-time and batch processing scenarios.

Data Analysis and Visualization

Leverage cloud-native analytics tools like Amazon Athena, Azure Synapse, and GCP Big

Query for querying large datasets.. Create visualizations using tools such as Tableau, Power BI, and Google Data Studio integrated with cloud data sources.

Advanced Analytics and Machine Learning Integration

Implement machine learning models using AI services from AWS, Azure, and GCP.. Evaluate performance metrics of different models and optimize them for cloud environments.

Requirements

Understanding of fundamental cloud computing concepts and technologies

Ability to analyze and interpret cloud-related big data analytics using AWS, Azure, and GCP

Experience with data visualization tools common in cloud environments

Knowledge of Big Data principles and frameworks (e.g., Hadoop, Spark)

Skills to develop and deploy end-to-end data pipelines in cloud platforms

Benefits of our Training Approach

Industry Expert

Expert-led courses designed by industry leading professionals

Learning Formats

Flexible formats: online, in-person, and blended options.

Industry Coverage

Covers a wide range of industries and skills.

Tailored Programs

Customizable programs to meet your company’s specific needs.

Engaging Learning

Interactive experiences designed to boost retention.

Team Scalability

Scalability to accommodate teams of any size

ICT50120 Diploma of Information Technology (Big Data Cloud Analytics)

Upon successful completion, you will receive the nationally recognized ICT50120 Diploma of Information Technology qualification with a specialization in Big Data Cloud Analytics. This certification recognizes your ability to analyze and leverage big data using cloud technologies, enhancing your career prospects in the information technology sector.

Employees Love Our Training

John M.

Christina streamlined our cloud infrastructure. Her DevOps expertise saved us a lot of time!

John M.

She automated our deployments seamlessly. Excellent work!

John M.

Christina is highly skilled in Kubernetes and Docker. Great to work with!

John M.

Her CI/CD solutions were spot on. I highly recommend her for any cloud project!

FAQ

Are there any prerequisites for this course?

While there are no strict prerequisites, a basic understanding of cloud computing and data analytics principles is recommended to maximize learning.

How much time will I need to commit to this course?

Participants should expect to spend around 6 hours per week over 5 weeks to complete the course, including both instructional time and hands-on practice.

What practical skills will I gain from this training?

You will gain practical skills in setting up data storage, processing pipelines, and performing analytics using major cloud platforms, which are directly applicable in real-world data projects.

What outcomes can I expect after completing this course?

Upon completion, you will have a solid understanding of Big Data analytics in cloud environments and the ability to implement solutions on AWS, Azure, and GCP, enhancing your employability in data-centric roles.

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