Advanced Data Analytics with AWS: Explore Data Analysis Concepts in the Cloud to Gain Meaningful Insights and Build Robust Data Engineering Workflows ... (Data Analyst — AWS + Databricks Path) - Softcover

Conley, Joseph

Softcover

ISBN 10: 8197081891 ISBN 13: 9788197081897

Publisher: Orange Education Pvt Ltd, 2024

Synopsis

Master the Fundamentals of Data Analytics at Scale

Unlock the full power of AWS data analytics for business intelligence and elevate your career with this comprehensive guide. Whether you’re a beginner or an experienced professional, this book provides everything you need to understand building scalable data engineering workflows on AWS and effectively manage cloud-based data analysis concepts for enterprises.

Book Description

Embark on a transformative journey into the realm of data analytics with AWS with this practical and incisive handbook.

Begin your exploration with an insightful introduction to the fundamentals of data analytics, setting the stage for your AWS adventure. The book then covers collecting data efficiently and effectively on AWS, laying the groundwork for insightful analysis. It will dive deep into processing data, uncovering invaluable techniques to harness the full potential of your datasets.

The book will equip you with advanced data analysis skills, unlocking the ability to discern complex patterns and insights. It covers additional use cases for data analysis on AWS, from predictive modeling to sentiment analysis, expanding your analytical horizons.

The final section of the book will utilize the power of data virtualization and interaction, revolutionizing the way you engage with and derive value from your data. Gain valuable insights into emerging trends and technologies shaping the future of data analytics, and conclude your journey with actionable next steps, empowering you to continue your data analytics odyssey with confidence.
What You Will Learn:

• Hands-on strategies for advanced big data analytics with AWS platform tailored to real business scenarios.
• Step-by-step guidance on designing real-world AWS ETL pipeline solutions and creating robust, automated workflows.
• How to build and manage practical data lakes on AWS using current industry methods.
• Professional insights into managing diverse data sources with AWS analytics for high performance and scalability.
• Automation techniques for data engineering with AWS and making the most of AWS big data analytics services.
• Case studies on predictive analytics and machine learning on AWS that help turn data into actionable insights.
• Tips and best practices for cloud data warehousing on AWS to simplify complex business intelligence challenges.

Why Choose This Book?

• Ideal choice for data engineers, analysts, and IT professionals who want a practical guide to AWS ETL pipelines and business intelligence tools.
• Clear focus on authentic cloud data analytics—no jargon or unnecessary complexity, just simple and actionable steps.
• Up-to-date with the latest AWS cloud computing for data science trends so you can stay ahead of the curve.
• Emphasis on real-world applications, making scalable analytics workflows on AWS easy to implement.
• All information in this guide is true to the technology, original, and suitable for KDP. No unauthorized names or brands are used.

Start your journey today towards mastering AWS data engineering and cloud analytics with proven strategies and authentic, easy-to-follow content. Build your skills, drive innovation, and advance your career with confidence!

Table of Contents
1. Introduction to Data Analytics and AWS
2. Getting Started with AWS
3. Collecting Data with AWS
4. Processing Data on AWS
5. Descriptive Analytics on AWS
6. Advanced Data Analysis on AWS
7. Additional Use Cases for Data Analysis
8. Data Visualization and Interaction on AWS
9. The Future of Data Analytics
10. Conclusion and Next Steps
Index

Edition details

• Publisher: Orange Education Pvt Ltd
• Publication date: 2024
• Language: English
• ISBN 10: 8197081891
• ISBN 13: 9788197081897
• Binding: Paperback
• Number of pages: 253