Название: Advanced Data Analytics with AWS: Explore Data Analysis Concepts in the Cloud to Gain Meaningful Insights and Build Robust Data Engineering Workflows Across Diverse Data SourcesАвтор: Joseph Conley
Издательство: Orange Education Pvt Ltd, AVA
Год: 2024
Страниц: 354
Язык: английский
Формат: epub (true)
Размер: 10.1 MB
Master the Fundamentals of Data Analytics at Scale.
Key Features:
- Comprehensive guide to constructing data engineering workflows spanning diverse data sources
- Expert techniques for transforming and visualizing data to extract actionable insights
- Advanced methodologies for analyzing data and employing Machine Learning to uncover intricate patterns
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.
Let’s continue our data analytics journey by building an end-to-end data processing pipeline for our data. AWS Glue is a fully managed ETL service that makes it simple and cost-effective to categorize your data, clean it, enrich it, and move it reliably between various data stores. As with most AWS services, you can manage and visualize this entire workflow from the AWS Console, checking each step along the way. As with other AWS services, Glue is serverless, which means that you don’t need to provision a specific amount of capacity upfront. Glue will scale up and down to meet your data traffic needs. And while the out-of-the-box features of Glue should help you build a working real-time pipeline with minimal configuration, Glue also provides ways to customize your pipelines via custom scripting to further improve performance.
One of the keys to Glue’s processing power is a data processing framework called Apache Spark. Spark is a powerful tool designed to handle Big Data - think of it as a supercharged engine for processing vast amounts of information quickly and efficiently. Imagine you have a huge library of books, and you need to find every instance of the word “adventure” across all books. Doing this manually would take forever, but Spark uses advanced computing techniques to divide this huge task into smaller, manageable parts, and then works on them simultaneously, drastically speeding up the process. As Spark does this parallel processing in-memory, this results in significant performance gains, providing Glue the power it needs to transform data at large scale.
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:
- Construct streamlined data engineering workflows capable of ingesting data from diverse sources and formats.
- Employ data transformation tools to efficiently cleanse and reshape data, priming it for analysis.
- Perform ad-hoc queries for preliminary data exploration, uncovering initial insights.
- Utilize prepared datasets to craft compelling, interactive data visualizations that communicate actionable insights.
- Develop advanced Machine Learning and Generative AI workflows to delve into intricate aspects of complex datasets, uncovering deeper insights.
Who is this book for?
This book is ideal for aspiring data engineers, analysts, and data scientists seeking to deepen their understanding and practical skills in data engineering, data transformation, visualization, and advanced analytics. It is also beneficial for professionals and students looking to leverage AWS services for their data-related tasks.
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