Master the Big Data by Akhil Vydyula [ebook]

Master the essentials of Big Data and overcome common challenges with practical strategies and tools.

person icon Akhil Vydyula

ebook icon Tutorialspoint

language icon Language - English

updated on icon Updated on Feb, 2025

category icon Development ,Data Science,Python

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This eBook includes

Formats : PDF (Read Only)

Pages : 146

ISBN : ISBN00002

Edition : 1.0

Language : English

About the Book

Book description

This comprehensive guide is designed for beginners looking to navigate the complexities of Big Data. It provides an overview of key concepts, challenges, and best practices in Big Data management. Readers will gain insights into popular tools and techniques, enabling them to tackle real-world data challenges effectively. Whether you're a student, data enthusiast, or a professional venturing into Big Data, this ebook equips you with the foundational knowledge needed for success.

Goals

Understand the fundamental concepts of Big Data and its significance in today’s data-driven world.
Identify common challenges associated with Big Data and learn effective strategies to address them.
Gain hands-on experience with popular Big Data tools and technologies.
Develop skills to analyze and visualize large datasets for informed decision-making.

Master the Big Data by Akhil Vydyula [ebook]

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Author Details

<a href="https://market.tutorialspoint.com/author/akhil_vydyula">Akhil Vydyula</a>

Data Scientist | Data & Analytics Specialist | Entrepreneur

Hello, I'm Akhil, a Senior Data Scientist at PwC specializing in the Advisory Consulting practice with a focus on Data and Analytics.

My career journey has provided me with the opportunity to delve into various aspects of data analysis and modelling, particularly within the BFSI sector, where I've managed the full lifecycle of development and execution.

I possess a diverse skill set that includes data wrangling, feature engineering, algorithm development, and model implementation. My expertise lies in leveraging advanced data mining techniques, such as statistical analysis, hypothesis testing, regression analysis, and both unsupervised and supervised machine learning, to uncover valuable insights and drive data-informed decisions. I'm especially passionate about risk identification through decision models, and I've honed my skills in machine learning algorithms, data/text mining, and data visualization to tackle these challenges effectively.

Currently, I am deeply involved in an exciting Amazon cloud project, focusing on the end-to-end development of ETL processes. I write ETL code using PySpark/Spark SQL to extract data from S3 buckets, perform necessary transformations, and execute scripts via EMR services. The processed data is then loaded into Postgres SQL (RDS/Redshift) in full, incremental, and live modes. To streamline operations, I’ve automated this process by setting up jobs in Step Functions, which trigger EMR instances in a specified sequence and provide execution status notifications. These Step Functions are scheduled through EventBridge rules.

Moreover, I've extensively utilized AWS Glue to replicate source data from on-premises systems to raw-layer S3 buckets using AWS DMS services. One of my key strengths is understanding the intricacies of data and applying precise transformations to convert data from multiple tables into key-value pairs. I’ve also optimized stored procedures in Postgres SQL to efficiently perform second-level transformations, joining multiple tables and loading the data into final tables.

I am passionate about harnessing the power of data to generate actionable insights and improve business outcomes. If you share this passion or are interested in collaborating on data-driven projects, I would love to connect. Let’s explore the endless possibilities that data analytics can offer!