FreeComputerBooks.com
Links to Free Computer, Mathematics, Technical Books all over the World
|
|
- Title: Data Engineering Teams: Creating Successful Big Data Teams and Products
- Author(s) Jesse Anderson
- Publisher: SMOKING HAND, LLC. (2022)
- Hardcover/Paperback: N/A
- eBook: PDF
- Language: English
- ISBN-10/ASIN: N/A
- ISBN-13: 978-1732649606
- Share This:
Unlock the secrets of Big Data and AI projects. We've always had teams for managing databases, but with the data management landscape so rapidly evolving – you need to take your data teams to a whole new level.
About the Author- Jesse Anderson is a Managing Director of Big Data Institute, and a seasoned professional with extensive experience in various organizations like Cloudera and Intuit.
- Data Engineering Teams: Creating Successful Big Data Teams and Products
- The Mirror Site (1) - PDF
- Book Homepage (PDF, ePub, etc.)
-
97 Things Every Data Engineer Should Know (Tobias Macey)
With this in-depth book, current and aspiring engineers will learn powerful real-world best practices for managing data big and small. Experts share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges.
-
The Evolving Role of the Data Engineer (Andy Oram)
If you're pursuing a career in data engineering or looking for ways to adapt your enterprise to the world of big data, this report shares the knowledge you need to find your way forward.
-
Open Source Data Pipelines for Intelligent Applications
Provides data engineers and scientists insight into how Kubernetes provides a platform for building data platforms that increase an organization’s data agility. How Kubernetes has changed the way we process big data and why businesses must adapt.
-
Data Science at the Command Line, 2nd Ed. (Jeroen Janssens)
This hands-on guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. Learn how to combine small, yet powerful, command-line tools to quickly obtain, scrub, explore, and model your data.
-
Data Engineering Cookbook: The Plumbing of Data Science
This is a practical and comprehensive guide. You will learn the basics of data engineering. Then you will learn the technologies and frameworks required to build data pipelines to work with large datasets.
-
The Ultimate Guide to Effective Data Cleaning
With this in-depth book, current and aspiring engineers will learn powerful real-world best practices for managing data big and small. Experts share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges.
-
The Data Engineer's Guide to Apache Spark (Databricks)
This book is for data engineers looking to leverage the immense growth of Apache Spark to build faster and more reliable data pipelines. It leverages Spark's amazing speed, scalability, simplicity, and versatility to build practical Big Data solutions.
-
Building the Data Lakehouse (Bill Inmon, et al.)
Learn about the features and architecture of the data lakehouse, along with its powerful analytical infrastructure. The data lakehouse is the next generation of the data warehouse and data lake.
-
Python Data Science Handbook: Essential Tools (Jake VanderPlas)
Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all - IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.
-
Data Science: Theories, Models, Algorithms, and Analytics
It provides a bucket full of information regarding Data Science, covers a wide variety of sections by giving access to theories, data science algorithms, tools and analytics. You'll explore the right approach to best practices to guide you along the way.
-
97 Things Every Cloud Engineer Should Know: from the Experts
With this book, professionals from around the world provide valuable insight into today's cloud engineering role. It explore the entire cloud computing experience, including fundamentals, architecture, and migration.
:
|
|