Table of Contents
What should a data engineer study?
Data engineers typically have an undergraduate degree in math, science, or a business-related field. The expertise gained from this kind of degree allows them to use programming languages to mine and query data, and in some cases use big data SQL engines.
How can I be good at data engineering?
The Path to Becoming a Data Engineer
- Become proficient at programming.
- Learn automation and scripting.
- Understand your databases.
- Master data processing techniques.
- Schedule your workflows.
- Study cloud computing.
- Internalize infrastructure.
- Follow the trends.
Does data Engineering pay well?
This is based on earnings reported by thousands of companies. You have to admit it’s a pretty good amount of cash! Another source, the job aggregator and information site Indeed.com, reports even higher earnings for data engineers: $129,415 per year with a possible $5,000 bonus.
What are the best books to learn data engineering?
In fact, Analytics Vidhya’s Founder and CEO Mr. Kunal Jain reads one book every week! There is no substitute for books, it’s still one of the best resources you would want to get your hands on. Books are a vital way of absorbing information on Data Engineering. So let’s begin! 1. The Data Engineering Cookbook by Andreas Kretz
What are the best books on feature engineering?
Top books on feature engineering include: Feature Engineering and Selection: A Practical Approach for Predictive Models, 2019. Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists, 2018. Let’s take a closer look at each in turn.
What are some of the best books on data cleaning?
I highly recommend it! Bad Data Handbook, on Amazon. The book “ Best Practices in Data Cleaning: A Complete Guide to Everything You Need to Do Before and After Collecting Your Data ” was written by Jason Osborne and was published in 2012.
What are the best books to learn about Hadoop architecture?
(5) Architecting Modern Data Platform by Jan Kunigk, Ian Buss, Paul Wilkinson, Lars George: A good book with fantastic graphs and images. Compared to (4), it more focuses on the external Hadoop services (Server RAM, CPU specifications, or Network Band Requirements, etc). Some are short, but some are demanding to start.