Data Engineering 101
Data Engineering 101 by Anna Antypenko
English | June 1, 2024 | ISBN: N/A | ASIN: B0D5FLXXX5 | 175 pages | EPUB | 1.36 Mb
English | June 1, 2024 | ISBN: N/A | ASIN: B0D5FLXXX5 | 175 pages | EPUB | 1.36 Mb
Are you tired of reading academic textbooks that make data engineering seem like a field only for the coding elites?
Do you feel like you’re constantly struggling with complex datasets, unable to make sense of them?
Do you want to unlock the true potential of data and become a sought-after professional in a rapidly evolving industry?
If you’ve answered yes to these questions, then you’re in the right place. Why? Because mastering data engineering doesn’t have to be an uphill battle.
Even if you’ve tried learning Python, SQL, or Hadoop, and it felt like you were reading a foreign language, it’s not the end of your data journey.
In fact, becoming a proficient data engineer and unlocking lucrative opportunities in data is achievable and it’s much easier than you think.
Here is just a small fraction of what you'll discover inside this book:
- The foundational overview: What is data engineering and why it’s critical to businesses in the digital age?
- Step-by-step guide to mastering Python, the most used language in data engineering
- Breaking down complex database systems into understandable chunks: Practical exposure to SQL, NoSQL and NewSQL
- Navigating the maze of ETL (Extract, Transform, Load) processes like a seasoned data engineer
- Demystifying Hadoop and its components: Get up and running with Hadoop ecosystems in no time.
- Unlocking the potential of Apache Kafka for real-time data processing
- The definitive guide to data warehousing and data lakes - which one is right for you?
- Mastering data pipelines: How to execute effective, efficient and fault-tolerant pipelines
- Exploring Cloud solutions: An in-depth guide to Amazon Web Services (AWS), Google Cloud and Azure
- The future of data engineering: Get a jump start on distributed systems, edge computing, and more