Topic: Data Engineering
This page features the most recent and most popular posts on Data Engineering and Data Engineers
Latest posts on Data Engineering
- Data vault: new weaponry in your data science toolkit - Mar 31, 2021Data Vault is a modern data modelling approach for capturing (historical) data in a structurally auditable and tractable way. While very helpful for data engineers, the Data Vault also enables Data Science in practice.
- How to build a DAG Factory on Airflow - Mar 19, 2021A guide to building efficient DAGs with half of the code.
- Wrangle Summit 2021: All the Best People, Ideas, and Technology in Data Engineering, All in One Place - Mar 18, 2021At Wrangle Summit 2021, Apr 7-9, you’ll get access to all the best people, ideas, and technology in data engineering, all in one place. Learn how to refine raw data and engineer unique data products, and gain insights from your data that can catalyze real, measurable business success.
- Introducing dbt, the ETL and ELT Disrupter - Mar 17, 2021Moving and processing data is happening 24/7/365 world-wide at massive scales that only get larger by the hour. Tools exist to introduce efficiencies in how data can be extracted from sources, transformed through calculations, and loaded into target data repositories. However, on their own, these tools can introduce some restrictions in the processing, especially for the needs of data analytics and data science.
- 9 Skills You Need to Become a Data Engineer - Mar 4, 2021A data engineer is a fast-growing profession with amazing challenges and rewards. Which skills do you need to become a data engineer? In this post, we’ll take a look at both hard and soft skills.
Most popular (badge-winning) recent posts on Data Engineering
- 9 Skills You Need to Become a Data Engineer [Silver Blog]A data engineer is a fast-growing profession with amazing challenges and rewards. Which skills do you need to become a data engineer? In this post, we’ll take a look at both hard and soft skills.
- Data Science Learning Roadmap for 2021 [Gold Blog]Venturing into the world of Data Science is an exciting, interesting, and rewarding path to consider. There is a great deal to master, and this self-learning recommendation plan will guide you toward establishing a solid understanding of all that is foundational to data science as well as a solid portfolio to showcase your developed expertise.
- Data Engineering — the Cousin of Data Science, is Troublesome [Gold Blog]A Data Scientist must be a jack of many, many trades. Especially when working in broader teams, understanding the roles of others, such as data engineering, can help you validate progress and be aware of potential pitfalls. So, how can you convince your analysts to realize the importance of expanding their toolkit? Examples from real life often provide great insight.
- Why the Future of ETL Is Not ELT, But EL(T) [Platinum Blog]The well-established technologies and tools around ETL (Extract, Transform, Load) are undergoing a potential paradigm shift with new approaches to data storage and expanding cloud-based compute. Decoupling the EL from T could reconcile analytics and operational data management use cases, in a new landscape where data warehouses and data lakes are merging.
- Introduction to Data Engineering [Gold Blog]The Q&A for the most frequently asked questions about Data Engineering: What does a data engineer do? What is a data pipeline? What is a data warehouse? How is a data engineer different from a data scientist? What skills and programming languages do you need to learn to become a data engineer?
- The Rise of the Machine Learning Engineer [Gold Blog]The evolution of Big Data into machine learning applications ushered in an exciting era of new roles and skillsets that became necessary to implement these technologies. With the Machine Learning Engineer being such a crucial component today, where the evolution of this field will take us tomorrow should be fascinating.
- Skills to Build for Data Engineering [Silver Blog]This article jumps into the latest skill set observations in the Data Engineering Job Market which could definitely add a boost to your existing career or assist you in starting off your Data Engineering journey.
- 7 Resources to Becoming a Data Engineer [Gold Blog]An estimated 8,650% growth of the volume of Data to 175 zetabytes from 2010 to 2025 has created an enormous need for Data Engineers to build an organization's big data platform to be fast, efficient and scalable.
- A Winning Game Plan For Building Your Data Science Team [Silver Blog]We need to understand the responsibilities, capabilities, expectations and competencies of the Data Engineer, Data Scientist and Business Stakeholder.
- A Beginner’s Guide to Data Engineering – Part I [Silver Blog]Data Engineering: The Close Cousin of Data Science.
- 37 Reasons why your Neural Network is not workingOver the course of many debugging sessions, I’ve compiled my experience along with the best ideas around in this handy list. I hope they would be useful to you.
- 5 Career Paths in Big Data and Data Science, ExplainedSexiest job... massive shortage... blah blah blah. Are you looking to get a real handle on the career paths available in "Data Science" and "Big Data?" Read this article for insight on where to look to sharpen the required entry-level skills.