Video Training → Udemy - Twitter + Apache Hadoop Eco System On AWS Cloud + GCP Cloud

Published by: voska89 on 26-10-2021, 19:58 | 0

Video Training → Udemy - Apache Spark for Data Engineers

Published by: voska89 on 26-10-2021, 19:26 | 0

E-Books → CMIS and Apache Chemistry in Action

Published by: ad-team on 4-10-2021, 12:44 | 0

Video Training → Udemy - Apache Cassandra for Data Engineers

Published by: voska89 on 3-10-2021, 17:18 | 0

Video Training → PacktPub - Apache Spark 3 for Data Engineering and Analytics with Python

Published by: Minhchick on 2-10-2021, 05:02 | 0

PacktPub - Apache Spark 3 for Data Engineering and Analytics with Python
English | Size: 2.16 GB
Category: Tutorial

Apache Spark 3 is an open-source distributed engine for querying and processing data.

E-Books → Apache Sun - Christine Clinton

Published by: ad-team on 24-09-2021, 16:57 | 0

Video Training → Udemy - Apache Web Server - not just learn, Master it

Published by: voska89 on 22-09-2021, 03:35 | 0

Video Training → Packt - Apache Spark 3 for Data Engineering and Analytics with Python

Published by: Minhchick on 18-09-2021, 20:24 | 0

Packt - Apache Spark 3 for Data Engineering and Analytics with Python-XQZT
English | Size: 4.91 GB
Category: Tutorial

Master Python and PySpark 3.0.1 for Data Engineering / Analytics (Databricks)

Video Training → Linkedin - Apache Spark Essential Training Big Data Engineering (2021)

Published by: voska89 on 16-09-2021, 14:13 | 0

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Advanced | Genre: eLearning | Language: English + srt | Duration: 1h 2m | Size: 156.8 MB
Data engineering is the foundation for building analytics and data science applications in the new Big Data world. Data engineering requires combining multiple big data technologies to construct data pipelines and networks to stream, process, and store data. This course focuses on building full-fledged solutions that combine Apache Spark with other Big Data tools to create end-to-end data pipelines. Instructor Kumaran Ponnambalam begins by defining data engineering, its functions, and its concepts. Next, Kumaran goes over how Spark capabilities such as parallel processing, execution plans, state management options, and machine learning work with extract, transform, load (ETL). He introduces you to batch processing use cases and processes, as well as real-time processing pipelines. After walking you through several useful best practices, Kumaran concludes with an end-to-end exercise project.