Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. Data Engineers are engineers responsible for uncovering trends in data sets and building algorithms and data pipelines to make raw data beneficial for the organization.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Knowledge Hut

SEPTEMBER 26, 2023

This cloud-centric approach ensures scalability, flexibility, and cost-efficiency for your data workloads. Some of the prominent languages supported include: Scala: Ideal for developers who want to leverage the full power of Apache Spark. Python: Widely used for data analysis, scripting, and machine learning.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Cloudera

SEPTEMBER 17, 2020

For modern data engineers using Apache Spark, DE offers an all-inclusive toolset that enables data pipeline orchestration, automation, advanced monitoring, visual troubleshooting, and a comprehensive management toolset for streamlining ETL processes and making complex data actionable across your analytic teams. Job Deployment Made Simple.

Data Pipeline 103

Data Pipeline Data Engineering Data Engineer Engineering 103

AltexSoft

JULY 18, 2023

With its native support for in-memory distributed processing and fault tolerance, Spark empowers users to build complex, multi-stage data pipelines with relative ease and efficiency. It has in-memory computing capabilities to deliver speed, a generalized execution model to support various applications, and Java, Scala, Python, and R APIs.

Big Data 52

Big Data Data Process Process Hadoop 52

Dataquest

JANUARY 25, 2017

This is where data engineers come in — they build pipelines that transform that data into formats that data scientists can use. Roughly, the operations in a data pipeline consist of the following phases: Ingestion — this involves gathering in the needed data. A data scientist is only as good as the data they have access to.

Data Engineering 52

Data Engineering Data Engineer Pipeline-centric Database-centric 52

AltexSoft

JUNE 7, 2021

It also provides tools for statistics, creating ML pipelines, model evaluation, and more. Written in Scala, the framework also supports Java, Python, and R. As a result, companies can count on a wider pool of talent — if compared with Java-centric Hadoop. Multi-language intuitive APIs. Spark limitations. Pricey hardware.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Databand.ai

DECEMBER 20, 2022

He specializes in distributed systems and data processing at scale, regularly working on data pipelines and taking complex analyses authored by data scientists/analysts and keeping them running in production. He is also a member of The Apache Software Foundation. You can also watch both episodes with Maxime (episodes #18 and #19).

Data Analytics 52

Data Analytics Google Cloud Data Science Data Mining 52