Data Engineering Podcast

OCTOBER 21, 2019

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.

Cloud 100

Cloud Hadoop Data Lake Programming Language 100

Data Engineering Podcast

NOVEMBER 18, 2019

Summary With the constant evolution of technology for data management it can seem impossible to make an informed decision about whether to build a data warehouse, or a data lake, or just leave your data wherever it currently rests. Raghu Murthy, founder and CEO of Datacoral built data infrastructures at Yahoo!

Data Lake 100

Data Lake Scala Data Warehouse Hadoop 100

AltexSoft

OCTOBER 30, 2021

ML models are designed by data scientists, but data engineers deploy those into production. They set up resources required by the model, create pipelines to connect them with data, manage computer resources, and monitor and configure the model’s performance. Managing data and metadata. Programming.

Data Engineering 98

Data Engineering Data Engineer Engineering Machine Learning 98

ProjectPro

MARCH 7, 2016

It is necessary for individuals to bridge the wide gap between the academia big data programs and the industry practices. Most of the big data certification initiatives come from the industry with the intent to establish equilibrium between the supply and demand for skilled big data professionals.

Big Data 40

Big Data Certification Hadoop Big Data Skills 40

ProjectPro

AUGUST 26, 2015

2005 - The tiny toy elephant Hadoop was developed by Doug Cutting and Mike Cafarella to handle the big data explosion from the web. ” 1999 - The term Internet of Things (IoT) was used for the very first time by Kevin Ashton in a business presentation at P & G. US government invests $200 million in big data research projects.

Big Data 40

Big Data Unstructured Data Hadoop NoSQL 40

Edureka

JANUARY 18, 2024

Explore real-world examples, emphasizing the importance of statistical thinking in designing experiments and drawing reliable conclusions from data. Programming A minimum of one programming language, such as Python, SQL, Scala, Java, or R, is required for the data science field.

Data Science 40

Data Science Deep Learning Machine Learning NoSQL 40

Ascend.io

MAY 18, 2023

The growing complexity drove a proliferation of software and data innovations, which in turn demanded highly trained data engineers to build code-based data pipelines that ensured data quality, consistency, and stability. Why is the modern data stack so challenging?

Data Warehouse 52

Data Warehouse Data Pipeline Data Lake Data Engineering 52