Knowledge Hut

DECEMBER 22, 2023

Statistics are important for analyzing and interpreting the data. Programming: There are many programming languages out there that were created for different purposes. Some offer great productivity and performance to process significant amounts of data, making them better suitable for data science.

Portfolio 98

Portfolio Data Science Programming Language Scala 98

ProjectPro

MARCH 7, 2016

Big Data is in the middle of its journey, offering various life-changing career opportunities. If your career goals are headed towards Big Data, then 2016 is the best time to hone your skills in the direction, by obtaining one or more of the big data certifications. It might seem redundant to you.

Big Data 40

Big Data Certification Hadoop Big Data Skills 40

Data Engineering Podcast

NOVEMBER 18, 2019

Raghu Murthy, founder and CEO of Datacoral built data infrastructures at Yahoo! and Facebook, scaling from terabytes to petabytes of analytic data. He started Datacoral with the goal to make SQL the universal data programming language. Raghu Murthy, founder and CEO of Datacoral built data infrastructures at Yahoo!

Data Lake 100

Data Lake Scala Data Warehouse Hadoop 100

Edureka

JANUARY 18, 2024

This guide provides a comprehensive understanding of the essential skills and knowledge required to become a successful data scientist, covering data manipulation, programming, mathematics, big data, deep learning, and machine learning technologies. Gain insight into their significance in handling vast datasets.

Data Science 40

Data Science Deep Learning NoSQL Machine Learning 40

AltexSoft

OCTOBER 30, 2021

The movement of data from its source to analytical tools for end users requires a whole infrastructure, and although this flow of data must be automated, building and maintaining it is a task of a data engineer. Data engineers are programmers that create software solutions with big data. Programming.

Data Engineering 98

Data Engineering Data Engineer Engineering Machine Learning 98