ProjectPro

FEBRUARY 1, 2018

The latest update to the 11 year old big data framework Hadoop 3.0 The assumption behind Hadoop’s original approach for high availability is to make data available with 3 replicas through cheap storage options.However, However, the latest release of Hadoop 3.0 News on Hadoop - Janaury 2018 Apache Hadoop 3.0

Hadoop 52

Hadoop Food Healthcare Cloud Computing 52

ProjectPro

MAY 23, 2015

It takes in approximately $36 million dollars from across 4300 US stores everyday.This article details into Walmart Big Data Analytical culture to understand how big data analytics is leveraged to improve Customer Emotional Intelligence Quotient and Employee Intelligence Quotient. How Walmart is tracking its customers?

Big Data 52

Big Data Data Analysis Hadoop Retail 52

ProjectPro

FEBRUARY 8, 2017

.” said the McKinsey Global Institute (MGI) in its executive overview of last month's report: "The Age of Analytics: Competing in a Data-Driven World." 2016 was an exciting year for big data with organizations developing real-world solutions with big data analytics making a major impact on their bottom line.

Big Data 40

Big Data Hadoop Data Lake Data Governance 40

ProjectPro

MARCH 17, 2014

Big data and hadoop are catch-phrases these days in the tech media for describing the storage and processing of huge amounts of data. Over the years, big data has been defined in various ways and there is lots of confusion surrounding the terms big data and hadoop. What is Big Data according to IBM?

Hadoop 52

Hadoop Big Data Unstructured Data Retail 52

U-Next

SEPTEMBER 23, 2022

Previously, organizations dealt with static, centrally stored data collected from numerous sources, but with the advent of the web and cloud services, cloud computing is fast supplanting the traditional in-house system as a dependable, scalable, and cost-effective IT solution. Real-life Examples of Big Data In Action .

Big Data Ecosystem 40

Big Data Ecosystem Big Data Healthcare Data Lake 40

AltexSoft

JUNE 26, 2023

Data collection is a methodical practice aimed at acquiring meaningful information to build a consistent and complete dataset for a specific business purpose — such as decision-making, answering research questions, or strategic planning. Key differences between structured, semi-structured, and unstructured data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

phData: Data Engineering

JANUARY 3, 2022

From 2020 to 2022, the total enterprise data volume will go from approximately one petabyte (PB) to 2.02 You’re likely familiar with the term “Big Data” — and the scale of this market is continuously growing. This is where data science comes into the picture. What is Data Modeling? This is a 42.2%

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52