ProjectPro

MARCH 17, 2014

However, while you might be familiar with what is big data and hadoop, there is high probability that other people around you are not really sure on –What is big data, what hadoop is, what big data analytics is or why it is important. Table of Contents What is Big Data and what is the Big Deal?

Hadoop 52

Hadoop Big Data Unstructured Data Retail 52

ProjectPro

JUNE 4, 2015

In our earlier articles, we have defined “What is Apache Hadoop” To recap, Apache Hadoop is a distributed computing open source framework for storing and processing huge unstructured datasets distributed across different clusters. Table of Contents Big Data Hadoop Training Videos- What is Hadoop and its popular vendors?

Hadoop 52

Hadoop Architecture IT Java 52

phData: Data Engineering

JANUARY 3, 2022

You’re likely familiar with the term “Big Data” — and the scale of this market is continuously growing. The big data analytics market is set to reach $103 billion by 2023 , with poor data quality costing the US economy up to $3.1 Understanding the pros and cons of data storage and query options.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 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

NOVEMBER 11, 2014

This blog helps you understand the critical differences between two popular big data frameworks. Hadoop and Spark are popular apache projects in the big data ecosystem. Apache Spark is an improvement on the original Hadoop MapReduce component of the Hadoop big data ecosystem.

Hadoop 40

Hadoop Scala Machine Learning Java 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. Find sources of relevant data. Choose data collection methods and tools.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52