Cloudera

OCTOBER 3, 2018

First, remember the history of Apache Hadoop. Google built an innovative scale-out platform for data storage and analysis in the late 1990s and early 2000s, and published research papers about their work. The two of them started the Hadoop project to build an open-source implementation of Google’s system.

Hadoop 75

Hadoop Cloud Data Storage Machine Learning 75

ProjectPro

JUNE 6, 2025

Google BigQuery Data Analysis Workflows Google BigQuery Architecture- A Detailed Overview Google BigQuery Datatypes BigQuery Tutorial for Beginners: How To Use BigQuery? Since its public release in 2011, BigQuery has been marketed as a unique analytics cloud data warehouse tool that requires no virtual machines or hardware resources.

Bytes 40

Bytes Google Cloud Data Warehouse Cloud Storage 40

ProjectPro

MARCH 14, 2014

Every department of an organization including marketing, finance and HR are now getting direct access to their own data. This is creating a huge job opportunity and there is an urgent requirement for the professionals to master Big Data Hadoop skills. In 2015, big data has evolved beyond the hype.

Hadoop 40

Hadoop Big Data Data Mining Consulting 40

Knowledge Hut

DECEMBER 13, 2023

The company was established in 2011, and as of right now, they employ about 250 people. Tata Consultancy Services Tata Consultancy Services is known among the big data companies in India. Micro Focus has rapidly amassed a robust portfolio of Big Data products in just a short amount of time.

Big Data 52

Big Data Consulting Amazon Web Services Hadoop 52

ProjectPro

AUGUST 6, 2015

Let’s take a look at how Amazon uses Big Data- Amazon has approximately 1 million hadoop clusters to support their risk management, affiliate network, website updates, machine learning systems and more. Sports brands like ESPN have also got on to the big data bandwagon. ” Interesting?

Big Data 52

Big Data Insurance Hadoop Media 52

Monte Carlo

JUNE 14, 2023

5 Data pipeline architecture designs and their evolution The Hadoop era , roughly 2011 to 2017, arguably ushered in big data processing capabilities to mainstream organizations. Data then, and even today for some organizations, was primarily hosted in on-premises databases with non-scalable storage.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

ProjectPro

JANUARY 24, 2023

Google BigQuery Data Analysis Workflows Google BigQuery Architecture- A Detailed Overview Google BigQuery Datatypes BigQuery Tutorial for Beginners: How To Use BigQuery? Since its public release in 2011, BigQuery has been marketed as a unique analytics cloud data warehouse tool that requires no virtual machines or hardware resources.

Bytes 52

Bytes Google Cloud Data Warehouse Cloud Storage 52