Maxime Beauchemin

JANUARY 20, 2017

I joined Facebook in 2011 as a business intelligence engineer. This discipline also integrates specialization around the operation of so called “big data” distributed systems, along with concepts around the extended Hadoop ecosystem, stream processing, and in computation at scale. By the time I left in 2013, I was a data engineer.

Data Engineering 130

Data Engineering Data Engineer Engineering ETL Tools 130

ProjectPro

APRIL 14, 2015

According to Juniper Research, the market for dating through mobile apps is expected to rise from $1 billion in 2011 to $2.3 Juniper Research estimates that due to the excessive use of mobile phone apps, the online dating market is all set to rise from $1 billion in 2011 to $2.3 billion by 2016. billion in 2016.

Big Data 52

Big Data Data Analysis Algorithm Hadoop 52

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. Hadoop is an open source solution for storing and processing large unstructured data sets. In 2011, it took only 2 days to generate 1.8 zettabytes. Zettabytes of information.

Big Data 40

Big Data Unstructured Data Hadoop NoSQL 40

Snowflake

APRIL 5, 2023

Cdiscount : du commerce en ligne aux services orientés B2B Figure historique du commerce en ligne français, créée en 1998 et marketplace depuis 2011, Cdiscount s’appuie aujourd’hui sur ses savoir-faire pour compléter sa stratégie avec des offres B2B : services de logistique, déploiement de marketplace et même cybersécurité.

Hadoop 52

Hadoop Algorithm Business Intelligence SQL 52

Confluent

SEPTEMBER 25, 2019

In 2011, Marc Andressen wrote an article called Why Software is Eating the World. Our early use cases involved populating data for LinkedIn’s social graph, search, and Hadoop and data warehouse environments, as well as user-facing applications like recommendation systems, newsfeeds, ad systems, and other product features.

Database-centric 56

Database-centric Kafka Pipeline-centric Retail 56

ProjectPro

JUNE 28, 2016

Apache Kafka is breaking barriers and eliminating the slow batch processing method that is used by Hadoop. Kafka was mainly developed to make working with Hadoop easier. True that it is eliminating the limitations of Hadoop – but it will not eliminate Hadoop itself. Apache Kafka attempts to solve this issue.

Kafka 40

Kafka Systems Hadoop Big Data 40

ProjectPro

MARCH 16, 2015

Need of Hadoop in Healthcare Data Solutions Charles Boicey an Information Solutions Architect at UCI says that “Hadoop is the only technology that allows healthcare to store data in its native form. Now we can bring everything into Hadoop , regardless of data format or speed of ingest. We leave no data behind.”

Healthcare 40

Healthcare Big Data Project Hospitality 40

Zalando Engineering

JUNE 6, 2016

A 2011 McKinsey Global Institute report revealed that nearly all sectors in the US economy had at least 200 terabytes of stored data per company, thus the need for specialised engineers to solve Big Data problems was conceded.

Big Data 40

Big Data Programming Language MongoDB NoSQL 40

ProjectPro

JULY 21, 2021

This fail-safe model comes directly from the world of Big-Data Distributed systems architecture like Hadoop. If a leader broker fails or malfunctions accidentally, Zookeeper elects a new leader among the alive brokers. Message Replay/Retention in Kafka Most of the big data use cases deal with messages being consumed as they are produced.

Kafka 52

Kafka Big Data Java Architecture 52

ProjectPro

MAY 13, 2015

A recent survey conducted by Dice estimates that salaries for employees who use Hadoop and NoSQL are more than $100,000.This According to a recent survey conducted by CompTIA on IT certifications- 66% of organizations consider IT certifications as highly valuable- a significant increase from 30% in 2011.

NoSQL 40

NoSQL MongoDB Certification Database 40

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. A well designed pipeline will meet use case requirements while being efficient from a maintenance and cost perspective.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

ProjectPro

JANUARY 24, 2023

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. Ace your Big Data engineer interview by working on unique end-to-end solved Big Data Projects using Hadoop BigQuery Tutorial for Beginners: How To Use BigQuery?

Bytes 52

Bytes Google Cloud Data Warehouse Cloud Storage 52

ProjectPro

JUNE 29, 2021

Specifically designed for Hadoop. Kafka was originally created at LinkedIn and then open-sourced in 2011. Flume is mainly used for collecting and aggregating large amounts of log data from multiple sources to a centralized data location. Easy to scale. Not as easy to scale as Kafka. It can be supported across various applications.

Kafka 40

Kafka Bytes Big Data Java 40

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. Amazon launched a promotional offer in 2011 – “Amazon pays shoppers $5 if they walk out of the store without any purchases.”

Big Data 52

Big Data Hadoop Insurance Media 52

ProjectPro

MARCH 14, 2014

This is creating a huge job opportunity and there is an urgent requirement for the professionals to master Big Data Hadoop skills. Studies show, that by 2020, 80% of all Fortune 500 companies will have adopted Hadoop. Image Credit : hortonworks As per big data industry trends , the hype of Big Data had just begun in 2011.

Hadoop 40

Hadoop Big Data Data Mining Retail 40

Knowledge Hut

DECEMBER 13, 2023

The company was established in 2011, and as of right now, they employ about 250 people. The Vertica Analytics Platform provides the fastest query processing on SQL Analytics, and Hadoop is built to manage a huge volume of structured data. They work with companies including Cisco, Intel, Paypal, American Express, and more.

Big Data 52

Big Data Consulting Hadoop Amazon Web Services 52