Ascend.io

FEBRUARY 15, 2023

Back in 2004, I got to work with MapReduce at Google years before Apache Hadoop was even released, using it on a nearly daily basis to analyze user activity on web search and analyze the efficacy of user experiments. Becoming subconsciously data-first In 2007, my two colleagues and I left Google and started Ooyala.

Cloud 52

Cloud Amazon Web Services Hadoop Telecommunication 52

Ascend.io

FEBRUARY 15, 2023

Back in 2004, I got to work with MapReduce at Google years before Apache Hadoop was even released, using it on a nearly daily basis to analyze user activity on web search and analyze the efficacy of user experiments. Becoming subconsciously data-first In 2007, my two colleagues and I left Google and started Ooyala.

Cloud 52

Cloud Amazon Web Services Hadoop Telecommunication 52

Towards Data Science

FEBRUARY 15, 2023

The main player in the context of the first data lakes was Hadoop, a distributed file system, with MapReduce, a processing paradigm built over the idea of minimal data movement and high parallelism. The proposal is simple — “Trow everything you have here inside and worry later”. The implementation 0.

Data Lake 80

Data Lake Data Warehouse Hadoop Data Architecture 80

Rockset

AUGUST 10, 2020

Traditional BI had its Renaissance moments with the advent of Big Data technologies such as Hadoop, and then cloud data lakes and warehouses have brought everyone to the Modern era. But these traditional BI tools are built for assisting strategic decision making at the executive level.

BI 40

BI Data Lake Hadoop SQL 40

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. Hadoop is an open source solution for storing and processing large unstructured data sets. zettabytes.

Big Data 40

Big Data Unstructured Data Hadoop NoSQL 40