2015 Big Data Data Lake 
AWS Big Data
AUGUST 8, 2024
Today’s data lakes are expanding across lines of business operating in diverse landscapes and using various engines to process and analyze data. Traditionally, SQL views have been used to define and share filtered data sets that meet the requirements of these lines of business for easier consumption. Choose Grant.
AWS Big Data
JANUARY 24, 2024
AWS-powered data lakes, supported by the unmatched availability of Amazon Simple Storage Service (Amazon S3), can handle the scale, agility, and flexibility required to combine different data and analytics approaches. About the Authors Pathik Shah is a Sr. Analytics Architect on Amazon Athena.
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IBM Big Data Hub
MAY 8, 2018
By 2025, there will be 180 trillion gigabytes of data in the world, compared to only 10 trillion gigabytes in 2015. Of this, 90 percent will be unstructured, which is why many organizations are adopting open source data lake technologies such as Apache Hadoop to handle this expanding volume and variety of data.
AWS Big Data
OCTOBER 23, 2023
Modern applications store massive amounts of data on Amazon Simple Storage Service (Amazon S3) data lakes, providing cost-effective and highly durable storage, and allowing you to run analytics and machine learning (ML) from your data lake to generate insights on your data.
AWS Big Data
NOVEMBER 17, 2023
Athena provides a simplified, flexible way to analyze petabytes of data where it lives. You can analyze data or build applications from an Amazon Simple Storage Service (Amazon S3) data lake and 30 data sources, including on-premises data sources or other cloud systems using SQL or Python.
Peter James Thomas
AUGUST 18, 2018
That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Overlapping with the above, from around 2012, I began to get involved in also designing and implementing Big Data Architectures; initially for narrow purposes and later Data Lakes spanning entire enterprises.
AWS Big Data
FEBRUARY 1, 2023
With data volumes exhibiting a double-digit percentage growth rate year on year and the COVID pandemic disrupting global logistics in 2021, it became more critical to scale and generate near-real-time data. You can visually create, run, and monitor extract, transform, and load (ETL) pipelines to load data into your data lakes.
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