Cloudera

JANUARY 22, 2019

Forrester describes Big Data Fabric as, “A unified, trusted, and comprehensive view of business data produced by orchestrating data sources automatically, intelligently, and securely, then preparing and processing them in big data platforms such as Hadoop and Apache Spark, data lakes, in-memory, and NoSQL.”.

Big Data 44

Big Data NoSQL Data Lake Hadoop 44

Knowledge Hut

JULY 5, 2024

Big Data Boom: Fast forward to the 2000s, and Big Data crashed onto the scene. Hadoop and Spark: The cavalry arrived in the form of Hadoop and Spark, revolutionizing how we process and analyze large datasets. Suddenly, we were dealing with massive amounts of information, and traditional tools struggled to keep up.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Cleanse 52

Monte Carlo

MAY 14, 2024

The “legacy” table formats The data landscape has evolved so quickly that table formats pioneered within the last 25 years are already achieving “legacy” status. It was designed to support high-volume data exchange and compatibility across different system versions, which is essential for streaming architectures such as Apache Kafka.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Monte Carlo

APRIL 24, 2023

Data lakes are useful, flexible data storage repositories that enable many types of data to be stored in its rawest state. Notice how Snowflake dutifully avoids (what may be a false) dichotomy by simply calling themselves a “data cloud.” Not to mention seamless integration with the Oracle ecosystem.

Data Lake 52

Data Lake Google Cloud Data Warehouse Cloud Storage 52

Knowledge Hut

JUNE 30, 2023

Key Benefits and Takeaways: Understand data intake strategies and data transformation procedures by learning data engineering principles with Python. Investigate alternative data storage solutions, such as databases and data lakes. Key Benefits and Takeaways: Learn the core concepts of big data systems.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Warehouse 52

ProjectPro

AUGUST 26, 2015

The largest item on Claude Shannon’s list of items was the Library of Congress that measured 100 trillion bits of data. 1960 - Data warehousing became cheaper. 1996 - Digital data storage became cost effective than paper - according to R.J.T. 2008 -Google processed 20 petabytes of data in a single day.

Big Data 40

Big Data Unstructured Data Hadoop NoSQL 40

Sync Computing

NOVEMBER 7, 2024

Estimates vary, but the amount of new data produced, recorded, and stored is in the ballpark of 200 exabytes per day on average, with an annual total growing from 33 zettabytes in 2018 to a projected 169 zettabytes in 2025. In case you dont know your metrics, these numbers are astronomical!

Data Lake 52

Data Lake Data Warehouse Business Intelligence Unstructured Data 52

ProjectPro

JUNE 6, 2025

Data Engineer: Key Responsibilities Some of the day-to-day responsibilities of a big data engineer include- Data Pipeline Design and Development- Building and maintaining pipelines to gather and load raw (structured/unstructured) data from various sources. SQL, NoSQL) are essential.

Machine Learning 40

Machine Learning Computer Science Consulting Software Engineering 40

Cloudera

DECEMBER 12, 2018

I spent eight years in the real-world performance group where I specialized in high visibility and high impact data warehousing competes and benchmarks. Greg Rahn: Toward the end of that eight-year stint, I saw this thing coming up called Hadoop and an engine called Hive. There’s MongoDB for document stores.

Data Warehouse 42

Data Warehouse Relational Database Hadoop BI 42

Rockset

JANUARY 23, 2020

While traditional RDBMS databases served well the data storage and data processing needs of the enterprise world from their commercial inception in the late 1970s until the dotcom era, the large amounts of data processed by the new applications—and the speed at which this data needs to be processed—required a new approach.

Database 40

Database MySQL Kafka NoSQL 40

Knowledge Hut

NOVEMBER 16, 2023

Data Storage As a Solutions Architect, you must have knowledge of databases. There are several data storage options available on the AWS platform. This includes powerful and simple bucket storage like S3, relational database service, and Hadoop clusters.

AWS 52

AWS Cloud Computing Certification Architecture 52

ProjectPro

JULY 15, 2021

According to an Indeed Jobs report, the share of cloud computing jobs has increased by 42% per million from 2018 to 2021. It is recommended to use SQL database for data storage as it comes with built-in security tools and features. Decision-making and support will be performed using data mining and feature extraction.

Cloud Computing 40

Cloud Computing Cloud Project Banking 40