Analytics Application Data Storage Technology 
Snowflake
JULY 13, 2023
As a result, ESO needed a data platform that could flex to support high availability and scalability, and that also helped the company to manage and optimize its spend. ESO’s data analytics platform was previously based on Cloudera running Scala and Spark.
Workfall
JUNE 27, 2023
It enables the collection of data from diverse platforms in real-time, organizing it into consolidated feeds while providing comprehensive metrics for monitoring. As a distributed data storage system, Kafka has been meticulously optimized to handle the continuous flow of streaming data generated by numerous sources.
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Knowledge Hut
JUNE 26, 2023
Get ready to delve into fascinating data engineering project concepts and explore a world of exciting data engineering projects in this article. Before working on these initiatives, you should be conversant with topics and technologies. Participating in a data engineering project is a great way to learn the ropes of the field.
Knowledge Hut
DECEMBER 26, 2023
Business intelligence (BI) is the collective name for a set of processes, systems, and technologies that turn raw data into knowledge that can be used to operate enterprises profitably. Business intelligence solutions comBIne technology and strategy for gathering, analyzing, and interpreting data from internal and external sources.
Precisely
MARCH 10, 2023
With the right geocoding technology, accurate and standardized address data is entirely possible. This capability opens the door to a wide array of data analytics applications. The Rise of Cloud Analytics Data analytics has advanced rapidly over the past decade.
Cloudera
NOVEMBER 13, 2017
Cloud PaaS takes this a step further and allows users to focus directly on building data pipelines, training machine learning models, developing analytics applications — all the value creation efforts, vs the infrastructure operations. These qualities are at the heart of our differentiation. We’re here to help.
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.
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