Artificial Intelligence Big Data Data Hardware 
Dynatrace
DECEMBER 15, 2022
Complex cloud computing environments are increasingly replacing traditional data centers. In fact, Gartner estimates that 80% of enterprises will shut down their on-premises data centers by 2025. Collect raw data in virtual and nonvirtual environments from multiple feeds, normalize and structure the data, and aggregate it for alerts.
Scalegrid
MAY 13, 2020
It can scale towards a multi-petabyte level data workload without a single issue, and it allows access to a cluster of powerful servers that will work together within a single SQL interface where you can view all of the data. This feature-packed database provides powerful and rapid analytics on data that scales up to petabyte volumes.
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All Things Distributed
DECEMBER 20, 2017
How companies can use ideas from mass production to create business with data. Developments like cloud computing, the internet of things, artificial intelligence, and machine learning are proving that IT has (again) become a strategic business driver. Value creation through data. Strategically, IT doesn't matter.
Dynatrace
MAY 1, 2023
IT operations analytics (ITOA) with artificial intelligence (AI) capabilities supports faster cloud deployment of digital products and services and trusted business insights. This operational data could be gathered from live running infrastructures using software agents, hypervisors, or network logs, for example.
Scalegrid
FEBRUARY 8, 2024
A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.
O'Reilly
SEPTEMBER 19, 2023
” I’ve called out the data field’s rebranding efforts before; but even then, I acknowledged that these weren’t just new coats of paint. Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” Goodbye, Hadoop.
Abhishek Tiwari
DECEMBER 27, 2017
ETL refers to extract, transform, load and it is generally used for data warehousing and data integration. There are several emerging data trends that will define the future of ETL in 2018. A common theme across all these trends is to remove the complexity by simplifying data management as a whole.
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