The Netflix TechBlog
MARCH 4, 2024
Operational automation–including but not limited to, auto diagnosis, auto remediation, auto configuration, auto tuning, auto scaling, auto debugging, and auto testing–is key to the success of modern data platforms. the retry success probability) and compute cost efficiency (i.e., Multi-objective optimizations.
Dynatrace
OCTOBER 4, 2022
While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. What is a data lakehouse? Data warehouses.
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Alex Podelko
DECEMBER 19, 2019
So you need to understand what is going on there – and Debbie is definitely an authority in that area. Boris has unique expertise in that area – especially in Big Data applications. Marrying Artificial Intelligence and Automation to Drive Operational Efficiencies by Priyanka Arora, Asha Somayajula, Subarna Gaine, Mastercard.
Dynatrace
APRIL 20, 2023
With more automated approaches to log monitoring and log analysis, however, organizations can gain visibility into their applications and infrastructure efficiently and with greater precision—even as cloud environments grow. “The weakness of a data lake is they fail when you need to access them fast,” Pawlowski said.
Percona
JANUARY 19, 2023
For instance, in Percona Managed Services , we have many clients with TBs worth of data that are well performant. In this blog post, we will review key topics to consider for managing large datasets more efficiently in MySQL. InnoDB will sort the data in primary key order, and that will serve to reference actual data pages on disk.
The Netflix TechBlog
MARCH 2, 2021
I started working at a local payment processing company after graduation, where I built survival models to calculate lifetime value and experimented with them on our brand new big data stack. I was doing data science without realizing it. My academic credentials definitely helped on the technical side.
Testsigma
MAY 14, 2021
However, the primary goal of traditional testing and cloud-based testing remains the same i.e., to deliver high-quality and efficient software. Definitely, cloud testing will involve some new technology and the testers will need to learn them. Examples are DevOps, AWS, Big Data, Testing as Service, testing environments.
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