Big Data Strategy Training 
Dynatrace
JULY 6, 2022
And what are the best strategies to reduce manual labor so your team can focus on more mission-critical issues? AI that is based on machine learning needs to be trained. This requires significant data engineering efforts, as well as work to build machine-learning models. Big data automation tools.
Dynatrace
OCTOBER 17, 2022
Artificial intelligence for IT operations, or AIOps, combines big data and machine learning to provide actionable insight for IT teams to shape and automate their operational strategy. It works without having to identify training data, then training and honing. A huge advantage of this approach is speed.
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The Morning Paper
DECEMBER 13, 2020
An overview of end-to-end entity resolution for big data , Christophides et al., It’s an important part of many modern data workflows, and an area I’ve been wrestling with in one of my own projects. There are a variety of strategies both for weighting and for pruning edges. ACM Computing Surveys, Dec. 2020, Article No.
The Morning Paper
SEPTEMBER 8, 2019
Experiences with approximating queries in Microsoft’s production big-data clusters Kandula et al., Microsoft’s big data clusters have 10s of thousands of machines, and are used by thousands of users to run some pretty complex queries. All three sampling strategies are heavily used at Microsoft. VLDB’19.
The Netflix TechBlog
NOVEMBER 20, 2023
IPS enables users to continue to use the data processing patterns with minimal changes. Introduction Netflix relies on data to power its business in all phases. As our business scales globally, the demand for data is growing and the needs for scalable low latency incremental processing begin to emerge.
O'Reilly
SEPTEMBER 19, 2023
Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” ” They weren’t quite sure what this “data” substance was, but they’d convinced themselves that they had tons of it that they could monetize.
Highly Scalable
MARCH 10, 2015
In this article we are trying to take a more rigorous approach and provide a systematic view of econometric models and objective functions that can leverage data analysis to make more automated decisions. Propensity models are regression and classification models trained on customer data. Problem 2 : Recommendations.
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