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Data Mining Problems in Retail

Highly Scalable

Retail is one of the most important business domains for data science and data mining applications because of its prolific data and numerous optimization problems such as optimal prices, discounts, recommendations, and stock levels that can be solved using data analysis methods.

Retail 152
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Conducting log analysis with an observability platform and full data context

Dynatrace

Logs highlight observability challenges Ingesting, storing, and processing the unprecedented explosion of data from sources such as software as a service, multicloud environments, containers, and serverless architectures can be overwhelming for today’s organizations.

Analytics 184
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Kubernetes in the wild report 2023

Dynatrace

Accordingly, for classic database use cases, organizations use a variety of relational databases and document stores. Specifically, they provide asynchronous communications within microservices architectures and high-throughput distributed systems. The data covers the period of January 2021 through September 2022.

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A case for ELT

Abhishek Tiwari

Cheap storage and on-demand compute in the cloud coupled with the emergence of new big data frameworks and tools are forcing us to rethink the whole ETL and data warehousing architecture. In addition, this approach is more tailored for both structured as well unstructured data sets. Classic ETL.