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An In-Depth Guide to Real-Time Analytics

Striim

“Sometimes there’s so much data that old batch processing (late at night once a day or once a week) just doesn’t have time to move all data and hence the only way to do it is trickle feed data via CDC,” says Dmitriy Rudakov, Director of Solution Architecture at Striim.

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What is Real-time Data Analytics and Why is it Important?

Knowledge Hut

Real-time data analytics is an essential innovation that enables companies to act quickly on data. By this year, more than half of business systems would base choices on current context data. This demonstrates the rising significance of real-time analytics architecture in the hectic corporate climate of today.

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How to Use KSQL Stream Processing and Real-Time Databases to Analyze Streaming Data in Kafka

Rockset

With all of these stream processing and real-time data store options, though, also comes questions for when each should be used and what their pros and cons are. I hope by the end you find yourself better informed and less confused about the real-time analytics landscape and are ready to dive in to it for yourself.

Kafka 40
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Azure Data Engineer Interview Questions -Edureka

Edureka

Data entry into PDW is optimized by Polybase, which also supports T-SQL. It allows developers to query external data from supported data stores transparently, regardless of the storage architecture of the external data store. 7) Describe the Azure Synapse Analytics architecture.