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What is a data lakehouse? Combining data lakes and warehouses for the best of both worlds

Dynatrace

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. A data lakehouse, therefore, enables organizations to get the best of both worlds.

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Redis® Monitoring Strategies for 2024

Scalegrid

To monitor Redis® instances effectively, collect Redis metrics focusing on cache hit ratio, memory allocated, and latency threshold. This ensures each Redis® instance optimally uses the in-memory data store and aligns with the operating system’s efficiency.

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What is a Distributed Storage System

Scalegrid

It utilizes methodologies like DStore, which takes advantage of underused hard drive space by using it for storing vast amounts of collected datasets while enabling efficient recovery processes. These systems enable vast amounts of data to be spread over multiple nodes, allowing for simultaneous access and boosting processing efficiency.

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Laravel For Healthcare App Development: Why So Obvious?

Tech News Gather

These apps offer several benefits for both patients and providers including convenience, accessibility, efficiency, and cost-effectiveness. Healthcare web apps improve the quality and efficiency of healthcare services as they bring down costs, and improve patient satisfaction and positive engagement.

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The Future in Visual Computing: Research Challenges

ACM Sigarch

As a result of these different types of usages, a number of interesting research challenges have emerged in the domain of visual computing and artificial intelligence (AI). Advantages can be harnessed in terms of execution efficiency as well as realizing immersive VR usages for example. Quality vs Bandwidth.

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Upcoming of the learned data structures

Abhishek Tiwari

Jeff is a Google Senior Fellow in the Google Brain team and widely known as a pioneer in artificial intelligence (AI) and deep learning community. Apart from indexes, super efficient sorting and join operations are some major areas come to my mind with immediate benefits of using learned data structure.

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5 data integration trends that will define the future of ETL in 2018

Abhishek Tiwari

It offers reliability and performance of a data warehouse, real-time and low-latency characteristics of a streaming system, and scale and cost-efficiency of a data lake. In contrast, Alluxio a middleware for data access - think Alluxio storage layer as fast cache. Machine learning meets data integration.