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Introducing Compute-Compute Separation for Real-Time Analytics

Rockset

When you deconstruct the core database architecture, deep in the heart of it you will find a single component that is performing two distinct competing functions: real-time data ingestion and query serving. When data ingestion has a flash flood moment, your queries will slow down or time out making your application flaky.

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AI and ML: No Longer the Stuff of Science Fiction

Cloudera

So to improve the speed of data analysis, the IRS worked with the combined technology integrating Cloudera Data Platform (CDP) and NVIDIA’s RAPIDS Accelerator for Apache Spark 3.0. The Roads and Transport Authority (RTA) operating in Dubai wanted to apply big data capabilities to transportation and enhance travel efficiency.

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Building Netflix’s Distributed Tracing Infrastructure

Netflix Tech

In our previous blog post we introduced Edgar, our troubleshooting tool for streaming sessions. An additional implication of a lenient sampling policy is the need for scalable stream processing and storage infrastructure fleets to handle increased data volume. —?which is difficult when troubleshooting distributed systems.

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Data Engineer Learning Path, Career Track & Roadmap for 2023

ProjectPro

Source: Image uploaded by Tawfik Borgi on (researchgate.net) So, what is the first step towards leveraging data? The first step is to work on cleaning it and eliminating the unwanted information in the dataset so that data analysts and data scientists can use it for analysis.

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Streaming SQL Joins in Rockset

Rockset

In that case you can either increase the CPU and RAM resources you use to process the query (in Rockset, that means a larger Virtual Instance) or you can implement the JOIN functionality at data ingestion time. These types of JOIN s allow you to trade the compute used in the query to compute used during ingestion.

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Big Data Fabric Weaves Together Automation, Scalability, and Intelligence

Cloudera

Forrester describes Big Data Fabric as, “A unified, trusted, and comprehensive view of business data produced by orchestrating data sources automatically, intelligently, and securely, then preparing and processing them in big data platforms such as Hadoop and Apache Spark, data lakes, in-memory, and NoSQL.”.

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Big Data Analytics: How It Works, Tools, and Real-Life Applications

AltexSoft

As you now know the key characteristics, it gets clear that not all data can be referred to as Big Data. What is Big Data analytics? Big Data analytics is the process of finding patterns, trends, and relationships in massive datasets that can’t be discovered with traditional data management techniques and tools.