Remove Data Analytics Remove Data Processing Remove Enterprise Remove Structured Data
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How Will The Cloud Impact Data Warehousing Technologies?

Smart Data Collective

sThe recent years have seen a tremendous surge in data generation levels , characterized by the dramatic digital transformation occurring in myriad enterprises across the industrial landscape. The amount of data being generated globally is increasing at rapid rates. Big data and data warehousing.

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Gain insights from historical location data using Amazon Location Service and AWS analytics services

AWS Big Data

Data analytics – Business analysts gather operational insights from multiple data sources, including the location data collected from the vehicles. Query the data using Athena Athena is a serverless, interactive analytics service built to analyze unstructured, semi-structured, and structured data where it is hosted.

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New Software Development Initiatives Lead To Second Stage Of Big Data

Smart Data Collective

Unstructured data lacks a specific format or structure. As a result, processing and analyzing unstructured data is super-difficult and time-consuming. Semi-structured. Semi-structured data contains a mixture of both structured and unstructured data. Real-Time Data Processing and Delivery.

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The new challenges of scale: What it takes to go from PB to EB data scale

CIO Business Intelligence

Enterprises can handle much higher data volumes on a unified platform spanning multiple use cases with the scalability to handle the storage and processing of large volumes of data – far beyond petabytes. Consider data types. This is why Cloudera’s single platform solution is so effective.

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

With QuickSight, you can embed dashboards to external websites and applications , and the SPICE engine enables rapid, interactive data visualization at scale. Data warehouse Data warehouses are efficient in consolidating structured data from multifarious sources and serving analytics queries from a large number of concurrent users.

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The Data Behind Tokyo 2020: The Evolution of the Olympic Games

Sisense

Not only does it support the successful planning and delivery of each edition of the Games, but it also helps each successive OCOG to develop its own vision, to understand how a host city and its citizens can benefit from the long-lasting impact and legacy of the Games, and to manage the opportunities and risks created.