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What is a data scientist? A key data analytics role and a lucrative career

CIO Business Intelligence

Data scientists are analytical data experts who use data science to discover insights from massive amounts of structured and unstructured data to help shape or meet specific business needs and goals. Data scientist salary. Semi-structured data falls between the two.

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The Future Is Hybrid Data, Embrace It

Cloudera

In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB. The future is hybrid data, embrace it.

IT 108
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Unstructured data management and governance using AWS AI/ML and analytics services

AWS Big Data

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Unstructured information may have a little or a lot of structure but in ways that are unexpected or inconsistent. Text, images, audio, and videos are common examples of unstructured data.

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The Future Is Hybrid Data, Embrace It

CIO Business Intelligence

In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB. But this is not your grandfather’s big data.

IT 78
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Use Amazon Athena to query data stored in Google Cloud Platform

AWS Big Data

As customers accelerate their migrations to the cloud and transform their businesses, some find themselves in situations where they have to manage data analytics in a multi-cloud environment, such as acquiring a company that runs on a different cloud provider. For instructions, refer to Setting up databases and tables in AWS Glue.

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Data architecture strategy for data quality

IBM Big Data Hub

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Perform data quality monitoring based on pre-configured rules.

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The Madness of Data (and analytics) Governance

Andrew White

The client had recently engaged with a well-known consulting company that had recommended a large data catalog effort to collect all enterprise metadata to help identify all data and business issues. Modern data (and analytics) governance does not necessarily need: Wall-to-wall discovery of your data and metadata.