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Glossary of Digital Terminology for Career Relevance

Rocket-Powered Data Science

Analytics: The products of Machine Learning and Data Science (such as predictive analytics, health analytics, cyber analytics). Edge Computing (and Edge Analytics): Industry 4.0: NLG is a software process that transforms structured data into human-language content. See [link]. Industry 4.0

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

AWS Big Data

The solution consists of the following interfaces: IoT or mobile application – A mobile application or an Internet of Things (IoT) device allows the tracking of a company vehicle while it is in use and transmits its current location securely to the data ingestion layer in AWS. For Data source , choose AwsDataCatalog.

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8 data strategy mistakes to avoid

CIO Business Intelligence

Building a successful data strategy at scale goes beyond collecting and analyzing data,” says Ryan Swann, chief data analytics officer at financial services firm Vanguard. RaceTrac is leveraging Alation’s Data Intelligence Platform to centralize data as well as provide self-service analytics for users as needed.

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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

This post provides guidance on how to build scalable analytical solutions for gaming industry use cases using Amazon Redshift Serverless. Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. A data warehouse is one of the components in a data hub.

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Differentiating Between Data Lakes and Data Warehouses

Smart Data Collective

We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes. Both data warehouses and data lakes are used when storing big data. Many people are confused about these two, but the only similarity between them is the high-level principle of data storing. Data Warehouse.

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Delivering Low-latency Analytics Products for Business Success

Rocket-Powered Data Science

I recently saw an informal online survey that asked users what types of data (tabular; text; images; or “other”) are being used in their organization’s analytics applications. The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data.

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11 dark secrets of data management

CIO Business Intelligence

Philosophers and economists may argue about the quality of the metaphor, but there’s no doubt that organizing and analyzing data is a vital endeavor for any enterprise looking to deliver on the promise of data-driven decision-making. And to do so, a solid data management strategy is key.