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Glossary of Digital Terminology for Career Relevance

Rocket-Powered Data Science

Computer Vision: Data Mining: Data Science: Application of scientific method to discovery from data (including Statistics, Machine Learning, data visualization, exploratory data analysis, experimentation, and more). NLG is a software process that transforms structured data into human-language content.

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Quantitative and Qualitative Data: A Vital Combination

Sisense

When these systems connect with external groups — customers, subscribers, shareholders, stakeholders — even more data is generated, collected, and exchanged. The result, as Sisense CEO Amir Orad wrote , is that every company is now a data company. This is quantitative data. or “how often?”

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Transforming Big Data into Actionable Intelligence

Sisense

However, when investigating big data from the perspective of computer science research, we happily discover much clearer use of this cluster of confusing concepts. As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data.

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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. The ingestion approach is not in scope of this post.

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

AWS Big Data

It includes business intelligence (BI) users, canned and interactive reports, dashboards, data science workloads, Internet of Things (IoT), web apps, and third-party data consumers. Popular consumption entities in many organizations are queries, reports, and data science workloads.

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Building Better Data Models to Unlock Next-Level Intelligence

Sisense

We’re going to nerd out for a minute and dig into the evolving architecture of Sisense to illustrate some elements of the data modeling process: Historically, the data modeling process that Sisense recommended was to structure data mainly to support the BI and analytics capabilities/users.

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3 Takeaways from Gartner’s 2018 Data and Analytics Summit

DataRobot Blog

In Rita Sallam’s July 27 research, Augmented Analytics , she writes that “the rise of self-service visual-bases data discovery stimulated the first wave of transition from centrally provisioned traditional BI to decentralized data discovery.” We agree with that.