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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). NLG is a software process that transforms structured data into human-language content. Algorithm: A set of rules to follow to solve a problem or to decide on a particular action (e.g.,

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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.

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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.

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Delivering Low-latency Analytics Products for Business Success

Rocket-Powered Data Science

The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data. The ease with which such structured data can be stored, understood, indexed, searched, accessed, and incorporated into business models could explain this high percentage.

Analytics 165
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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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Big Data Fabric Weaves Together Automation, Scalability, and Intelligence

Cloudera

Today’s data landscape is characterized by exponentially increasing volumes of data, comprising a variety of structured, unstructured, and semi-structured data types originating from an expanding number of disparate data sources located on-premises, in the cloud, and at the edge.

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Cloudera + Hortonworks, from the Edge to AI

Cloudera

In the data center and in the cloud, there’s a proliferation of players, often building on technology we’ve created or contributed to, battling for share. The opportunity has only grown with the advent of practical Internet of Things applications. In the meantime, each of us also has unique product offerings.