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Understanding Big Data

Big DataData ScienceData Science 101FeaturedUnderstanding Big Data

If you are new to the field, Big Data can be intimidating! With the basic concepts under your belt, let’s focus on some key terms to impress your date, your boss, your family, or whoever. Let’s get started: Algorithm: A mathematical formula or statistical process used to perform an analysis of

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BI & AnalyticsData ScienceResourcesUnderstanding Big Data

There’s a part of data science that you rarely hear about: the deployment and production of data flows.  Everybody talks about how to build models, but little time is spent discussing the difficulties of actually using those models. Yet these production issues are the reason many companies fail to see

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Artificial IntelligenceData ScienceEventsMachine LearningUnderstanding Big Data

Ajit Jaokar is a leading expert working at the intersection of Data Science, IoT, AI, Machine Learning, Big Data, Mobile, and Smart Cities. He teaches IoT and Data Science at Oxford and also is a director of Smart Cities Lab in Madrid. Ajit’s work involves applying machine learning techniques to

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Data ScienceData Science 101Understanding Big Data

Competent analysis is not only about understanding statistics, but about implementing the correct statistical approach or method. In this brief article I will showcase some common statistical blunders that we generally make and how to avoid them. To make this information simple and consumable I have divided these errors into

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Big DataData ScienceUnderstanding Big Data

Social networks, in one form or another, have existed since people first began to interact. Indeed, put two or more people together and you have the foundation of a social network. It is therefore no surprise that, in today’s Internet-everywhere world, online social networks have become entirely ubiquitous. Within this

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Big DataTech TrendsUnderstanding Big Data

This is Part 2 of Data Strategy series discussing “How To” following Part 1 of Data Strategy that dealt with “5 ‘W’s of Data Strategy”.  Strategy is about doing the right things and tactics is about doing things right. Data Strategy is about doing the right things to distill Data

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Big DataData ScienceData Science 101Understanding Big Data

One of the coolest things about being a data scientist is being industry-agnostic. You could dive into gigabytes or even petabytes of data from any industry and derive meaningful interpretations that may catch even the industry insiders by surprise. When the global financial crisis hit the American market in 2008, few

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Big DataTech TrendsUnderstanding Big Data

I am sure you’ve come across many 2016 statistics on Data and Analytics as I have. I’d like to use couple of statistics from IDG’s Enterprise 2016 Data & Analytics Research to start this article. As per their research, 78% of enterprises agree that data strategy, collection & analysis of big

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Metadata
Big DataData ScienceUnderstanding Big Data

Metadata. You may have heard the term before, and may have asked yourself either “what is metadata” or “why is it as important as data?” This article will be an attempt to clear up those two subjects. As this can often be quite dense, let’s jump right in! Metadata can

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Big DatainfographicsUnderstanding Big Data

Another year, another stellar run for the tech world’s darling – data. Big Data analytics and Business Intelligence are both fueling the growth of Enteprises all over the world, and also getting heavy investment within the Big Data market. The ability to gain insights laying dormant in unstructured data is enabling organizations to compete and

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