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Understanding Big Data

BI & AnalyticsUnderstanding Big Data

In our cartographic overview of the big data ecosystem, we stated a Big Data environment should allow you to store, process, analyse and visualise data. Thus far in the “Understanding Big Data” series, we’ve been breaking down the ecosystem into composite parts, focusing on software which specifically focuses one or

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Data Science 101FeaturedUnderstanding Big Data

‘SQL is outdated’. ‘RDBMS can no longer meet businesses’ data management needs’. ‘New database technologies like NoSQL are the solution for today’s enterprises’. We hear statements like these alot, both inside and outside the database technologies industry. But are they accurate? Is SQL a thing of the past, and are

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Machine LearningUnderstanding Big Data

In 1959, Arthur Samuel defined machine learning as a “Field of study that gives computers the ability to learn without being explicitly programmed”. It’s a science of algorithms and automation; the algorithms “learn” from the dataset, identifying patterns or classifying trends for instance, and then automates output- whether that’s sorting

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BI & AnalyticsUnderstanding Big Data

Follow @DataconomyMedia So far in the “Understanding Big Data” series, we’ve looked at what “big data” actually means; what the big data landscape looks like; and some of the infrastructural approaches you might look into when you’re taking the first tentative steps away from the data warehouse. In this edition,

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Understanding Big Data

Follow @DataconomyMedia It’s been suggested that “Hadoop” has become a buzzword, much like the broader signifier “big data”, and I’m inclined to agree. It could certainly be seen to fit Dan Ariely’s analogy of “Big data” being like teenage sex: “everyone talks about it, nobody really knows how to do

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Understanding Big Data

Infrastructure is the cornerstone of Big Data architecture. Possessing the right tools for storing, processing and analysing your data is crucial in any Big Data project. In last installment of “Understanding Big Data”, we provided a general overview of all of the technologies in the Big Data landscape. In this

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Data ScienceUnderstanding Big Data

This article was first posted by Carla Gentry here. Carla is currently owner and data scientist at Analytical Solution.She has worked in the field of data science for over 15 years, and has worked for Fortune 100 and 500 companies such as Johnson & Johnson, Hershey, Kraft, Kellogg’s and Firestone. She

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Data ScienceUnderstanding Big Data

The on-going Big Data media hype stirs up a lot of passionate voices. There are naysayers (“it is nothing new“), doomsayers (“it will disrupt everything”), and soothsayers (e.g., Predictive Analytics experts). The naysayers are most bothersome, in my humble opinion. (Note: I amnot talking about skeptics, whom we definitely and desperately need during any period of maximized

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Data ScienceUnderstanding Big Data

For the uninitiated, the Big Data landscape can be daunting. The vast proliferation of technologies in this competitive market mean there’s no single go-to solution when you begin to build your Big Data architecture. In this series of articles, we will examine the Big Data ecosystem, and the multivarious technologies

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BI & AnalyticsData ScienceUnderstanding Big Data

By now, it’s almost impossible to not have heard the term Big Data- a cursory glance at Google Trends will show how the term has exploded over the past few years, and become unavoidably ubiquitous in public consciousness. But what you may have managed to avoid is gaining a thorough

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