BIG DATA TERMS EVERYONE SHOULD KNOW

75 BIG DATA TERMS EVERYONE SHOULD KNOW Published by  RAMESH DONTHA · JULY 21, 2017 on Dataconomy.com  This article is a continuation of my first article, 25 Big Data terms everyone should know. Since it got such an overwhelmingly positive response, I decided to add an extra 50 terms to the list.  Just to give you a quick recap, I covered the following terms in my first article: Algorithm, Analytics, Descriptive analytics, Prescriptive analytics, Predictive analytics, Batch processing, Cassandra, Cloud computing, Cluster computing, Dark Data, Data Lake, Data mining, Data Scientist, Distributed file system, ETL, Hadoop, In-memory computing, IOT, Machine learning, Mapreduce, NoSQL, R, Spark, Stream processing, Structured Vs. Unstructured Data. Now let’s get on with 50 more big data terms. Apache Software Foundation Read More …

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DATA SCIENCE SKILLS, AND HOW TO LEARN THEM

TOP 10 DATA SCIENCE SKILLS, AND HOW TO LEARN THEM Published by  EILEEN MCNULTY · DECEMBER 25, 2014 on Dataconomy.com One of most popular posts this year came from Ferris Jumah, a data scientist at LinkedIn, who mapped the most popular skills of data scientists by scraping LinkedIn profile data. One of the common comments amongst data scientists who came across this post- as with most of our posts focused around data science skillsets- was “Surely, you can’t expect data scientists to have all these skills?” Naturally, we don’t- every data science role involves a particular comibination of some of the skills, and anyone who had mastered all of the programming languages listed alone would be some sort of computing demi-God. Read More …

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BANKS AND FINTECHS

BANKS AND FINTECHS, INSTEAD OF BANKS VERSUS FINTECHS  JUAN SALAZAR · APRIL 21, 2017 on Dataconomy.com In 2016, global market uncertainty seemed to make investors somewhat more cautious, thanks to the results of the votes in the UK and the USA. However, fintech’s stellar run did not come to a halt. According to the February report by KPMG, venture capital investment in the space rose 7%, totalling $13.6 billion. Overall investment in fintechs hit $24.7B, thanks to evolving technologies, and the success of companies focusing strongly on providing outstanding user experiences. The only one among all regions, Europe saw its fintech venture investment grow in volume. It grew from 230 financings in 2015 to 242 in 2016. While 2016 almost amounted to Read More …

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INTRO TO MACHINE LEARNING

INTRO TO MACHINE LEARNING: 10 ESSENTIAL ALGORITHMS FOR MACHINE LEARNING ENGINEERS  JAMES LE · APRIL 21, 2017 Dataconomy.com It is no doubt that the sub-field of machine learning / artificial intelligence has increasingly gained more popularity in the past couple of years. As Big Data is the hottest trend in the tech industry at the moment, machine learning is incredibly powerful to make predictions or calculated suggestions based on large amounts of data. Some of the most common examples of machine learning are Netflix’s algorithms to make movie suggestions based on movies you have watched in the past or Amazon’s algorithms that recommend books based on books you have bought before. So if you want to learn more about machine learning, Read More …

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Online Big Data Courses

Data Science 101 10 Online Big Data Courses Eileen McNulty · September 25, 2014 on Dataconomy.com 22 Comments 10 68.2k 17 The explosion of hype around the term “big data” ushered in a rabid desire in companies big and small to get their hands on employees with a data science skill set. For evidence, you need look no further than Indeed’s graph of the number of big data-related job postings: If you already have the skill set to enter the world’s sexiest profession, it’s a great time to be alive. For those with enough money and expendable time, there’s always the option to go back to school. But for the rest of us, hope is not lost; thanks the rise of Read More …

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