The open source technology market is huge. It fuels 1 million unique projects today, and opens up massive opportunities for small and large enterprises alike. It means small companies can deploy technologies in a cost-effective manner, and large enterprises have the means to scale; as John Gallaugher points out, Google has over 1.4 million servers; without open sourced technology, licensing costs on that scale would be huge. Yet, open source is a multi-billion dollar industry. For technology that’s ostensibly free to use and develop, where is the money coming from? In this installment of Understanding Big Data, we’ll be looking at some of the leading open source providers- and how much you can actually get for free. The Apache Foundation The Apache Foundation have been providing users with community-led, open-source solutions for…
KPMG and Imperial College London yesterday announced the launch of a new initiative that aims to meet the excess demand for data scientists. With an investment of £20m from KPMG, the two organisations will open the “KPMG Centre for Advanced Business Analytics”, where the focus of the project will be on five key areas: analysis of business capital, growth opportunities, people, operations and resilience. “Our clients are facing the enormity and complexity of big-data and our partnership with Imperial will help our clients meet this challenge. The fact is that one in five of the UK’s largest companies now measure the value of corporate data on their balance sheets,” said Alwin Magimay, KPMG’s UK head of digital and analytics. “Businesses realise that finding better ways of analysing data is the…
PredictionIO, a company aiming to become the “MySQL of prediction”, has just raised $2.5 million in seed funding to open source machine learning, and allow developers to build predictive applications with just a few lines of code. Investors in the seed round include Azure Capital, QuestVP, CrunchFund and Stanford. As well as receiving funding from Stanford, PredictionIO are a part of the Stanford-affiliated StartX Accelerator Summer roster, receiving $100,000 of resources from the accelerator’s impressive portfolio of partners and guidance from over 200 affiliated serial entrepreneurs. With the impressive funding round, PredictionIO are fuelling their grand ambition- to be the machine learning server behind every application. Although they’re not the first to offer to offer machine-learning-as-a-service (companies like Google Prediction and Skytree have that one covered), their unique selling point…
Apple and IBM on Tuesday announced a “landmark” partnership to merge their respective strengths to tackle the enterprise market. The deal, which was announced after Tuesday’s market’s close, will see IBM’s big data capabilities combine with Apple’s user-friendly iOS operating system. The two companies will work together on developing more than 100 software programmes for business customers to use on their iPad’s and iPhone’s, ultimately helping Apple become more attractive to corporations, while also strengthening IBM’s leadership in business software. “iPhone and iPad are the best mobile devices in the world and have transformed the way people work with over 98 percent of the Fortune 500 and over 92 percent of the Global 500 using iOS devices in their business today,” said Tim Cook, Apple’s CEO. “For the first time…
We met with Adam Drake to hear his thoughts on Data Science and the qualities a Data Scientist should have. Adam is currently the Chief Data Scientist and Director of Engineering for Zanox, Europe’s largest affiliate network. He has been in technology roles for over 17 years in a variety of industries, including online marketing, financial services, healthcare, and oil and gas. His background is in Applied Mathematics, and his interests include online learning systems, high-frequency/ low-latency data processing systems, recommender systems, distributed systems, and functional programming. Follow @DataconomyMedia Interested in more content like this? Sign up to our newsletter, and you wont miss a thing!…
Warning: The following post contains moments of wild speculation. You have been warned. Right now is an interesting moment in the history of civilization. In the past technology has molded itself to the needs of society, but we’ve passed that point. In the last 15 years we’ve started to see society molding itself to technology instead. TL;DR Distributed proof of ownership, anonymity, crowdfunding, the subscription economy, and location-based services–taken together, at the intersections–are going to rock your world. We’ve reached a saturation point where technology is so pervasive–mostly due to smartphones, little computers we carry around with us–that what used to be wild speculation now seems just around the corner. Society has pretty much absorbed the change inherent in a global network connecting every person to every other person, and…
IEEE, the “world’s largest professional association for the language of technology”, have released an interactive ranking of programming languages. In the overall list, as well as many of the sub-rankings, Java emerges as the victor. The IEEE blog details how they went about creating their definitive rankings. “Starting from a list of over 150 programming languages gathered from GitHub, we looked at the volume of results found on Google when we searched for each one in the pattern “X programming” where “X” is the name of the language. We filtered out languages if they had a very low number of search results and then went through the list by hand to identify the most interesting languages. We labeled each language according to its use in Web, mobile, enterprise/desktop, or embedded…
The open source technology market is huge. It fuels 1 million unique projects today, and opens up massive opportunities for small and large enterprises alike. It means small companies can deploy technologies in a cost-effective manner, and large enterprises have the means to scale; as John Gallaugher points out, Google has over 1.4 million servers; without open sourced technology, licensing costs on that scale would be huge. Yet, open source is a multi-billion dollar industry. For technology that’s ostensibly free to use and develop, where is the money coming from? In this installment of Understanding Big Data, we’ll be looking at some of the leading open source providers- and how much you can actually get for free. The Apache Foundation The Apache Foundation have been providing users with community-led, open-source solutions for…
KPMG and Imperial College London yesterday announced the launch of a new initiative that aims to meet the excess demand for data scientists. With an investment of £20m from KPMG, the two organisations will open the “KPMG Centre for Advanced Business Analytics”, where the focus of the project will be on five key areas: analysis of business capital, growth opportunities, people, operations and resilience. “Our clients are facing the enormity and complexity of big-data and our partnership with Imperial will help our clients meet this challenge. The fact is that one in five of the UK’s largest companies now measure the value of corporate data on their balance sheets,” said Alwin Magimay, KPMG’s UK head of digital and analytics. “Businesses realise that finding better ways of analysing data is the…
PredictionIO, a company aiming to become the “MySQL of prediction”, has just raised $2.5 million in seed funding to open source machine learning, and allow developers to build predictive applications with just a few lines of code. Investors in the seed round include Azure Capital, QuestVP, CrunchFund and Stanford. As well as receiving funding from Stanford, PredictionIO are a part of the Stanford-affiliated StartX Accelerator Summer roster, receiving $100,000 of resources from the accelerator’s impressive portfolio of partners and guidance from over 200 affiliated serial entrepreneurs. With the impressive funding round, PredictionIO are fuelling their grand ambition- to be the machine learning server behind every application. Although they’re not the first to offer to offer machine-learning-as-a-service (companies like Google Prediction and Skytree have that one covered), their unique selling point…
Apple and IBM on Tuesday announced a “landmark” partnership to merge their respective strengths to tackle the enterprise market. The deal, which was announced after Tuesday’s market’s close, will see IBM’s big data capabilities combine with Apple’s user-friendly iOS operating system. The two companies will work together on developing more than 100 software programmes for business customers to use on their iPad’s and iPhone’s, ultimately helping Apple become more attractive to corporations, while also strengthening IBM’s leadership in business software. “iPhone and iPad are the best mobile devices in the world and have transformed the way people work with over 98 percent of the Fortune 500 and over 92 percent of the Global 500 using iOS devices in their business today,” said Tim Cook, Apple’s CEO. “For the first time…
Warning: The following post contains moments of wild speculation. You have been warned. Right now is an interesting moment in the history of civilization. In the past technology has molded itself to the needs of society, but we’ve passed that point. In the last 15 years we’ve started to see society molding itself to technology instead. TL;DR Distributed proof of ownership, anonymity, crowdfunding, the subscription economy, and location-based services–taken together, at the intersections–are going to rock your world. We’ve reached a saturation point where technology is so pervasive–mostly due to smartphones, little computers we carry around with us–that what used to be wild speculation now seems just around the corner. Society has pretty much absorbed the change inherent in a global network connecting every person to every other person, and…
IEEE, the “world’s largest professional association for the language of technology”, have released an interactive ranking of programming languages. In the overall list, as well as many of the sub-rankings, Java emerges as the victor. The IEEE blog details how they went about creating their definitive rankings. “Starting from a list of over 150 programming languages gathered from GitHub, we looked at the volume of results found on Google when we searched for each one in the pattern “X programming” where “X” is the name of the language. We filtered out languages if they had a very low number of search results and then went through the list by hand to identify the most interesting languages. We labeled each language according to its use in Web, mobile, enterprise/desktop, or embedded…
