Dataconomy https://dataconomy.com Bridging the gap between technology and business Thu, 08 Nov 2018 17:22:29 +0000 en-US hourly 1 https://wordpress.org/?v=4.9.8 Kubernetes Meets Big Data https://dataconomy.com/2018/11/kubernetes-meets-big-data/ https://dataconomy.com/2018/11/kubernetes-meets-big-data/#respond Thu, 08 Nov 2018 17:22:29 +0000 https://dataconomy.com/?p=20497

Organizations yearn order and simplicity over chaos and confusion, but the data-driven era we live in challenges these desires on a daily basis. Seemingly every day, massive amounts of transactional and streaming data is being introduced into enterprises. This data must be collected, deciphered, shared, and acted upon. Cloud-native technologies

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5 Startups & Scaleups To Watch Out For at DN18 https://dataconomy.com/2018/11/data-natives-dn18-startups-scaleups/ https://dataconomy.com/2018/11/data-natives-dn18-startups-scaleups/#respond Thu, 08 Nov 2018 13:06:41 +0000 https://dataconomy.com/?p=20501

An insider tip: if you’re looking for the real inside track on tech innovation at a conference, look to the startups. Undoubtedly the larger companies have the resources and brainpower to fuel the innovations of tomorrow, but many of the nascent ideas which will revolutionise the ways we live and

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How Deep Learning can solve the problem of global climate change https://dataconomy.com/2018/11/how-deep-learning-can-solve-the-problem-of-global-climate-change/ https://dataconomy.com/2018/11/how-deep-learning-can-solve-the-problem-of-global-climate-change/#respond Wed, 07 Nov 2018 15:07:36 +0000 https://dataconomy.com/?p=20486

With the help of a use case, Dr Patrick Vetter, Head of Competence Center Data Science at Supper and Supper GMBH explains how a deep learning methodology can locate and segment wind turbines on satellite imagery. As a pioneer in fighting global climate change, Germany is increasingly investing in renewable

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Machine Learning with a twist: How trivial labels can be used to predict policy changes https://dataconomy.com/2018/11/machine-learning-with-a-twist-how-trivial-labels-can-be-used-to-predict-policy-changes/ https://dataconomy.com/2018/11/machine-learning-with-a-twist-how-trivial-labels-can-be-used-to-predict-policy-changes/#respond Thu, 01 Nov 2018 11:41:36 +0000 https://dataconomy.com/?p=20479

A clever algorithm that has digested seven decades’ worth of articles in China’s state-run media is now ready to predict its future policies. The research design of this “crystal ball” can also be applied to tackling a variety of other problems. Supervised learning — the most developed form of Machine

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Best Methods To Overcome Mobile App Usability Problems https://dataconomy.com/2018/10/best-methods-to-overcome-mobile-app-usability-problems/ https://dataconomy.com/2018/10/best-methods-to-overcome-mobile-app-usability-problems/#respond Wed, 31 Oct 2018 15:14:52 +0000 https://dataconomy.com/?p=20475

There is nothing that turns off users as much as bad UX. Your mobile app should provide a seamless user experience if you want it to be one of the most successful apps. Everything from the moment your users download the app to the moment they check out needs to

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Ethics to Ecotech: 5 Unmissable Talks At Data Natives 2018 https://dataconomy.com/2018/10/data-natives-2018-best-talks/ https://dataconomy.com/2018/10/data-natives-2018-best-talks/#respond Thu, 25 Oct 2018 13:20:56 +0000 https://dataconomy.com/?p=20466

The pace of life and industry is accelerating at an unprecedented rate. Interconnected tech, inconceivably fast data processing capabilities and sophisticated methods of using this data all mean that we’re living in fast-forward. The Data Natives Conference 2018 will be exploring life at an accelerated pace, and what rapid innovation

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Three questions you need to answer to succeed in data-driven projects https://dataconomy.com/2018/10/three-questions-you-need-to-answer-to-succeed-in-data-driven-projects/ https://dataconomy.com/2018/10/three-questions-you-need-to-answer-to-succeed-in-data-driven-projects/#respond Tue, 23 Oct 2018 13:10:50 +0000 https://dataconomy.com/?p=20459

The success of data-driven projects has quite a few challenges and barriers. Here is a look at how you could overcome them by simply asking yourself three questions. Data has become probably the most valuable asset that companies could have nowadays. It can give you insights into your customers’ behaviour

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How Blockchain is Boosting Renewable Energy https://dataconomy.com/2018/10/how-blockchain-is-boosting-renewable-energy/ https://dataconomy.com/2018/10/how-blockchain-is-boosting-renewable-energy/#respond Mon, 22 Oct 2018 16:23:08 +0000 https://dataconomy.com/?p=20455

The explosion in renewable energy projects on blockchain is already promising—there are 122 startups operating in the space, with nearly half launching since 2017. More impressively, these startups have raised over $320 billion between the second quarter of 2017 and the first of 2018. Electricity is undoubtedly one of the

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Is your Precision Medicine AI ready for the Bio-Psycho-Socio-Cultural Patient? https://dataconomy.com/2018/10/is-your-precision-medicine-ai-ready-for-the-bio-psycho-socio-cultural-patient/ https://dataconomy.com/2018/10/is-your-precision-medicine-ai-ready-for-the-bio-psycho-socio-cultural-patient/#respond Fri, 19 Oct 2018 15:50:22 +0000 https://dataconomy.com/?p=20443

The data necessary to account for every aspect of our human complexity poses significant challenges to health AI systems. There’s certainly no way around data science to get a hold of it – but don’t you count physicians out too soon! Precision Medicine bears the promise to bring highly individualized

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The cart before the horse in data-science projects: back to basics https://dataconomy.com/2018/10/the-cart-before-the-horse-in-data-science-projects-back-to-basics/ https://dataconomy.com/2018/10/the-cart-before-the-horse-in-data-science-projects-back-to-basics/#respond Wed, 17 Oct 2018 16:34:01 +0000 https://dataconomy.com/?p=20428

The cart before the horse? What are we talking about: You have the perfect scenario in front of you. You or your team just learnt about an exciting way to analyse data, found a new data-source that looks very promising, or were impressed by a new data visualisation tool. Understandably,

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