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The arrival of tools for the real-time analysis of Big Data has brought with it many advantages for companies that need to deal with the constant mass entry of data and extract real value from this flow of information.
Python is one of the most-used languages in data science, largely because it is a commonly-used syntax with a very short learning curve. Developers can use specific libraries for graphics.
JavaScript applied at client and server level enables developers to tackle full-stack web app development projects. MongoDB, Express, AngularJS and Node.js (MEAN) are a full development stack.
Samsung and Google have launched two new software development kits (SDKs) and financial incentives for developers in order to improve their user interfaces and smartwatch applications, all with a single goal in mind: to bring down the Apple Watch.
Esta nueva solución de Google es especial para las compañías que necesitan la gestión y el análisis de datos en sectores como el de servicios financieros, energía, biomedicina, telecomunicaciones o publicidad online.
Graph databases help to find relationships between data and extract their true value. One of the best known is Neo4j, which is a service implemented in Java.
All companies have so many easy-to-use data analysis solutions at their disposal, that it would be a sin not knowing what will happen in six months
Apple's idea is to provide a tool to the research community that makes it possible to launch applications that offer added value thanks to the collected data.
If there is a company that is betting on cognitive computing, that is IBM. The latest milestone in their research on Artificial Intelligence is IBM Watson Personality Insights, a tool that very well could be your psychologist.
Discover how to make predictions through data with this webinar carried on by Andrés González, Responsible of Big Data and Data prediction solutions in Clever Task.
