Derzeit wird viel über das interessante und spannende Leben eines Data Scientist bzw. Data Engineers geschrieben: scheinbar einer der gefragtesten Berufsbilder überhaupt: im Silicon Valley werden Traumgehälter bezahlt; alle reissen sich um die Datenwissenschaftler.
Wie aber sieht sich der Data Engineer selbst? Wie Josh Wille, Clouderas Senior Director of Data Science, im MIT Technology Review meint, stellt sich der Job aus Sicht eines Data Scientist eher ernüchternd dar: ein Grossteil der Zeit muss damit verbracht werden, Daten aufzuräumen und zu strukturieren. Diese eher administrativ zu nennenden Tätigkeiten sind Bedingung für die Kür: den Erkenntnisgewinn.
“I’m a data janitor. That’s the sexiest job of the 21st century,” he says. “It’s very flattering, but it’s also a little baffling.”
Datarella Prediction Engine
Data provides researchers and companies with an in-depth view of aggregation states and the behavior of humans and things. In Big Data projects – as distinguished from classic market research – all data will be collected and stored abundantly and as raw data; without any data handling at this stage. There is no hypothesizing – all insights result from available raw data directly, using data analytics tools. Subsequently used data visualization tools uncover insights for those groups of people with less affinity to data science.
Besides describing actual or historical aggregation states or behavior, it’s possible to predict future behavior if adequate data is available; e.g. how should advertisements be created to generate high conversion rates? Or, what are the key success factors for media contents in order to maximize their reach and audience? These and other questions regarding future success may be answered by using intelligent prediction tools.
The Datarella Prediction Engine has been designed for gathering precise statements regarding future success in the areas of media & advertising, eCommerce, finance, mobility and health. For more information about the DPE please contact us..
DATARELLA – MAKING TECHNOLOGY SOCIALLY RELEVANT
We think that technology should help to make the world a better place. Since this is a super challenging claim, we at Datarella drill it down to the individual – until we can meet that expectation: with our explore app, we help the individual to live a better life. Thus, explore in combination with behavior analytics technology in the background, has a deep impact on the living conditions of the end user and becomes socially relevant.
We engage in ‘The Quantified Self’ – self-tracking via smartphone and wearable apps.
We support businesses and governmental bodies to make the best of data science – applied Big Data – and the quantified self. We offer introductory lectures, workshops, development, and project management from the birth of an idea to the deployment.
THE PRODUCT ‘EXPLORE’
explore is a mobile guide for the end user to improve the quality her life. explore is personalized, interactive and self-learning. The user can subscribe to explore guides – e.g. the ‘Osteo-Guide’ – matching her individual life situation. These guides will help our users to manage their lives better.
At its core, explore is an app which collects data from its user: actively, by asking the user relevant questions based on her behavior; and passively, by collecting the phone’s sensor data.
We develop white label solutions, loyalty tools, and offer insights and analytics from mobile tracking data.
Quantified Self, Mobile Tracking, Data Science, Big Data