BIg Data - An introduction

Data science is the extraction of knowledge from large volumes of data. World-class data science teams are able to extract and connect many different types of structured and unstructured types of data using a variety of different fields such as mathematics, statistics, information theory, computer science and domain-specific knowledge from areas such as marketing, finance, engineering, chemistry and medicine to build intelligent and self-learning decision models that can open significant new revenue streams, superior market insight, production efficiencies and many other kinds of competitive advantages. The recognition of patterns in data is further used to develop powerful predictive models to anticipate developments and align business and production processes upon them. 

Big Data is the end of the era of pure gut feeling.
— Ushan Ganeshananthan | CEO, KIANA Systems

While data science is no news to scientists, the power of its application in business has only become evident over the course of the last 25 years, as worldwide data volume and methods of data collection have skyrocketed - providing for the first time a universal basis for many businesses from across all sectors to consider the advantages of data analysis and machine learning along their value chain. Big data has become the ultimate technology buzzword for a reason. Top managers and engineers worldwide have not only understood that complementing gut feeling with certitude can go a long way. Creating new business models worldwide data has developed from a side product to the actual object of interest. It is no surprise that the vast majority of companies by now have started to invest into Big Data.

KIANA Systems has been a pioneer in the fields of data mining and big data analytics as well as in the development of machine learning and artificial intelligence systems since 2001. We are one of the leading data analytics firms in Europe. We help our clients define and pursue a data-driven strategy, identify internal and external value streams and connect the existing IT landscape with the latest data analytics and machine learning technologies to create high-impact projects and long-term solutions. 


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