Data Science as business decisioning tool
Multidisciplinary field with a focus on predicting future outcomes while using past and current data is called Data Science. In order to make better decisions in the future, man utilized data with combination of scientific methodologies, processes and algoritms and implemented Data Science.
Mathematical formulas were out there for decades, but now, when we are flooded with so much data, it was normal to quantify those unstructured data and translate them into useful information. And that is how we included data science in business.
Using cuting-edge technology we have evolved data processing so we can use those information to change the direction of current work or organize business in a better way. It can help with customer targeting, changing internal processes or speed up selection process.
With our partners, we have developed an AI driven product for knowledge management. Combined effort of top software development experts, university professors and innovators have brought us to new algorithms in Machine Learning.
The main challenge with implementing Data Science in companies is the expensiveness in identification and interpreting large amounts of data as it can be complex and time-consuming. It’s surely worth the effort since the results contributes to competitive advantages like new opportunities or new strategies which are dominance benefits of any organization.
The Data Science team is usually consisted of computer engineers, mathematicians, statistics and domain experts from the field that is processed.
Wednesday is our time for ICodeFactory learning sessions. Last week we hosted a guest lecturer to tell us more about award winning application of artificial intelligence in agriculture. This solution combines results from a number of scientific fields and it is based on the development of meteorological indicators with advanced machine learning and artificial intelligence algorithms. Amazing, right?
Data-driven decisions are already part of our lives, whether we are aware of it or not.
In the future we will meet much more data science technologies and tools that will lead us to better results, products or services. Stay tuned.