Just because someone might be an engineer for Google, or a UX Designer for Apple, doesn’t mean their interests and hobbies end there, although while working 80 hours per week for said company may make exploring other activities and passions difficult. So what happens when engineers leave large companies, such as Apple, to spearhead their own initiative, utilizing all they had learned from the multinational technology company? It seems that many apply their years of acquired knowledge to endeavors they had taken a hiatus from upon working for larger companies.
Once an engineer for Apple, Alex Fishman, now uses his Big Data skills for his wine app – Delectable – founded and developed in 2012. Big Data can aid in organizing, filtering, and concluding all the confusing identification process and information that is commonly associated with wine. The app not only is able to sort through data regarding preference and specific lexicon used by connoisseurs and novices, but it can also show patterns and changes among wine drinkers within different quarters throughout the years. Computation systems and services such as Big Data, Machine Learning and Cloud strategies have a broad range of utility in other fields apart from strictly technology focused. Applying such services to social, cultural, and human research has been advantageous for sorting out large amounts of data.
For those that aren’t data scientists recently leaving a cushy job at Apple, yet still have a creative idea to contribute to the app world, are now in luck with the recent demand and development of alternative options for non-data scientists. Big Data applications have started to enter the market as of recent to provide the resources necessary for less technically savvy entrepreneurs to obtain quality and relevant information for precise data gathering. These apps allow novices to make their data-driven decisions on their own, without a data expert, reducing time, money, and specialization.
Both big data applications, as well as specialists, can significantly help with bringing precision to decision making and trend tracking. Machine learning in particular can also yield sound, conclusive recommendations. Different from more antiquated research techniques where information was collected, graphed, and then analyzed by humans to find patterns to make suggestions, Big Data and Machine Learning have the ability to draw from a more expansive pool of information in a shorter period of time, for more accurate, nuanced proposals.
Don’t worry, Big Data and Machine Learning are not replacing humans, just yet, since machines need humans to take action on the information founded. Only humans at the moment have the power to circulate the recommendations suggested through Big Data collections.
Reducing human error, while maintaining the human voice and final interpretation, is what Big Data can, and does, accomplish. Accuracy is imperative when more and more new found entrepreneurs with innovative ideas want to launch utility apps. Utility is only resourceful with the right information and knowledge. Humans have always been limited in the realm of precision. Therefore, whether you are a technocrat – like Delectable’s Alex Fishman – or a novice in data collection, Big Data and Machine Learning is becoming a necessary service to create a quality, reliable, and culturally relevant app.