From personalized education, to cleaning the oceans, or transforming healthcare – data science is poised to continue revolutionizing how businesses operate by producing actionable insights from data. Digitalization has made it easier for companies to collect data about their internal processes, but this data can’t be used to its full potential without data scientists.
But what exactly is data science and how does one become a data scientist?
This program — designed in partnership with Alteryx, a leading provider of an end-to-end data science and analytics platform — prepares managers and executives to implement data science initiatives across their businesses.
Why should business leaders consider this course? According to Udacity CEO Gabe Dalporto, “The most successful businesses in the world today put data at the center of their culture and decision making. Udacity’s newest Executive Program equips business leaders to unlock the value of data in their organizations and achieve transformational business outcomes.”
In the past few years, more data has been produced than in the millennia of human history before. This data represents a gold mine in terms of commercial value and also important reference material for policy makers. But much of this value will stay untapped — or, worse, be misinterpreted — as long as the tools necessary for processing the staggering amount of information remain unavailable.
In this article, we’ll look at how machine learning can give us insight into patterns in this sea of big data and extract key pieces of information hidden in it.
In today’s digital age, information is constantly being created, collected, stored, and analyzed. Every aspect of customer behavior can be translated into data points and interpreted by different technologies. With the unstoppable expansion of the data universe, organizations need more of their employees to have the analytical skills to comprehend the ubiquitous amount of data and transform it into actionable insights.
To analyze data, it first needs to be extracted from databases. Currently, the most popular language used for querying and manipulating databases is SQL. While we often think of SQL as a tool used in technical roles, such as programmers and data scientists, many people today in “non-technical” roles such as marketing and sales are being trained in SQL to better leverage data and extend their professional capabilities.