Data Science Insight for Beginners

Data Science is the sum of processes, tools and knowledge to get valuable information from data. Through our use of technology via shopping, sharing of pictures, posts on social media etc. we provide data to companies and research institutions who analyze and use the results of their findings to make predictions if a prospective customer will make a purchase on a site or not, suggest to medical practitioners the best treatments for patients.

Below I share a summary of a course I am taking on Introduction to Data Science Specialization by IBM on Coursera. The first course is What is Data Science?

1. Definition of Data Science
   Data Science can be defined as the use of processes and tools to extract, clean and make meaning out of data which could be either in structured or unstructured format. Example using purchase data of a client to give him/her discount on their next purchase can be classified as a use of data science in the retail business.

2. Paths to Data Science
   Until recent.i.e. post 2010, most data scientists are people with a statistics or mathematics background. Some also included people who had a degree in engineering, physics and business. Recently people from all walks of life have studied to join the field.

3. What do Data Scientists Do?
   They clean and shape data into a format that is easy for analysis. They also use algorithms to make predictions based on the data they have.

4. How companies can get started in Data Science?
   First and foremost, companies should begin to store their data; costs, profits etc. They should also have proper documentation for the data so it is easy to understand when it is used many years from now. Companies should also educate their employees on data literacy, make sure that the employees in the company are interested in the data science process as their actions or in actions can affect the quality of the data that is been captured.

5. How to recruit for Data Science?
   First look for candidates who resonate best with the goals of your company. Is the candidate passionate about what you do, are they curious about everything? These attributes are important as they are difficult to teach. People with such skills can then be taught the technical skills. Last but not least, candidates should have strong presentation skills as the final output of the process is to share the results found.

6. Advice to New Data Scientists
   It is important for one to be curious about everything as data science is about finding “hidden gems” in structured or unstructured data. One should also know their competitive advantage. That is one should be clear in the area he/she can give off their best, is it in the retail, medical or entertainment space.

I also set out to find examples to real-life applications of data science in our everyday life.

• SPORTS: The official website of Liverpool Football Club shared an article on how the team is using Data Science during their matches. The data science department tracks the movements of the players on the field and provides those useful for the coach to make a decision. liverpool.com/liverpool-fc-news/features/li..
• MARKETING: A popular story of how Target found out a teenage was pregnant before her father did is also an example of how retailers are using data science through data mining to suggest personalized products to customers. forbes.com/sites/kashmirhill/2012/02/16/how..
• AGRICULTURE: Watson Decision Platform for Agriculture is a platform by IBM which uses IBM’s strength in cloud, AI and IoT to help farmers make informed decisions about pricing, irrigation and weather so they have more yield that are very high in quality. business.weather.com/blog/evolution-modern-..

My next post will be on the second course in the specialization - Open Source tools for Data Science.