What Is Data Science

Written by Mehr Un Nisa

On August 25, 2020

Let’s face it, many of us first started Google-searching AI vs Data Science after Harvard Business Review popularized it as ‘The Sexiest Job of the 21st Century’ in 2012. Up until a few years ago, it was a field of study that only a few people specialized in and was taught by selective institutions. Fast Forward to today, Data Science has taken everything by storm.

When we first begin to think about Data Science, we imagine a plethora of numbers and variables or data of any form. This is exactly what a Data Scientist starts with. Where the beginning could either be heaps of raw data or a problem statement, the end objective is always the same: Deriving Insights.


AI Vs Machine Learning Vs Deep Learning Vs Data Science



Before we go further, we’d like to emphasize the fact that people tend to confuse AI, Machine Learning, Deep Learning and Data Science altogether. Initially, we did too. However, there are subtle differences between them and I’ll try to make things as simple as I can:

  • Artificial Intelligence is the broadest out of all these fields. Artificial Intelligence simply implies giving computers the ability to perform humanly actions through intelligently written computer programs. E.g. A computer playing games against you.
  • Machine Learning is a subset of Artificial Intelligence. Verily, Machine Learning is almost exactly like Artificial Intelligence with the main difference being subtle, but self-explanatory. Machine Learning involves a machine ‘learning’ from previously collected data to perform humanly actions, with precision. E.g. A Support Vector Classifier classifying whether a newly input image either is a of a cat or a dog.
  • Deep Learning is a further subset of Machine Learning; Deep Learning and Machine Learning essentially do the same thing albeit that Deep Learning makes use of complex, deep and layered structures called Neural Networks. The structure of these networks is inspired from the human brain and these have been the breakthrough that has vastly improved the results of traditional Machine Learning algorithms. E.g. A Generative Adversarial Neural Network performing face swaps on images.
  • Data Science is an intersection between Machine Learning, Deep Learning as well as Mathematics and Statistics. It involves using all of the aforementioned fields to derive insights and meaning from data which can be subsequently used to make valuable decisions beforehand. E.g. Forecasting when a stock is likely to lose value so that one can make decisions beforehand.

If you are still not clear about AI Vs Machine Learning Vs Deep Learning Vs Data Science, feel free to talk to us. Our team of experts will try to clear this in detail.

Data Science In A Nutshell


To define Data Science, the Internet provides us with a wide variety of complex definitions that a layman might not be able to decipher. Hence, to understand this in the simplest of terms, imagine buckets continuously being filled with data. A Data Scientist’s job entails taking these buckets, preparing them and bringing structure to the collected data. Once structured, they use that data to derive actionable insights from them and answer questions like ‘What does all this data mean’ and ‘what can we learn from it?’.

Suppose you own a fruit store. You’ve been selling fruit for years and hence, have collected lots of data about your sales through your point of sale system. Wouldn’t it be cool if you found some way of analyzing your collected data to know how much Apples are you expected to sell next month so that you can pre-order them accordingly? Or how much of the Apples you’re buying, on average, don’t sell and you could reduce costs? Data Science can help you do this and much more!


Data Science Is Everywhere


Applications of Data Science - AI vs Data Science


From Amazon Alexa to Netflix, Data Science is everywhere. The ability of these intelligent systems to give recommendations and predict searches are just some of the things that add a human element to machines which they initially lacked. The addition of this ‘human element’ to machines sparked the Machine & Deep Learning revolution that led to numerous jaw-dropping technological advancements.

Significant applications of Machine Learning in conjunction with Data Science are:

  • Computer Vision: One of AI’s most widely celebrated domains, Computer Vision gives computers the power to see just like any other human being. This allows us to address and solve various problems and translate them into robust products. In keeping-up with building robust products, MilestoneZero developed an intelligent system that could estimate the age and gender as well as emotions and smile of a customer and show a similarity match list of celebrities. Fun, right? 
  • Natural Language Processing (NLP): NLP equips a machine to understand and derive meaning from large amounts of text, speech or audio data. Thereby, extending the intelligent facets of a machine. Its multiple practical applications include chatbots helping you on a website you’ve visited, an app summarizing a big article for you (GeekText anyone?) etc.
  • Speech Recognition / Processing: A subset of NLP, Speech Recognition has broad applications in the field of Machine Learning and Data Science in general. Want Siri to read-aloud the morning paper for you or Alexa to offer you career advice, Speech Processing has you covered.
  • Recommendation Systems: These allow better customer experience tailored by the way they interact with a system.
  • Predictive Analytics: Using the present to know about the future epitomizes Data Science. Predictive Analytics allows businesses to forecast sales, predict market crashes and what not to stay ahead from the rest.


How Data Can Shape The Future


Like kerosene fuels airplanes, Data Science is set to (and already is) fuel productive businesses. Be it a startup or an enterprise, all are producing tonnes of data every millisecond and each click is working towards shaping their future. How’s that possible? Because Data Science gives you the ability to peek ahead of time.

This tonnes of data has the power to give you insights, information, metrics and what not previously deemed unattainable. Now, instead of the aforementioned fruit shop where you might be saving or gaining thousands of dollars, apply this concept to enterprise-level businesses or startups. You’ll get the power to play with potentially millions of dollars!

Data is now driving actions. It is showing businesses their next winning strategy, their potential failures / successes beforehand and that one marketing campaign that will steal the show. It empowers them to work on changing the market and the world at large. Thus, it seems that it is true when they say: ‘Data is the new oil’. It needs to be taken seriously and we can help you uncover its true potential for your ideas.

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All Rights Reserved | MilestoneZero Technologies | 2020

All Rights Reserved | MilestoneZero Technologies | 2020