Data Science vs Business Analytics vs Artificial Intelligence is getting harder to distinguish as more and more data is getting analyzed and a lot of avenues are opening up.

More often than not, these avenues are interrelated and indistinguishable. 

Data Science vs Business Analytics vs Artificial Intelligence might get confusing being such closely related. In this article, we will help you differentiate between these three fields. 

Let’s start with examples!

Consider these illustrations of the three fields. You might be able to see the difference for yourself once you understand these examples.

Data Science through illustrations

What do you do when you want to search for something on the web?

That’s right, you Google it! Together with the search results, you get to see how many search results did your search term yield and the time Google took to display search results.

Data Science, the organized way of using data, has made this possible. Internet Search is one of the basic examples of the use of Data Science and there are many others like predicting customer behavior, fraud detection and many others.

Artificial Intelligence through illustrations

The extremely intelligent trio- Google Assistant, Siri and Alexa are now household names.

As per your preference and their performance, one may be more popular than the other.

These are the speech assistants that not only work on the voice-based input from you but also recognize you based on your previous activities on your google account and elsewhere.

For instance, Google Assistant engages in a two-way conversation and never lets the user feel lonely. Try saying- “I am bored.” The helpful Google Assistant would promptly revert with- “Bored? What is this? Here are some activities to entertain you.” It might also give you some interesting and fun facts to read.

Business Analytics through illustrations

Imagine that you are the Manager of a manufacturing firm. There’s machinery in your factory that has been in use for 7 years.

As a part of the data collection drive for the machinery operating for more than 5 years, you want information on this particular machinery’s performance. The data that you will thus collect, will not just help you assess its performance but also aid you in taking the decision- retain this machinery or buy a new one; which option will be cost-effective.

Data Science vs Business Analytics vs Artificial Intelligence

First things first… let’s clear the basics; what is what, and then we will take a look at the applications of these three fields.

Data Science

According to a report, more than 2.5 Quintilian bytes of data are generated every day and it is expected that the data generated every second will be 1.7 MB by 2020.

This estimate is per person; just imagine the massive amount of data and the opportunity it opens up!

Deriving insights from the data by the use of scientific methods, systems and processes is the underlying aim of this interdisciplinary field, Data Science. Businesses benefit from these insightful analyses and make use of it to increase the efficiency of their processes, adopt a targeted approach, etc. 

Take Data Science to be the process to extract, prepare, analyze, visualize and maintain information. 

Artificial Intelligence

As per the PWC report, by 2030, Global GDP could increase by 14%, equal to 15.7 Trillion, due to continuous innovations in this field.

This is a field that deals with making machines intelligent enough to perform tasks requiring human intelligence. Algorithms are the medium through which autonomous actions are powered. The AI-powered machines are able to mirror cognitive functions, such as learning, speech recognition, decision making and problem-solving etc. 

How?

Artificial intelligence is modeled on human neurons; exactly like your brain works with the help of those tiny neurons or messenger cells. This neural network for machines is termed as Artificial Neural Network.

Artificial intelligence is like an omnipotent being; you’ll find it in the news almost every day.  Those speech and image recognition apps related news you come across is the gift of this highly intriguing field. 

Business Analytics

Analytics powered by the data that facilitates decisions for businesses is the powerful field of business analytics for you. This is possible with the patterns and insights drawn from the marketing, sales, predictive and survey data.

With such a massive amount of data everywhere, business analytics is like that savior who simplifies this huge amount of data and organizes it to make it useful.

Predictive modeling is achieved in business analytics through the use of statistical and explanatory analysis.

In simple terms, why something happened in a particular way is found out within this process. For example, you own a publishing house and recently saw a great decline in the demand for Q3. Business analytics will help you find the reason- assessing the market, competitor style for you and etc.

Let’s understand Data Science vs Business Analytics vs Artificial intelligence through their applications in the real world.

Applications of Data Science and Artificial Intelligence

• Recommender Systems

The “similar product” feature on Amazon and other e-commerce sites is one of the most popular applications of Data Science. This recommender system lets you select the product of your choice from the various available options. 

Do you know how these sites gauge your preferences? It is based on your search preferences and interests (the product that you clicked to view). Search engines and product websites use this recommendation system to promote their products. Indeed, a good opportunity for them.

• Image Recognition

With the advancements in machine learning algorithms, image recognition is now possible with increased precision. The machine identifies an image based on the previous knowledge and identification. You must have seen the auto-tag feature of Facebook. It is one of the best examples of image recognition. Besides, it is also being used in different sectors like tourism, gaming, retail, etc.

• Fraud Detection

By comparing the types of transactions and other details of the applicant like its history, profile etc., the machine can differentiate a genuine transaction from a fraud one. Not just this, banks and digital payment apps are also making use of ML to prevent money laundering and keep an eye on the types of transactions going on between the buyers and the sellers.

Applications of Business Analytics

• Finance

Almost all the companies have massive financial data. It will be easier for businesses to decide the price of various products with the help of efficient business analytics tools. The financial data can also be used to study the trends of a specific stock’s performance. The owner of these stocks can thus decide whether to sell or retain it.

• Marketing

This is one of the most practical and tangible applications of business analytics. All of your marketing strategies are of no use until you can gauge its impact and the user engagement achieved with it. Business analytics comes to your rescue and lets you assess all these parameters to evolve and improve your marketing strategies. 

What is the Future of Data Science vs Business Analytics vs Artificial Intelligence?

Machines are now getting ‘intelligent’ with the advent and continuous technological advancements of AI in almost every field.

The process that starts with data collection, moves a step further to make machines learn and finally ends with making machines intelligent and help humans. You must have heard about the humanoid robot ‘Sophia’. It is one of the perfect examples of what AI is capable of doing.

Several organizations and governments have increased their investment in the visionary projects and research in this field as they are aware of the benefits and the potential of data science and AI. An artificial intelligence-powered business will not only be the most profitable one but would also have an edge over others.

As far as the future of business analytics is concerned, it is set to scale at an unprecedented rate. This is because existing organizations won’t cease to exist and new ones will be established; companies will grow in size and number.

The field will not be limited just to the marketing and sales domain but extend over to improved customer engagement and highlighting gaps and scope in different domains. 

Anything that is connected with data isn’t a standalone concept; just like business analytics isn’t. The comparison of Data Science vs Business Analytics vs AI doesn’t mean they are unknown to each other; they work towards realizing the same objective- making huge amounts of data usable and meaningful.

We hope you can now successfully differentiate between Data Science vs Business Analytics vs Artificial intelligence; in case you have any doubts or want to share something, please feel free to share it in the comment box below.

All the best for your Data Science journey!!