Data Science vs. Big Data vs. Data Analytics

Data is ruling the world, and we can see its impact on almost all the business niche. It is not only helping in creating new and high-performing tools and techniques, but at the same time, data is also forming the base for strategizing business policies. So, we can say that our reliance on data is increasing. It is expected that by the end of 2020, we will have our 1.7 megabytes of new information created every second for every human being. Here, you must know that the available data is staggered, and it has to be organized so that it becomes informative. Here comes the role of techniques like big data, data analytics, and data science. Owing to these technologies' growing importance, we are witnessing a great demand for big data training, data analytics certification, and data science training to have data experts.

Data science, big data, and data analytics might be dealing with data, but they tend to differ in their approach and functioning. Here we are going to discuss the difference between them.

Big Data vs. Data Analytics vs. Data Science:

Definition:

Data Science- It deals with the structured and unstructured data. The work of data scientists is to analyze the data and take out the informative part. Data cleansing, preparation, and analysis are a part of Data Science.

It makes use of different statistical, mathematical, and programming tools to capture data ingeniously. It aims at extracting insight from data.

Big Data- Big Data begins with raw data, and it has to deal with a humongous volume of data that needs special tools for processing. It is used to analyze insights that can eventually help in improving the decision making process.

Data Analytics- It is used to examine raw data to derive useful information. In this, the expert has to apply algorithmic and mechanical processes to derive useful information. Many companies are now using data analytics to derive useful inferences, which can help them formulate their business strategies.

Application:

Data Science-

1. Internet Search- The search engines make use of data science to provide better results and the ones that would match customer's queries.

1. Digital Advertisements- Another area where data since finds application in the digital marketing world like display banners and digital billboards.

2. Relevant products- Yes, with the help of data science, it becomes easier for the companies to put forward those products which are in great demand by the customers. The algorithm studies the previous purchases and buying behavior of the customer, and based on it; the recommended products are presented.

Big Data-

1. Financial services- Companies dealing with credit cards, banking services, financial advisories, insurance firms, and institutional investment are using big data. These companies have a huge amount of unstructured data, and they are scanned via:

• Fraud analytics

• Customer analytics

• Operational analytics

• Compliance analytics

1. Communications- It is imperative for telecom companies to retain their customers and increase their subscriber base. The best way to combat this issue is by daily analysis of customer behavior. Since this number is massive, big data techniques will be useful here.

1. Retail- Retail stores have to deal with a massive amount of data, with the right analysis of this data, it will be easier for them to serve their customers better. The right kind of data assessment tool under Big Data will be beneficial in this.

Data Analytics

1. Healthcare- It is imperative for hospitals and other medical care facility providers to control the cost while delivering outstanding medical aid. The data from machine and medical equipment are used to track as well as optimize patient flow and treatment.

1. Travel- We know that data analytics techniques help analyze customer behavior. Eventually, it helps in enhancing the buying experience. Travel companies can use these techniques to find out the preferences and choices of customers visiting their website, and based on it, they can suggest them with the right measure and personalized travel recommendations.

1. Gaming- Yes, even the gaming industry can make use of data analytics to optimize customer experiences. They can work on the likes and dislikes of the customers, thereby enhancing the gaming experience.

So, these were the differentiating factors between data analytics, big data, and data science. The difference also lies in the conceptual part, and when you study this curriculum. Well, a professional learning platform will help you in developing the right knowledge about these technologies.

The Future-

Global Tech Council provides online data science training, big data training, and data analytics certification programs. This program aims to provide in-depth knowledge about these fields and also learn the application part of the same. These technologies are going to rule the world, and we are going to witness a rise in the demand for such professionals. With the right approach, you can become a part of one of the leading industries.

If you wish to make a good career in data science, big data, or data analytics, this is the right time to start your journey.

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