Big Data Vs Data Science – The Beginner’s Guide

Introduction

What is the difference between Big Data and Data Science? Are they interrelated? Which one of the two is a better field? This article is here to answer all the questions a beginner may ask to understand the difference between Big Data and Data Science. Let us begin by understanding both terms individually.

Big Data is used to refer to a large volume of data. This humongous amount of data comprises the structured as well as unstructured categories. This data floods a business regularly. Collecting a massive amount of data is not what matters. What matters is the efficient use of this data.

Data Science blends domain expertise, programming skills, mathematical knowledge, and statistics. It does this to extract important insights from data. These insights help businesses flourish and expand beneficially.

So, what are the key differences between these fields? Let’s find out!

1. Big Data Vs Data Science
2. Which One Of The Two Is Better?

1. Big Data Vs Data Science

Let us try to pick out key topics of differentiation to understand Big Data vs Data Science in a better way.

A) Meaning

Let us try to find the difference between the meanings of Data Science and Big Data.

• Data Science

The Data Science domain is more involved with the scientific strategy data interpretation and information retrieval from a specific data set.

• Big Data

Conversely, the field of Big Data refers to the massive data that the standard data analysis methods cannot handle efficiently.

B) Concept

• Data Science

The concept of Data Science follows scientific techniques, methods, etc., to treat Big Data. It is mostly involved with the extraction of insights from large data sets. Data Science assists in business decisions for better success probability.

• Big Data

On the other hand, the Big Data concept focuses on the assorted types of data created through multiple data sources. Big Data is home to all kinds and formats of data.

C) Application

Let us try to differentiate between the areas of application for Data Science and Big Data.

• Data Science

Data Science is applied to Internet searches. Search engines apply Data Science algorithms to display the best match for our search query. Thanks to these algorithms, it takes only a few seconds for appropriate search results to display.

Digital Advertisements also utilize Data Science. Data-driven ad placements play a huge role in Digital Marketing.

Moreover, Data Science deals with risk detection. Data Scientists actively try to search, identify, and alleviate risks from several perspectives. There are various other applications of Data Science too.

• Big Data

Big Data has numerous applications as well.

It aids in financial services by providing improved customer insights, engagement, and customer trends.

Telecommunication also uses Big Data. It helps in the optimization of network usage and services. Furthermore, it aids in the enhancement of customer experience. Big Data also assists in improving security.

Also, Big Data applications can be seen in the research and development area. They help researchers study government data to understand the social and health sciences.

Big Data is also applied in health and sports, security, law enforcement, etc.

D) Approach

Data Science and Big Data use different approaches to get the desired outcomes. Let’s discuss them below.

• Data Science

Fundamentally, the domain of Data Science broadly uses Mathematics and Statistics. It also inculcates programming skills for creating a model to test the hypothesis. Using all these specializations, Data Science assists in organizational decision-making.

• Big Data

Business firms use Big Data widely. Big Data is implemented to trace the firm’s appearance in the market. Using Big Data, organizations easily get to be at the forefront of the competition.

E) Foundation Of Creation

• Data Science

Data Science comes into existence by applying scientific methods to dig out information from Big Data. This domain is closely associated with data filtering, development, and analysis. Data Science obtains complex patterns from Big Data for developing models.

• Big Data 

Big Data comes into existence due to Internet traffic, electronic devices, audio or video streams, discussion forums on the internet, etc. It also forms because of the organizational generated data and the data created from system logs.

2. Which One Of The Two Is Better?

Since Data Science and Big Data are quite different, it is hard to compare them to point out which one is better. The question – Big Data vs Data Science which is better? – is a tricky one. However, upon clear differentiation between the two, you can decide for yourself whether you want to build a career in Data Science and Big Data.

Let us further discuss some key differences between the two domains.

• Industries implement Big Data concepts for efficient performance, a greater understanding of the market, an upper hand in the competition, etc. On the contrary, Data Science algorithms assist in modeling Big Data to extract meaning for organizational decision-making.

• Companies can gather a massive amount of data, and it is concerned with Big Data. But Data Science deals with the implementation of this data for the extraction of useful information.

• While Data Science mainly deals with utilizing Big Data, there is no credibility involved with Big Data unless analyzed properly. Data Science approaches the task of data utilization by using theories and practical methods. Big Data is a sea of data that needs to be processed, analyzed, and reasoned to provide benefits.

• A lot of people confuse Data Science with Machine Learning. It is also common for people to be unable to differentiate between Data Science and Big Data Analytics. Machine Learning is implemented in Data Science to design and create statistical models for obtaining useful information from the massive amount of Big Data. On the other hand, Big Data Analysis or Data Mining is implemented to deal with large data sets.

• Big Data has a better grip on areas involving technology, software, computations, etc. Contrarily, Data Science gets widely used for carrying out business decisions.

Both Data Science and Big Data are ever-involving fields with immense future scope. Areas of business and research constantly use Data Science and Big Data to yield better results. Thus, learners have a variety of career options to choose from.

Conclusion

Finally, let us quickly revise everything discussed in this article. Data Science and Big Data are often confused with each other. But there are some key differences between them. 

In this article, we tried to understand the basic definitions of Data Science and Big Data. We tried answering – What is Big Data and Data Science? Then, we discussed the difference between their meanings and concepts. We also discussed the comparison between their applications and approaches.

Lastly, we looked at the key differences between Data Science and Big Data to get a better understanding of each of these fields. We also tried to differentiate between terms often confused with each other. For example, we discussed Big Data Analytics vs Data Science. We hope you found this article useful.

To learn more about Data Science, and build a career in Data Science, check out our Postgraduate Diploma In Data Science certified by Manipal Academy of Higher Education. The course runs for 11 months and is carried out in-person. 

Also Read

• A Beginner’s Guide to the Data Science Life Cycle