Data Science vs. Big Data vs. Data Analytics

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.

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.

Data Science-

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:

2. 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.

3. 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.

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.

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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