data science introduction | data science and data analytics difference​

Data Science Introduction :

Data science is the study of data to extract meaningful insights and develop strategies for businesses and industries.
    In this Blog you will learn following points also you can download power point ppt of this topic link is below.

• What is data science?
• What data science do?
• What is data analytics?
• What data analytics do?
• Example of data science and data analytics
• Difference between data science and data analytics

let's start with introduction of data science.

What is data science?

The term “data science” combines two key elements: “data” and “science.”

1. Data: It refers to the raw information that is collected, stored, and processed. In today’s digital age, enormous amounts of data are generated from various sources such as sensors, social media, transactions, and more. This data can come in structured formats (e.g., databases) or unstructured formats (e.g., text, images, videos).
2. Science: It refers to the systematic study and investigation of phenomena using scientific methods and principles. drawing conclusions based on evidence.

“data+science” refers to the scientific study of data.Data science is the study of data to extract meaningful insights and develop strategies for businesses and industries.

            

                Imagine you’re scrolling through your favorite social media platform, and you notice that certain types of posts always seem to grab your attention. Maybe it’s cute animal videos, delicious food recipes, or inspiring travel photos. Now, from the platform’s perspective, they want to keep you engaged and coming back for more. This is where data science comes into play. They collect a ton of information about what you like, share, and comment on. They use data science techniques to analyze all this information to understand your preferences better.

What data science do?

Data science uses various tools to uncover actionable insights hidden in organization’s data. Data Science involves applying scientific methods, statistical techniques, computational tools, and domain expertise to explore, analyse, and extract insights from data. Data Science can help businesses gain insights and knowledge to make the right decisions. Data science produce a system that give prediction.

Example of Data science

1. LYNA:- Google developed a tool called LYNA for identifying breast cancer tumors.
2. Fraud Detection in Financial Institution : Data science, particularly machine learning and artificial intelligence algorithms, has introduced more adaptive and robust fraud detection mechanisms. By analyzing large amounts of historical transaction data, data scientists can develop predictive models that can detect unusual patterns or anomalies in real-time transactions. Moreover, data science enables the integration of multiple data sources, such as transaction records, customer behavior data, device information, and social network data, to build comprehensive profiles of customers and their activities. By utilizing these enriched data sets, data scientists can create more precise fraud detection models.

What is data analytics?

Data analytics (DA) is the process of examining data sets to find trends and draw conclusions about the information they contain. For example

in above image show the data of a website using data analytics tools that conclude the data and giving a concise information regarding trends of users for particular website related to choice of topic, language of topics viewer likes to watch.

Download pdf notes of this topics 

What data Analytics do?

Data analytics identify which particular product features users prefer. Data analytics usually have a more narrow and specialized role seeking out the answers to specific question. Data analytics convert large data into conclusion.

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Data Science Vs Data Analytics Example

Data science and data analytics are closely related but there are key differences. While both fields involve working with data to gain insights, data science often involves using data to build models that can predict future outcomes, while data analytics tends to focus more on analyzing past data to inform decisions in the present.

        lets compare our body with a business. for related to any problem we can concern two types of doctors for treatment. first is general doctor whose scope is macro second specialized doctor whose scope is micro. both can treat in its own way.

same as data science is work like a general doctor for our business whereas data analytics is work like a specialized doctor for our business. data analytics give the answer of particular question.

Data Science	Data Analytics
Data science focuses on the macro asking strategic level questions and driving innovation.	Data analytics focuses on the micro finding answer to specific questions using the available data.
Dept knowledge of Programming is required.	Basic Programming Knowledge is necessary.
Uses Machine learning algorithm to get insights	Does not Uses Machine learning algorithm to get insights
Data science works on structured and unstructured data using machine learning and AI.	Data Analytics works on structured data using tools like MS Excel and data visualization software.

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