Simple Guide to Data Science Vs Artificial Intelligence

1. Simple Guide to Data Science Vs Artificial Intelligence All businesses and inventions are endorsing the newest development is technology to create more. This world is the world of big data, AI, BI, and machine learning. Despite the cons, the pros are unlimited. Before specializing in any of them, we need to understand the difference between Data science and AI. Table of Contents 1.What is Data Science? 1.1.Data Velocity: 1.2.Data Variety: 1.3.Data Volume: 2.What is Data Science Used for? 2.1.Data Scientist: 3.What is Artificial Intelligence (AI)? 4.What is AI Used for? 5.Big Data vs Artificial Intelligence: Difference Between Data science and Artificial Intelligence 5.1.Conclusion on Data Science vs AI

2. What is Data Science? Data Science definition says that it is a combination of algorithms, data analysis, domain knowledge, mathematics, coding skills, statistic, computation, and other such processes to extract data from any kind of data at hand. The three Vs of Big Data easily describe what data science holds. They are Velocity, Variety, and Volume. These three vectors of data science keep expanding in their axis to denote the three aspects of big data. Data Velocity: Velocity is Data science that measures the rate of flow of data flowing in. Since data is eventually growing every second, it is important to measure the speed at which it is entering the collection and observation zone. They can be measures in real-time, batches, or periods. Data Variety: There are numerous types of data that are used in big data. These are the varieties in forms of structures, unstructured, PDFs, documents, videos, and other formats available.

3. Data Volume: It simply denotes the size of data that keeps increasing. Depending on the data variety, it could be in kilobytes, megabytes, or TB. What is Data Science Used for? Data Science sounds like a complicated term. However, this system is a simple and continuous process to read data and use them to our benefit. The data science cycle goes around by observing information at hand, interrogations, and creating an appropriate hypothesis, predicting, testing the predictions, and finally developing new theories to improve products and services. At the stage of testing the predictions, new data is gathered for the verification of results. This phase is where the hypothesis either fails, gets verified, or face a modification.

4. Data Scientist: A data scientist is responsible for the Big Data Science system, especially the end when they have to communicate to managers, share partners, stakeholders, and other related authorities. What is Artificial Intelligence (AI)? Artificial Intelligence known as AI has been the talk of the years in most industries. AI is the introduction of human intelligence into machines. This enables the robot to act, work, and behave like humans for the task they are programmed for. So, what are these behaviours that they are programmed for? The most usual answer is problem- solving and learning. So, a robot mimics human actions through programmes to fulfil the purpose they are made for. For copying human actions, the need to possess human intelligence which is input to them through codes. You can read the full content: https://digitalsushma.com/simple-guide-to-data-science-vs-artificial-intelligence/ •••••••••••••••••••••••••• Digital Sushma Email ID: contact@digitalsushma.com Phone No.: +1-702-875-6940 Visit Us: https://digitalsushma.com/ Stay Connected Via: https://www.facebook.com/digitalsushma/ https://www.instagram.com/sushmasmaurya/ https://in.pinterest.com/digitalsushmacom/ https://twitter.com/DigitalSushma