What is Data Science?
What is Data Science?
Data science can be explained as the science that deals with the identification, representation, and extraction of needful and meaningful information from a pool of data that are useful for the further growth of the business. It is actually a mixture of programming and analytics that works on unstructured raw data to create finely chopped useful pieces. The presence of a large amount of data with various structure and purpose, it is quite difficult to choose the most appropriate one. It is in this phase that the data engineers set up databases and data storage to ease the data mining.
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In a business firm, the amount of data creation increases rapidly and the data scientist helps such organizations to convert the raw data into valuable business data. Data extraction converts the unstructured data into pure and polish data that will be useful for further processing. The important characteristics that a data engineer should possess are good knowledge of machine learning, statistical skills, analytics, coding, and algorithmic experience.
Taking up data science career means you have to make yourself expertise in deploying statistics and deducting reasoning. The best way to get the best result is going through several steps that every data scientist should obey. It includes:
- Understanding the problem
- Collecting enough data
- Processing the raw data
- Exploring the data
- Analyzing the data
- Communicating the results
Subsets of Data Science
The different subset of data science includes:
It includes analysis of data using various tools and technologies. It can be done using various programming languages.
He performs the high-level strategies that include integrating, centralizing, streamlining and protecting the data. He should have high authority over various plans and should have good knowledge of various tools like Hive, Pig, and Spark etc.
He is supposed to work with a large amount of data where the logical statistics and programming languages club each other. The data engineer should have a software background.
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Data Science – the three Skillset
Data science can be called a club of three major skills which includes mathematical expertise, hacking skills (technologies) and strong business acumen.
Before approaching the data, the data scientist should create a quantitative strategy through which exact dimensions and correlations of data can be expressed mathematically. The solutions to many business problems can be solved by building analytical models. It is a misconception that the lion’s share mathematics includes the statistics. But, the fusion of both classical and Bayesian statistic is will be helpful.
Hacking Skills (technologies)
Here we don’t mean breaking a computer and taking out the confidential data. The hacking here refers to the clever technical skills that will make the solutions as faster as possible. Many technologies are very important in this area. Many complex algorithms are related to each task and hence the deep knowledge in core programming languages is a must. Data flow control is another sophisticated area. The man dealing with the problem should be tricky enough to find the loops and high dimensional cohesive solutions.
A data scientist should have a solid awareness of tactical business traps. He will be the one person in the organization that works closely with the data and hence he can create great strategies that will solve very minute problems.
Top tools of Data Science
It is categorized as:
- R Programming
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Differentiating Data science from Big data
Big data consists of structured, unstructured and semi-structured data whereas data science deals with programming, statistical and problem-solving techniques. In big data, we will be using various methods to extract meaningful insights from large data. In data science, we will be using the above-mentioned techniques to solve the problems. Irregular and unauthorized data will be dealing with data science.
The importance of data science is increasing day by day. There are many factors that enable its growth. Evolution of digital marketing is an important reason. The data science algorithms are used in every strategy in digital marketing to increase the CTR. Also, the data science will increase the performance. It will give way to real-time experimentation. One who can please the customers will win the business. Data science will create the best way for the same.