Python Data Science

Data plays an important role in our lives. For example, a chain of hospitals contain data related to medical reports and prescriptions of their patients.A bank contains thousands of customer's transaction details. Share market data represents minute-to-minute changes in the values of the shares.In this way, the entire world is roaming around huge data.

Once the data is stored, we should be able to retrieve it based on some pre-requisites. A business company wants to know about how much amount they had spent in the last 6 months on purchasing the raw material or how many items had been found defective in their production unit. Such data cannot be easily retrieved from the huge data available in the data warehouse. We have to retrieve the data as per the needs of the business organization. This is called data analysis or data analytics where the data that is retrieved will be analyzed to answer the questions raised by the management of the organization. A person who does data analysis is called 'data analyst'.

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Data Analysis and Data Visualization

Once the data is analyzed, it is the duty of the IT professional to present the results in the form of pictures or graphs so that the management will be able to understand it easily. Such graphs will also help them forecast the future of their company. This is called data visualization. The primary goal of data visualization is to communicate information clearly and efficiently using statistical graphs, plots and diagrams.

Data science

Data science is a term used for techniques to extract information from the data warehouse, analyze them and present the necessary data to the business organization in order to arrive at important conclusions and decisions. A person who is involved in this work is called 'data scientist'.

Differences of Data Scientist and Data Analyst

Data Scientist Data Analyst
Data scientist formulates the questions that will help a business organization and then proceed in solving them. Data analyst receives questions from the business team and provides answers to them.
Data scientist will have strong data visualization skills and the ability to convert data into a business story. Data analyst simply analyzes the data and provides information requested by the team.
Perfection in mathematics,statistics and programming languages like python and R are needed for a data scientist. Perfection in data warehousing,big data concepts,SQL and business intelligence is needed for a data analyst.
Data scientist estimates the unknown information from the known data. Data analyst looks at the known data from a new perspective.