Data science is the study of colossal amount of data to derive important information that is useful for the success of business. It deals with providing meaningful insights into the data present in the organizations repository. A data scientist mines information from raw and unstructured data. The information that is mined from the raw data is than processed with the help of analytical, business and programming skills. Today business world has transformed in a digital space where the organizations deal with huge amount of data that are digitally stored. The use of technology has made data storage easy and cost effective. A data scientist is a person who deals with the processing of both structured and unstructured data. Data science is one of the highest paid professions of the IT industry. ExcelR Solutions holds data science training program for candidates who aspire to become data scientist.
Data science life cycle
- Discovery: The data scientist must assess whether they have all the required resources present like technology, time, data, etc. In this phase the data scientist frames the business problem and formulates hypotheses.
- Data preparation: In the process that data scientist needs analytical sandbox to perform analytics. The data scientist explores and processes the data and transforms it to analytical sandbox.
- Model planning: Here, the data scientist regulates methods and techniques to develop relation between variables. The relationship than sets the base for algorithms in the next phase.
- Model building: In this phase the data scientist develops datasets that will be used for testing. The existing tools will be used for testing in order to determine whether they will suffice for model building or if it needs new tools.
- Operationalize: Here the data scientist delivers final reports, tools and techniques, briefings, and technical documents. A pilot project may also be implemented to test the real-time production environment.
- Communicate results: In this phase the data scientist communicates all the key findings to the stakeholders. Data scientist than determines the success and failure of the project based on the criteria formulated in phase 1.
Things that can be achieved with active data science
- Data Analytics Solutions is useful for reduction of cost. It uses various tools and techniques to analyse the cost history and helps find ways for reduction of cost.
- It is also helpful if the business is aspiring to enter in new markets.
- It is also used for gauging the effectiveness of the marketing campaign that is followed by the business.
- It is also used for launching of new product or service.