Data Science, one of the fastest growing industries today, requires you to keep up to date with the latest trends in technology, tools, industry trends and job opportunities, to stay afloat as an information professional. In this discussion, my goal is to discuss the definition of data science, techniques, the relationship with Big Data and analysis. I have also addressed some common queries about a career in Data Science; the logical route, the options for the transition to a Data Scientist role, or the suggested certifications to obtain a junior role.
The science of data as a multidisciplinary subject encompasses the use of mathematics, statistics and computer science to study and evaluate data. The key objective of Data Science is to extract valuable information for use in strategic decision making, product development, trend analysis and forecasting.
The concepts and processes of Data Science are derived mainly from data engineering, statistics, programming, social engineering, data storage, machine learning and natural language processing. The key techniques in use are data extraction, big data analysis, data extraction and data recovery.
Benefits of data science
Data science has several benefits. Here, I have listed some of the best things in data science:
Best business value
The main advantage of having Data Science in an organization is making decisions faster and better. These data-driven decisions, in turn, lead to greater profitability and improved operational efficiency, business performance and workflows. Data Science helps identify and refine target audiences in customer-oriented organizations.
Identification and Refinement of target audiences
The data obtained from Google Analytics to customer surveys should be analyzed to identify demographic data. A Data Science professional helps to accurately identify key groups through a comprehensive analysis of different data sources. Organizations can also tailor services and products to customer groups and help profit margins thrive.
Better risk analysis
Predictive analytics, driven by Big Data and Data Science, allows users to scan and analyze news reports and social media sources to stay updated on the latest industry trends. In addition, it also promotes detailed health tests on its suppliers and clients. This is useful for assessing the risks and taking the necessary steps for mitigation well in advance.
Recruit better in less time
Reviewing thousands of resumes is one of the biggest problems of any recruiter. Thanks to Big Data, finding the right candidate is much easier now, with the large number of profiles available through social networks, corporate databases and job search websites. Data Science professionals find it much easier to sort data and hunt the best candidates for the organization.
Through data extraction, internal resume and application processing, and even sophisticated tests and data-based skill sets, Data Science can help your recruiting team make faster and more accurate selections.