Data Science

Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract data, analyze data and then visualize the data.

Data Science Life Cycle

Data science generally has a five-stage life cycle having below mentioned stages which require different data extraction and data management techniques, algorithms, programs, data visualization, data analysis and data communication tools and scientific techniques.

• Capture: Data acquisition, data entry, signal reception, data extraction
• Maintain: Data warehousing, data cleansing, data staging, data processing, data architecture
• Process: Data mining, clustering/classification, data modeling, data summarization
• Communicate: Data reporting, data visualization, business intelligence, decision making
• Analyze: Exploratory/confirmatory, predictive analysis, regression, text mining, qualitative analysis

Data Science Uses

Data science is implied in various fields as it is having wide horizon, few of the uses are mentioned below-

• Automation and decision-making- Self Driving cars, example- Tesla
• Classifications- Responses, Emails-Spam, example- Gmail
• Forecasting- Weather, Earthquake,
• Pattern detection- Stock Exchange, Trading, Gaming
• Anomaly detection- Fraud, Transactions, Finance Sector- Client’s creditworthiness, frauds
• Recognition- Facial, Voice, Handwriting
• Recommendations- Sales, example- Amazon
• Complex calculations- Formulas, Chemical Compositions,
• Medical Science- Cancer, Genes
• Entertainment- Movies, Feeds, News, example- Netflix
• Logistics- Navigation, Map, Shortest Routes, example-UPS company’s ORION tool