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
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