Topic 8 Flashcards
What are the Five Vs of Big Data?
Volume, Velocity, Variety, Veracity, Value
What does ‘Volume’ in Big Data refer to?
The massive scale of data
What does ‘Velocity’ in Big Data refer to?
The speed at which data is received and processed
What does ‘Variety’ in Big Data refer to?
The different forms of data like text, images, and video
What does ‘Veracity’ in Big Data mean?
The uncertainty, noise, or bias in data
What does ‘Value’ in Big Data mean?
The usefulness or benefit derived from the data
What is Business Intelligence?
The process of turning data into actionable insights
What are functions of Business Intelligence tools?
Reporting, OLAP, analytics, data mining, text mining, predictive and prescriptive analytics
What is Business Analytics?
Analyzing past performance to inform business planning
What are the three types of analytics?
Descriptive, Predictive, Prescriptive
What is Descriptive Analytics?
Analysis of historical data to understand what has happened
What is Predictive Analytics?
Forecasting future outcomes based on current data
What is Prescriptive Analytics?
Recommending actions based on data analysis
What is Hadoop?
A framework for distributed storage and processing of large datasets
What is Apache Spark?
A fast engine for large-scale data processing including streaming, SQL, and machine learning
What is a benefit of cloud-based analytics platforms?
Flexible, scalable computing power without major infrastructure
What is an example of a data management tool?
SQL databases
Which language is commonly used for data science?
Python
What is a popular tool for data visualization?
Tableau
What is a statistical programming language used in analytics?
R
What is digital dexterity?
The mindset and behaviors that enable employees to succeed with digital tools
Why does Big Data matter for digital transformation?
It enables competitive advantage, innovation, and better customer insights
What is a challenge of data integration?
Difficulty combining data from different sources or formats
Why is high data quality important?
Poor data leads to bad decisions and unreliable analysis
