WEEK 11 - BUSINESS INTELLIGENCE

Question 1

Define business intelligence

Answer 1

leverages software and services to transform data into actionable insights for strategic and tactical business decisions. BI tools access and analyze data sets and present analytical findings in reports, summaries, dashboards, graphs, charts and maps

Question 2

key concepts of business intelligence

Answer 2

• 3Vs of Big Data: volume, variety and velocity
• Big Data: massive quantities of unstructured and semi-structured data from the internet and more, providing more patterns and insights than smaller datasets

Question 3

define data warehouse

Answer 3

central repositories of information that store current and historical data for analysis
- they consolidate data from transaction systems, relational databases and other sources

Question 4

define data mart

Answer 4

subsets of data warehouses, often summarized or highly focused, designed for specific users or departments

Question 5

define hadoop

Answer 5

an open-source framework for storing and processing large datasets efficiently using clusters of computers

Question 6

define in-memory computing

Answer 6

allows data to be stored in RAM for faster access and processing

Question 7

define analytical platforms

Answer 7

• specialized tools for complex data analysis and visualization

Question 8

characteristics of data warehouses

Answer 8

• hold billions of records and petabytes of data
• integrate data from multiple sources
• typically store historical data for 5 years or more
• support cross-business access and analysis
• separate analytics processing from transactional databases

Question 9

characteristics of data marts

Answer 9

• focused on specific subject areas
• smaller in size compared to data warehouses
• serve a specific community or department

Question 9

characteristics of hadoop

Answer 9

• stores and processes large datasets in parallel using clusters of computers
• handles both structure and unstructured data
• useful for processing diverse data types, including social media feeds, logs, audio and video

Question 9

what is data mining?

Answer 9

• finds hidden patterns and relationships in large databases and infers rules to predict future behavior

Question 10

what is OLAP (online analytical processing)?

Answer 10

• enables multidimensional data analysis, allowing users to view data from multiple perspectives
• OLAP Cubes: specialized databases that store pre-calculated data for rapid access
• supports ad hoc queries and complex analyses

Question 11

define text mining

Answer 11

• extracts key elements from unstructured data sets, discovering patterns and relationships
• sentiment analysis measures customer sentiment from online comments and emails

Question 11

what types of information are found from data mining?

Answer 11

• associations: patterns discovered based on item relationships in transactions
• sequences: events linked over time
• classifications: identifying patterns that describe groups
• clustering: discovering unclassified grouping
• forecasting: using series of values to predict future values

Question 12

what is web mining?

Answer 12

Analyzes web data to understand customer behavior, evaluate websites, and quantify marketing success
- content mining: extracts knowledge from web content
- structure mining: analyzes website structural elements
- usage mining: analyzes user interaction data gathered by web servers

Question 13

example of hadoop use case

Answer 13

facebook relies on Hadoop for data storage and processing, enabling the analysis of user data to improve products and targeted advertising

Question 14

examples of data mining in practice

Answer 14

• association example: a study reveals a 65% chance of purchasing a cola drink with corn chips
• sequence example: identifying patterns like purchasing a refrigerator within two weeks of buying a house
• classification example: a mobile phone company uses classification to identify customers likely to leave
• clustering example grouping bike buyers based on demographics
• forecasting example: estimating future sales figures

Question 15

example of business intelligence being used in sentiment analysis

Answer 15

kraft foods uses sentiment analysis to understand customer emotions and preferences from social media and blogs

Question 16

business intelligence in web mining example

Answer 16

• analyzing web server logs to improve marketing strategies and customer engagement