Understanding Data Mining in Business Intelligence

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What is Data Mining?

A process that uses statistical, mathematical, artificial intelligence and machine learning techniques to extract useful information from large databases.

Where is Data Mining in Business Intelligence?

Data mining is a part of business intelligence.

Why do we need Data Mining in managerial decision making?

To perform statistical and mathematical analysis, hypothesis testing, prediction, and customer scoring models.

What are the major characteristics of Data Mining?

Data are often buried deep within very large databases and sophisticated tools are used to clean and synchronize data for the best result.

What is the main focus of customer analytics in CRM and revenue management?

Clustering customers into groupings based on better understanding

What is the primary goal of text mining?

To extract additional useful information from stored data

What does web content mining primarily involve?

Extraction of useful information from Webpages

What is the purpose of calculating weights of terms in text mining?

$1) Term frequency factor (the actual number of times the word appears in a document) and 2) Inverse document frequency (the number of times the word appears in all document in a set)$

How does web usage mining contribute to understanding user behavior?

$Generated through web page visits, transactions and web server logs$

What is an example application of data mining to non-structured or less structured text files?

Applying data mining to customer database to discover patterns.

What does optimization involve in customer analytics?

Detecting patterns to optimize transaction and customer interaction.

What type of mining focuses on understanding user behavior through web page visits and transactions?

Web usage mining.

What is the primary focus of web structure mining?

Generating information from the links included in WebPages.

What does text mining primarily focus on?

Application of data mining to nonstructured or less structured text files.

What are the two main types of data mining?

Hypothesis-driven and discovery-driven

What is the major difference between cluster analysis and classification?

Classification sorts cases into groups, while cluster analysis identifies common characteristics shared by group members.

What does association data mining establish relationships between?

Items that occur together

In which business sector is data mining used to understand customer behavior?

Retailing

What do prediction methods use to predict future values?

Variables

What is the aim of data clustering algorithms?

To create groups with maximum similarity and minimum similarity across groups

What is the primary purpose of sequence discovery in data mining?

Identifying associations over time, tracking elapsed time between events and frequency of occurrences

Which type of induction method is classification?

Supervised

What does retail-focused data mining primarily involve analyzing?

Demographic data, transaction data, and online interaction data

In which sector is association rule discovery often used?

Retailing for market basket analysis

What are the two types of data mining based on their approach?

Hypothesis-driven and discovery-driven

  1. What is the primary purpose of text mining?

The primary purpose of text mining is to extract meaningful numerical indices from unstructured or less structured text files and then process these indices using various data mining algorithms.

  1. What are the steps involved in mining text?

The steps involved in mining text include eliminating commonly used words (stop-words), replacing words with their stems or roots, considering synonyms and phrases, and calculating the weights of the remaining terms based on their frequency and importance.

  1. How does text mining contribute to competitive advantage for organizations?

Text mining allows organizations to visualize relationships between documents, such as policies, memos, emails, and minutes of meetings, which can be a major source of competitive advantage.

  1. What is an example application of text mining in the airline industry?

An example application of text mining in the airline industry is to focus on key problem areas through pattern identification by accessing incident reports to increase the quality of service, such as identifying incidents that might lead to trouble and helping management stop the issue.

  1. How does web usage mining contribute to understanding user behavior?

Web usage mining contributes to understanding user behavior by generating insights through web page visits, transactions, and web server logs, which are useful for customer relationship management (CRM) and web analytics.

Text mining primarily focuses on extracting meaningful numerical indices from ______ text files

unstructured or less structured

Web mining is the discovery through the analysis of interesting and useful information from the ______, about the web and usually using a web based tool

web

Web content mining involves the extraction of useful information from ______

Webpages

Web structure mining generates information from the ______ included in WebPages

links

Web usage mining is generated through web page visits, transactions and web server logs, and is useful for ______ and understanding user behavior

CRM

What is the primary purpose of a data warehouse in Business Intelligence?

To support decision-making applications by providing access to prepared data

What is the main function of business analytics in Business Intelligence?

To allow users to create reports, queries, and conduct data analysis

What is the purpose of data mining in Business Intelligence?

To look for hidden patterns in data for predicting future behavior

What is the role of OLAP (Online Analytical Processing) in Business Intelligence?

To enable users to interactively analyze multidimensional data

What is the primary objective of Business Performance Management (BPM) based on balanced scorecard methodology (BSC)?

To optimize overall performance of an organization

Which type of users in Business Intelligence (BI) are typically met by tools such as dashboards?

Executives - top managers of any organization

What is the major theory of Business Intelligence (BI) that distinguishes it from transaction processing?

BI is not transaction processing, hence OLTP vs. OLAP

What is the primary focus of Online Transaction Processing Systems (OLTP)?

Handling a company’s routine ongoing business activities

What distinguishes Online Analytic Processing (OLAP) from Online Transaction Processing Systems (OLTP)?

Enabling user queries and analysis of historical data

What are the three major types of BI users according to the provided text?

IT staff, Power users, Executives - top managers of any organization.

Study Notes

Data Mining Methods and Applications

  • Data mining activities can lead to unexpected results, requiring creative decision-making.
  • Prediction methods use variables to predict future values, while descriptive methods find human-interpretable patterns.
  • Data mining tasks fall into four categories: classification, clustering, association rule discovery, and sequential pattern discovery.
  • Classification, a supervised induction method, is commonly used for analyzing historical data and predicting future behavior.
  • Data clustering algorithms partition a database into segments with similar qualities, aiming to create groups with maximum similarity and minimum similarity across groups.
  • The major difference between cluster analysis and classification is that classification sorts cases into groups, while cluster analysis identifies common characteristics shared by group members.
  • Association data mining establishes relationships between items that occur together, often used in market basket analysis.
  • Sequence discovery identifies associations over time, tracking elapsed time between events and frequency of occurrences.
  • Two types of data mining are hypothesis-driven, starting with a proposition, and discovery-driven, uncovering unknown facts.
  • Data mining is used in various business sectors including banking, retailing, manufacturing, marketing, government, health, airlines, and broadcasting.
  • Understanding customer behavior in retail involves analyzing demographic data, transaction data, and online interaction data.
  • In retail, data mining focuses on web analytics, gathering web statistics to track customer behavior and adjust websites to meet customer needs.

This quiz explores the concept of data mining and its applications in business intelligence. It covers the use of statistical, mathematical, and machine learning techniques to extract valuable information from large databases.

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