Summary: Data Mining For Business Analytics Concepts, Techniques, And Applications With Xlminer | 9781118729243 | Galit Shmueli, et al

Read the summary and the most important questions on Data Mining for Business Analytics Concepts, Techniques, and Applications with XLMiner | 9781118729243 | Galit Shmueli; Peter C. Bruce; Nitin R. Patel

• 1 Introduction to BI & BM

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• Which analytics methods are there

  Retrospective:
  1. Descriptive analytics: use data to understand past and present (SQL, OLAP)
  2. . Diagnostic analytics – Explain why something happened
  
  Prospective
  3. Predictive analytics: predict future behavior based on past behavior (Time series, clustering, decision trees, NN)
  4. Prescriptive analytics: make decisions or recommendation to achieve the best performance (simulation, optimization, AI)

• Which business intelligence methods are retro and which are prospective?

  Retro: descriptive and diagnostic
  pro: predictive and prescriptive

• Which function do we use with descriptive analytics?

  – Database management – Data warehousing framework – Business reporting, OLAP databases, dashboards

• Which function do we use with predictive and prescriptive analytics?

  – Data mining process – Regression models – Naive Bayes & k-nearest neighbor – Decision trees – Association rules – Clustering

• One view: what is BA?

   predictive + prescriptive analytics

• What is the BI process?

  The objective of the BI product is to provide historical, current and predictive views of business operations. Information/knowledge that could relate to: - Understanding customer preferences - Coping with competition - Identifying with opportunities - Enhancing internal efficiency BI solutions support the BI process by utilizing BI tools.

• Which BI tools and techniques do we know

  - Data warehousing
  - Knowledge management
  - Query and reporting
  - Online analytical processing
  -Digital dashboards
  - Data, process, and text mining
  - Statistics
  - Visualization

• What is Business Intelligence Architecture

  The idea: data flows through the veins of the organization. For example: a customer buys something, than a certain event is created in the sales database. All the different databases have a ‘local’ view on the business. Some parts of the data are interesting for decision making. To use the data, ETL is used. After the ETL the clean data is stored in a data warehouse. After that, a large set of techniques is available to provide insights for the decision maker.

• What is a database?

  Database = a collections of related tables, designed, maintained and utilized by multiple users, with software to update and query the data. So, it’s not comparable with multiple excel tables, because database tables are related to each other.
  
  A database is also an environment to Manipulate data using a query language (e.g. SQL), and it is often an client/server architecture. The clients are active (low processing and very thin) and the database server is relatively passive (but does a lot of processing, is thick).

• What is a DBMS

  is the software that controls the data (Oracle, DB2, MySQL, MS Access) Internal memory is very important for a database