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Data Mining

Knowledge of tools, techniques and practices in data mining technologies used to acquire essential business information.

Behavior Statements

Proficiency Level 1 - Basic understanding

Explains basic data mining concepts using data specific language.

Describes current data mining applications used in the organization.

Names one or more data mining software tools used by the organization.

Explains how data mining contributes to business intelligence.

Proficiency Level 2 - Working experience

Participates in the design and development of data mining applications.

Assists in the analysis of information in the process of data mining.

Describes the activities involved in preparing data for data mining operations.

Explains the differences between verification and discovery models in data mining.

Applies data mining techniques: decision trees, association rules, link analysis, clustering, etc.

Proficiency Level 3 - Extensive experience

Utilizes a variety of data mining tools, techniques and applications.

Participates in benchmarking activities to identify best practices in data mining processes.

Expounds on specific data visualization formats to effectively communicate data mining results.

Consults on suitability of neural networks versus OLAP systems for given data mining applications.

Articulates the pros and cons of data mining applications produced by diverse software vendors.

Promotes the value of data mining for business managers.

Proficiency Level 4 - Subject matter depth and breadth

Provides expertise on the development and implementation of complex data mining applications.

Guides others on tools and techniques used to apply data mining processes to specific business needs.

Evaluates data mining tools and acquires those that benefit the business.

Creates and justifies the business case for applying data mining processes to CRM or ERP functions.

Reviews data mining applications frequently to ensure that false conclusions are not produced.

Makes recommendations for business process changes based on data mining results.

Interview Questions

  • Tell me about a complex problem you encountered when using a certain data mining product. How was this issue diagnosed and resolved?
  • Could you illustrate the pros and cons of different data mining applications produced by diverse software vendors?
  • What types of data mining tools and applications have you used in the past?
  • How did you ensure your data mining tools and applications meet the needs of different functions or clients?

Titles with Shared Competencies