Join Ron Davis for an in-depth discussion in this video Key concepts, part of Microsoft Business Intelligence Stack in Depth.
…Key concepts.…The mining structure.…The mining structure defines the type of data from which mining models are built.…It specifies source data view, the number and…types of columns and an optional partition into training and testing sets.…A single mining structure can support multiple mining models that…share the same problem domain.…The most basic part of a data mining question is the attribute.…Which is a single piece of information about an example.…
Examples include a customer's gender, age, marital status.…A product's category, volume, color, et cetera.…Other attributes can be whether the customer purchased a particular product,…or even how much of that product they bought, or how much they liked it.…When choosing attributes for data mining, you should be careful to…choose attributes that are likely to be relevant to your question.…And provide information that can be used by the data mining algorithm.…Many attributes are not suitable for…data mining at least, not in the form that they exist within your data.…
- Working with data sources and data views in SQL
- Understanding the star and snowflake database schemas
- Working with the SQL 2012 semantic model (aka tabular mode)
- Using Data Analysis Expressions (DAX)
- Using Excel Web Parts to connect to spreadsheets
- Building dashboards with key performance indicators (KPIs) and reports
- Understanding the Microsoft data-mining process
Skill Level Intermediate
Microsoft Business Intelligence Stack Fundamentalswith Ron Davis43m 39s Intermediate
1. The Traditional Multidimensional Model
2. The New Tabular Model
3. Basic Power Pivot
4. SharePoint Excel Services
5. Basic PerformancePoint
6. SharePoint Visio Services
7. Data Mining and Predictive Analytics
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