Search for	Example	Results
A single word	`cat`	Topics that contain the word "cat". You will also find its grammatical variations, such as "cats".
A phrase. You can specify that the search results contain a specific phrase.	`"cat food"` (quotation marks)	Topics that contain the literal phrase "cat food" and all its grammatical variations. Without the quotation marks, the query is equivalent to specifying an OR operator, which finds topics with one of the individual words instead of the phrase.

Search for	Operator	Example
Two or more words in the same topic	`AND` `and` `+` (plus symbol) `&` (ampersand)	`cat AND dog` `"cat food"+milk` `"cat food"&"dog food"`
Either word in a topic	`OR` `or` `\|` (pipe)	`cat OR dog` `cat \| dog`
Topics that do not contain a specific word or phrase	`NOT` `not` `!` (exclamation point)	`NOT cat` `! dog`
Topics that contain one string and do not contain another	`^` (caret)	`cat ^ mouse`
A combination of search types	`( )` parentheses	`cat + (dog \| mouse)` `cat \| dog + (! mouse)`

IT Business Analytics10.10

Develop > Develop Content > Extend Content > Content Development Process > Data Modeling

Data Modeling

This stage is done completely in the IDE tool.

The IDE tool has the following ITBA DWH definition:

Target Entity is a Fact or Dimension.

Entity name along with column names is defined according to the Star-Schema Architecture.
Integration Entity is the source table representation.

Entity name along with column names and data types is defined according to source table design.
Source Entity is the actual and accurate representation of an entity to be extracted from the source.

It describes how and what data is extracted from the source. It is generated automatically according to the integration entity design. However depending on the extractor being used, it may require some changes as the automatic generation is targeted for the DB extractor only. Note that there are three types of extractor that you can chose in the source entity's properties: Direct (DB extractor), Fixed, and Rule (API extractor or Web Service).
Transformation Entity is the logical representation of all the transformations that are performed by the DWH during the data processing. It’s the accurate representation of the Target Entity.
Column Mapping - Source to target column mapping

The modeling approach:

The Solution Modeling Highlights:

Different functions are collaborating on same models simultaneously until reaching a final version.
Actually serves as a high-level DB Studio + ETL tool. No need to touch the DB directly.
95% of the solution is defined by this high-level modeling.