Date Blender Overview
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The Data Blender is a Data processing tool, or an ETL type tool, (Extraction/Transform/Load) and is drag and drop. The forte of the Date Blender is that a user can more easily manipulate data and has more features. A common use of the Data Blender is to funnel data through a series of transformations, to generate a uniform data set and then allows for the stacking of tables. The final output is then an aggregate of all data.
Primary Customer Usecases are:
Scenarios where Advizor needs to ‘Append’ Data.
Scenarios where Advizor needs to ‘Transpose’ Data.
Automated e-mailing of Reports.
The following, is an example of a Data Blender job flow:
Commonly used 'Compile' Functions:
Append – Append multiple ‘inputs’ data rows.
Aggregate – To aggregate data across multiple tables and from multiple sources. Advizor this a ‘Table Rollup’ or ‘Stacking Tables’.
Transform – Is an Advizor Analyst Expression builder. In order to make data more uniform, Advizor Analyst will sometimes perform calculations.
Rank – Is integrated within Advizor AnalystX and ranks the different rows of data, based on the value in a cell.
Transpose – Similar to a pivot table, in excel. Advizor Analyst Chart selections are performed across rows, so converting Column data into Rows, allows more flexibility in selecting data.
Reverse – Performs the opposite of Transpose. Reverse converts the Rows into Columns. However; given that Advizor prefers converting Columns into Rows; this option isn't utilized very often.
Lookup – Can lookup a columns data values but Advizor does not use this option very often.
Quantile – Assign data rows to a Quantile; which Advizor Analyst can utilize via. the Expression Builder.
Median – Calculate the median of a columns data; which Advizor Analyst can also utilize via. the Expression Builder.
Commonly used 'Process' Functions:
Filter – To query the data.
Sort – Sort all data rows.
Cache – Cache all data rows into a temp file.
Convert – Convert a Column’s data to a new type.
Rename – Rename and/or exclude columns.
DeDup - Remove data rows, with duplicate values, in a selected Column.
FindDup – Find data rows, with duplicate values, in a selected Column.
Commonly used 'Output' Functions:
Output – Write the data rows to a table.
Report – Write the data rows to a report. Also, Advizor Analyst uses this to send automated e-mails.
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