Date Blender Overview

For additional Tutorials related to the Data Blender, please visit the following Online Help.

For Training Videos, related to the Data Blender, please visit the following Video Tutorials

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:

1. Scenarios where Advizor needs to ‘Append’ Data.

2. Scenarios where Advizor needs to ‘Transpose’ Data.

3. 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.