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Excel Importing Guide

Revision as of 12:56, 28 August 2014 by Jeferson (talk | contribs)

The instructions below will help you make sure your Excel file is formatted correctly to be imported as a TaticView data source.


You can download a sample file here: Sales.xlsx

If you still have problems importing, try Importing Problems.


Headers

Headers are not mandatory, but if present they should be contained in just one row (the first one) and not be in merged cells.


Headers wrong.png Headers right.png


Avoid Multiple Data Tables

Only one table by spreadsheet can be imported. If the data in two different tables can not be joined, they must be imported as two separated data sources.


Multipletables wrong.png Multipletables right.png


Fix/Remove Empty Rows/Columns

Remove or Fix (by adding at least a header) to full empty rows and columns.


Emptyrowcolumns wrong.png Emptyrowcolumns right.png


Remove Merged Cells

Data should not contain merged cells for repeated values. All cells must be unmerged and values must be repeated for each cell.


Mergedcells wrong.png Mergedcells right.png


Remove Aggregate Rows

Files should not contain aggregation rows cells for repeated values. Delete that rows, as TaticView will make all necessary aggregations in run-time.


Summaryrows wrong.png Summaryrows right.png


Remove All Table External Items

Files should only contain the data table to be imported. All non related data, as main headers, images, charts, must be removed prior to importing.


Unrelatedinfo wrong.png Unrelatedinfo right.png


Check for Invalid Numeric Data

Numeric columns should be formatted in Excel prior to uploading the file. This can be done by using the “Convert to number” feature in Excel for all numeric fields. Value data fields can not contain text or symbols, as they cannot be aggregated. When data is not available, cells may be left blank or as zero (0).


Nonnumeric wrong.png Nonnumeric right.png


Normalize your Data

Normalization of data (where column headers can be converted into attribute values) will result in better analysis. To do this, first convert metric names to represent attribute values, and then consolidate all metric columns into a single column of data.


Normalization wrong.png Normalization right.png