Excel Importing Guide

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Revision as of 17:54, 20 January 2015 by FuzzyBot (talk | contribs) (Importing a new version from external source)
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As instruções abaixo irão ajudá-lo a formatar corretamente seus arquivos Excel para importação no TaticView.


You can download a sample file here: Sales.xlsx

If you still have problems importing, try Importing Problems.


Cabeçalhos

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


Evite Múltiplas Tabelas

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


Corrija/Remova Linhas/Colunas Vazias

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


Emptyrowcolumns wrong.png Emptyrowcolumns right.png


Remove Merged Cells

Os dados não devem estar contidos em células mescladas. Todas células devem ser separadas e os valores repetidos para cada célula.


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

Os arquivo a serem importados devem conter apenas a tabela de dados. Toda informação não relacionada, como informações, imagens, gráficos devem ser removidos antes da importação.


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 seus Dados

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