You can upload data from Excel and CSV files to eazyBI and then create reports, charts and dashboards from these data.
Please at first read about eazyBI cubes, dimensions and measures - you will need to understand multi-dimensional data model to be able to map source file columns to cube dimensions and measures.
Go to Source Data tab and select source file for upload.
If you upload CSV files then use either comma (,) or semicolon (;) field separators. Decimal values should always use periods (.) as decimal separators. Commas (,) in integer and decimal values will be ignored (e.g. if they are used as thousands separators).
If you upload Excel files then integer, decimal and date fields will be detected based on Excel cell formatting.
If source CSV file contains non-English characters then CSV file should be in UTF-8 encoding as otherwise you might receive error messages when previewing uploaded file.
If your original non-English data are in Microsoft Excel then upload these Excel files as Excel export to CSV does not support UTF-8 encoding.
After CSV file is uploaded you can click Preview button to specify source file columns mapping.
In source file preview screen you can enter data cube name where you would like to import your data. If this is new data set then enter new cube name (e.g. Sales cube if you are importing sales transactions). You can also import new file in existing data cube - in this case you can use either existing cube dimensions and measures or specify new ones (which will be added to existing cube during import).
It is recommended that CSV file has header row with column names - eazyBI will try to detect if your CSV file has header row or not. If eazyBI has detected it incorrectly then please change number of header rows (e.g. specify 0 if you do not have any header row).
eazyBI will try to detect each source file column data type based on first 100 rows of source file. Detected column types (string, integer,decimal, date or datetime) are shown below each column name. If some column type is detected incorrectly then you can change it (e.g. change from integer to string if this column might contain also non-integer values).
Next you need to map source file columns to cube dimensions and measures.
By default eazyBI will suggest to map string columns to dimension with name which is derived from column name (underscores replaced with spaces, each word is capitalized). If necessary then you can enter different dimension name that you would like to use in eazyBI.
You can map each column to separate dimension but sometimes it would be better to map several columns to the same dimension but different hierarchy levels. E.g. in this example it would be better to map country, state_province, city and fullname to the same Customers dimension with hierarchy levels Country (highest hierarchy level), State Province (one country expands to several states or provinces), City (one state or province expands to several cities), Customer Name (one city expands to several individual customers). It is important that in source file hierarchy level columns are always in the sequence from highest hierarchy level to lowest hierarchy level.
When you map several columns to the same dimension then you can select existing dimension name from list for next columns (delete suggested default dimension name to see list of available dimension names).
If you map several columns to the same dimension then it is mandatory to specify dimension hierarchy level for each column. By default hierarchy level name will be generated from column name (in the same way as default dimension name). If necessary then you can enter different dimension hierarchy level name.
If you would like to ignore some columns during import (do not want that these columns are imported) then you should leave dimension selection blank for this column.
Date or datetime column by default will be mapped to Time dimension. Time dimension after import will automatically create year, quarter,month and day hierarchy levels as well as additional weekly hierarchy with year, week and day hierarchy levels. Therefore you should not provide any dimension hierarchy level information in source file mapping as time hierarchies will be created automatically.
You should use one of the following date formats in your CSV file that eazyBI will recognize as date format and you will be able to import it as Time dimension:
- YYYY.MM.DD or DD.MM.YYYY
- YYYY/MM/DD or MM/DD/YYYY
The following datetime formats are recognized (currently only date portion of datetime value will be imported in Time dimension):
Measures and integer and decimal columns
Numeric columns (integer and decimal data types) by default will be mapped to Measures and you need to specify measure names for these columns (by default derived from column names). Measures are values that you would like to analyze across other dimensions and which will be aggregated by other dimensions hierarchy levels.
If you have other integer values (most typically e.g. identifier columns like customer ID or order ID etc.) in source file columns then do not map them to Measures - either enter corresponding dimension name or leave dimension name blank to ignore them during import.
When you have completed columns mapping to dimensions and measures then click Start import button to import source file data into specified data cube. If there will be any missing information in source file columns mapping then you will get error message about missing information and columns with errors will be highlighted:
If there are no columns mapping errors then source file import will be started in background and you will see file import status (and how many rows are imported) which will automatically refresh.
If all source file rows will be imported successfully then source file status at the end will change to Imported.
If there will be any errors during source file import then it will stop on first error with Error status. You can click on Error link to see detailed error message. Detailed error message will show line number together with line content and information about the error. Most frequent error is invalid quotes inside quoted string (in CSV files you should double quotes inside quoted string) or non-English character encoding (not in UTF-8 encoding).
If you have error in source file then you can fix it and upload file again with the same file name - you will need to confirm that you really want to replace uploaded file. When you will import replaced file then at first all previously imported rows from previous file will be deleted and after that rows from new file will be imported.
You can replace also successfully imported source files. E.g. if you regularly perform full export of your data from some source system then you can always use the same source file name and replace previous version with new one and replace all imported data with new.
You can also delete either successfully imported files or files in error status. When deleting source file you need to specify if you want to delete just source file or to delete also from data cube all imported data from this source file.
If you will import additional data with the same source file structure (e.g. if you each day, week or month import new data for this time period) then use unique file name for each time period.
If new source file has the same structure (same column names and data types) as existing imported file then columns mapping will be copied from already imported file. After clicking on Preview button you will be able to import it by clicking Start import button.
Note that all data cubes in one eazyBI account share the same dimensions. If you want to use the same dimension in different data cubes then use the same dimension name. If they are different dimensions then use different dimension names (even when you use different data cubes).
If you are using eazyBI standard integration with other source applications (e.g. Basecamp, Highrise, JIRA, Zendesk or Harvest) but you would like to add additional measures to your source application data cubes then it is possible to import additional measures from CSV files in existing source application data cubes.
But there is also risk that you will not prepare correctly additional data in CSV files which may result in damaged existing source application data. Please view additional data import example for JIRA Issues cube. If necessary contact eazyBI support and describe your need and we will help you prepare correctly CSV files with additional data.