You can upload data to your workspace using the LDM Modeler and start immediately analyzing it.
To do so, upload a CSV file with data in the LDM Modeler. You may or may not have a logical data model (LDM) in your workspace already. The CSV file is added as a dataset to your LDM, the data is immediately available in your workspace, and you can start analyzing it in Analytical Designer.
Make sure that your CSV files meet the requirements described in CSV File Requirements.
Here is an example of what your CSV file may look like:
order_line_id,order_id,order_status,date,product_id,price,quantity 10668-9VYN74-2,10668-9VYN74,Cancelled,2016-07-12,210,100.33,1.00 10697-7GBN87-1,10697-7GBN87,Delivered,2017-12-05,310,39.35,1.00 10907-0TPH53-3,10907-0TPH53,Delivered,2015-03-28,220,50.40,1.00 10778-7INQ32-1,10778-7INQ32,Delivered,2018-02-08,230,78.40,1.00 10240-3SBQ40-3,10240-3SBQ40,Delivered,2017-05-07,160,21.49,1.00 10356-7ZBU60-1,10356-7ZBU60,Cancelled,2015-03-01,140,21.49,1.00 10700-0ACT49-1,10700-0ACT49,Returned,2019-02-20,150,21.82,1.00 10175-0YRN35-3,10175-0YRN35,Delivered,2015-04-11,150,19.15,3.00 10152-6HOB25-1,10152-6HOB25,Cancelled,2016-03-04,140,29.67,1.00
- In the LDM Modeler (for how to access the LDM Modeler, click here), drag your CSV file and drop it in the canvas area.
The file preview opens. For example:
This preview shows the data from your file. Based on the column names and the contents of those columns in the CSV file, the column names and the types of the data are suggested for the dataset that will be created from this file.
- Non-numerical data is auto-detected as attributes (see Attributes in Logical Data Models).
- Numbers are auto-detected as measures (or facts; see Facts in Logical Data Models).
Dates are detected as dates (see Dates in Logical Data Models).
In an LDM, dates are managed through a separate object, the Date dataset (see Dates in Logical Data Models). If your CSV file contains dates, not one but two datasets will be added to your LDM: one Date dataset for the dates, and the other one with the rest of information. These two datasets will be automatically connected with a relation (see Connection Points in Logical Data Models).
- Review the suggested column names and the data types for the columns. If needed, change the names and/or the types of data.
For example, a column containing numeric identifiers can be detected as a measure. However, the identifiers are usually non-measurable descriptive data, and therefore must be an attribute. In this case, you need to change the type of the data for this column.
You can also do the following:
Set some attribute as a primary key.
The primary key defines the unique identifier for a row of data in a file and serves as a connection point that allows you to connect this dataset to another dataset. In other words, you will be able to create a relation between the dataset that you are going to create and another dataset in the LDM.
A relation between two datasets allows you to use information from one dataset to slice the data in the other dataset. For more information about primary keys, see Primary and Foreign Keys and Connection Points in Logical Data Models.
If you do not set the primary key now, you will be able to do it after the dataset has been created (see Update a Logical Data Model).
- Set some attribute as a reference to another dataset (this dataset must already exist in the LDM). The reference serves as a foreign key, and a relation between these two datasets will be created after you import the CSV file. For more information about references, see Primary and Foreign Keys and Connection Points in Logical Data Models.
- When you are done reviewing, click Import.
The CSV file is imported, and the dataset is added.
Notice the following:
- Depending on whether the CSV file contained facts, the dataset is color-coded with orange (the dataset contains only attributes and no facts) or green (the dataset contains at least one fact). For more details, see Datasets in Logical Data Models.
- If the CSV file contained a date, the second dataset - the Date dataset - is also added and is connected to your dataset.
- If you set some attribute to be a primary key, this attribute is noted with an orange key icon ( ).
- If you set some attribute to be a reference to another dataset, this attribute is noted with a gray key button ( ), and a relation is created between the newly created dataset and the referenced dataset.
- If you have other datasets in your LDM, decide whether you want to create a relation between the newly added dataset and any other dataset in your LDM. If yes, do so (see Update a Logical Data Model).
- When you are done, click Publish to publish the logical data model to your workspace.
You are prompted to choose the mode of publishing. The Preserve data mode is selected by default.
- Keep the Preserve data mode, and make sure that the Upload data from imported CSV files checkbox is selected.
- Click Publish.
The publishing process starts. When the publishing completes, you see a message that the LDM has been published. Close this message.
The data has been uploaded to you workspace, and you can immediately start analyzing it. To do so, click your username in the top right corner, and select Analyze data. You are redirected to Analytical Designer, where you can create insights from your data. For more information, see Create Insights.
When you get an update for the data that you have uploaded to the dataset, upload the new data to the dataset (see Update Data in a Dataset in the Logical Data Model).