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titleStep 3 Import the data
  1. Hover over the BusinessData stream and select 
    Insert excerpt
    _run_analysis
    _run_analysis
    nopaneltrue
    , then click Yes to confirm.
  2. Close the confirmation messages.
  3. To check that the data has loaded into the stream, hover your mouse pointer over the stream and select 
    Insert excerpt
    _stream_views
    _stream_views
    nopaneltrue
     then select 
    Insert excerpt
    _view_default
    _view_default
    nopaneltrue
    . PhixFlow displays the data it has loaded into the stream.


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titleScript / Details

Step 1

You now need to load the spreadsheet that contains the data into your application. 

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  • automatically configures the file collector properties to upload the file
  • creates a stream ready to hold the data. Streams are like PhixFlow's internal spreadsheets. 

Step 2

Script

If you look in the stream properties, you can see PhixFlow had named the file using the file collector name. It already has the list of attributes - the table columns - from the first tab in the spreadsheet. 

Key concept

At this point the stream knows about the data, but does not contain any data. This is the time to check that stream properties and the data types and sizes are correct. You cannot make changes to the attributes once data is loaded.

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Step 3

You can now load the data into the stream.

  • In the model, hover our mouse pointer over the BusinessData stream and select Image Removed Run Analysis.
  • In the confirmation window, click Yes to confirm.
  • In the bottom left of the screen, PhixFlow shows some confirmation messages. Close these.
  • We can now check that the data has loaded into the stream. In the model, hover your mouse pointer over the stream and select Image Removed Stream Views then select Image Removed Default View. This simply shows the data using a standard table view. You can see that the same data from the Excel spreadsheet is now loaded in the stream, with the additional columns we added to the Attributes.
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titleAdvanced or move?

Before you start any PhixFlow project, it is important to take time to understand your data.

  • What is your data? Do you need to represent people, places, products, money, time? These are the data entities.
  • How does the data connect? These connections are the data relationships.  
  • How will you represent the data in PhixFlow? This depends on the attributes the data has.
  • Is the data "clean" or do you need to tidy it up?
  • What data is missing?  PhixFlow can combine existing data from different sources and use it to calculate additional data.
  • What volume of data do you need to handle? For very large data volumes, you will be able to use modelling strategies to process data efficiently. 
  • What do you need to do with the data? What is the business problem you want to solve?

Remember that you can:

  • PhixFlow can connect to data stored in external databases (list or link?) or data files in a range of formats (list or link?)
  • PhixFlow analysis models are a powerful tool that you can use on any data project. Analysis models can help you to improve your data integrity, by 
    • identifying missing data, duplication and variation 
    • reconciling data in different files or systems.
  • The Introduction to Modelling Course shows how to do this
  • set up your own styles and palettes to create completely customised layouts. The Building Applications Course goes through this process.

You can represent your data and requirements in an Entity-Relationship Diagram (ERD); see Wikipedia. It can help you to understand the data entities, their attributes and relationships. An ERD shows you the data architecture. As well as clarifying the data you already have and what you need to calculate, an ERD can help you identify:

  • static data: once added is unlikely to need updating. For example, the list of possible salutations:
    • Mr, Ms, Dr, Sir, Lord
  • control data, that PhixFlow uses for  screen input, for example data that is displayed in a drop-down list.
  • CRUD data, that PhixFlow will be able to create, read, update and delete.

Within PhixFLow it is a good idea to be consistent, at a minimum within an application. You can use prefixes to distinguish CRUD or control data from static data. During the planning phase you can set up a naming policy.