It is utmost important to verify your data that you want to load into Swiftly and analyze using diagrams and charts. Without a clean data, you may be led into a wrong hypothesis and incorrect prediction.

So, before we begin slicing and dicing data using various charts available in Swiftly, we must clean any incorrect, incomplete, improperly formatted data via the validation process.

Swiftly make this job easy by providing you two-step verification and resequencing process where you can:

  • Verify the metadata of the data type used in your source file and decide whether they should be considered as Card or Queue. Read more about it here.
  • Review and select the correct use of card attributes, whether they should be treated as ID, name, filter, other or ignore.
  • Set the column type of each stage of your value stream, whether they are:
    • Ready: The first column where the cards that have been committed are placed. In Proto Kanban this corresponds to “ToDo”.,
    • In Progress: Any column where card is actively worked on.,
    • Wait: Buffer column where cards are waiting to be pulled.
    • Done: Last column where completed cards are placed. If no done column is present, any card that moves out of the board is considered done.
  • Organize the workflow stages or queues by dragging and dropping them to the correct order.

Read all the points mentioned in Simple Excel File Format section on the Load Your File Into Swiftly page.

Verify Metadata

The input metadata table provides you a hint of the data types used in various columns of your Excel file. These columns can either be a data type of date, number or strings and they should either be bucketed under Card or Queue attribute. Generally, a number or strings column like ID and Name should be under Card and date column should be under Queue attribute.

The Input Metadata table shows a column header in green if it detects the data under it as of Card attribute. If the data conforms to the data type as suitable for Card attributes like number or strings, then the total count of such data is shown with a tick mark against it.

In the above example, the data under the column id are of number data type, thus by default, belong to Card attribute.  All the value under the id column conform to number data type, so it is ticked in green.

Likewise, Ingress Lead Start Date column has the date data type and all the value under this column conform to the same data type. So, it is also ticked in green. and ticked in green. Moreover, being a date, the data in this column is used as a  Queue or Value stream attribute.

But, if you look at the Bus Proposal Done column, it has one error entry which does not conform to Date data type. Rest of the 120 rows in this column have a date value. So, the exception is shown in orange color.  When you click that entry,  the data type changes to String and further details of that entry is highlighted in the same orange color in the Sample Records table.

The Sample Records table shows a couple of inconsistent data with the row number so that you can revisit your source file and rectify the exact cells.

Verify Card Attributes

You must review and select the correct use of the card attributes which have been detected by the system and shown in the Input Metadata table. The correct use of the card attributes also determines how they are used in the analytics.

Read the following definition of various types of attribute so that you can select the correct one from the drop-down:

  1. id: column to be used as id for the card
  2. name: column to be used for name or short description of the card
  3. filter: Only string attributes with small number of unique values can be used as a filter. The filter specifies that these values are shown in the filter section of the analysis and can be used to filter the dataset.
  4. other: other attributes, that are loaded and can be used for pivot analysis, but are not part of the filter.
  5. Ignore: these attributes are not loaded.

Reorganize Value Stream

Drag and drop the column headers (which are identified as Queue in the Input Metadata table) to organize the value stream in correct order that maximizes left to right flow. Select the correct type for each column.

  • Ready: The first column where the cards that have been committed are placed. In Proto Kanban this corresponds to “ToDo”.,
  • In Progress: Any column where card is actively worked on.,
  • Wait: Buffer column where cards are waiting to be pulled.
  • Done: Last column where completed cards are placed. If no done column is present, any card that moves out of the board is considered done.

 

 

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