What Are Datapoints?

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A datapoint is similar to a field in a table, but with built-in dimensional linkages. It also has linkages back to sources and forward to measures, which provide a clear lineage from harvest point to presentation.

There are four different types of datapoints in PMF:


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Procedure: How to Edit Loadable, Generated, or User Entered Datapoints

Note: Most of the information for Loadable, Generated, or User-Entered datapoints are read-only. The only think you can change about them is their name or description.

  1. In the Manage tab, click the Datapoints panel button.
  2. Expand the Loaded Datapoints, Generated Datapoints, or User Entered Datapoints folder and select the datapoint you want to view.

    The Edit Datapoint panel opens.

  3. Edit the Name or Description of the loadable datapoint.
  4. Click Save.

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Derived Datapoints

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How to:

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Derived datapoints let you create calculations that include dimensional metadata. For example, you can create a series of derived datapoints that perform a series of calculations on Sales performance for your manufacturing company:

These datapoints can now be added up to become Total Cost (by Product, Location and Time).

You can then set Total Cost against your Sales (by Product, Location and Time) to calculate Profit.

You can also load precalculated Total Costs and Profit datapoints from an external Source, but there is no guarantee the data will be calculated in the proper order. If you use derived datapoints to calculate the values:



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Procedure: How to Create a Derived Datapoint

To create a derived datapoint:

  1. In the Manage tab, click the Datapoints panel button.
  2. Click New.

    The New Datapoint panel opens.

  3. Name the new derived datapoint.
  4. Drag the datapoints you need for your calculation into the canvas. Each datapoint must be separated by its operation, as shown in the following image.

    Derived Datapoints

    Calculations can also include constants. To add a constant, drag the Constant object into position on the canvas, and type in the constant value inside the Constant object.

    Separate datapoints for WebFOCUS functions are typically created during the source load, since capturing these calculations is done best in the first-generation in the lineage, during harvesting.

    For example, if you want to capture counts of a particular condition, rather than trying to save all those attributes somewhere so you can perform the filtering later, you can determine When, that is what filters should be true, for the count. You can then pull that count into a loadable datapoint. Approaching data this way allows you to make calculations in the lineage after this harvesting phase simpler for you to manage.

  5. Click Save. If the calculation is not complete, PMF recognizes this, and marks the derived datapoint as Incomplete. Incomplete derived datapoints do not participate in recalculation.


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Procedure: How to Change Datapoints

To change a derived datapoint:

  1. In the Manage tab, click the Datapoints panel button.
  2. Select the derived datapoint you want to change. The Edit Datapoint panel opens.
  3. Make your desired edits. You can change anything in a derived datapoint, including the name and its formula.

    Note:

    • Datapoints are included in formulas and linked to measures by reference, so renaming them changes their name through the entire system.
    • Altering the formula for a derived datapoint automatically flags its data, and any later generations in the lineage for that datapoint, including child derived datapoints and measure values, for a one-time wipe. If the data is also scheduled for reload, PMF performs that load after wiping the data.


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Procedure: How to Copy Derived Datapoints

You can make an exact copy of any existing derived datapoint. After making the copy, you can immediately alter it as needed. To copy a datapoint:

  1. From the Manage tab, click the Datapoints panel button.
  2. Select the derived datapoint you want to copy. The Edit Datapoint panel opens.
  3. Click Save As. You will be prompted for a new name for the derived datapoint, as shown in the following image.

    Save As window

  4. Click Save. PMF will make an exact copy of the derived datapoint. You can edit and save your changes at any time, and click Save As again if you want to make more copies. This datapoint is what will be loaded for editing.


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Procedure: How to Wipe Derived Datapoint Data

All loaded data from a derived datapoint can be wiped out or deleted in a single operation, because they are not attached to a source.

Note: Wiping data affects downstream datapoints for the datapoint you wipe. Every datapoint downstream is marked as having incomplete components. Incomplete components do not participate in recalculation.

  1. From the Manage tab, click the Datapoints panel button.
  2. Select the datapoint that needs to be deleted. The Edit Datapoint panel opens.
  3. Click the Wipe Data button. PMF will ask you to confirm the data purge.
  4. Click OK.

Note: It may take PMF a moment to purge all of the data.



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Creating Calculated Measures With Derived Datapoints

PMF allows you to create an unlimited number of calculations for your measures using special datapoints that store and process calculations, known as derived datapoints. These calculations can be based on one or more existing datapoints, of any kind, including loadable, user-entered, generated, and other derived datapoints. Note the following:



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Reference: Previewing Derived Datapoints

You can preview the data that PMF will generate by clicking the Preview tab, as shown in the following image.

Preview tab

The Preview tab generally shows rows that are new, or will be updated or deleted.

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Reference: Lineage and Recalculation With Derived Datapoints

Derived datapoints can have a complex, multi-part lineage, depending on their relationship to other derived datapoints.



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Reference: Derived Datapoint Lineage Tab

You can view lineage for all datapoints for any derived datapoint. Lineage shows the progress of data through PMF, from the external data harvested into datapoints, through any derived datapoints, and finally all terminal points in Measures. The Lineage tab displays the components in the generated source by default, as shown in the following image.

The lineage tab automatically displays the entire lineage. You can click the Collapse All button to hide the entire lineage.



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Reference: Derived Datapoint Load History

PMF keeps track of each load that is executed for each derived datapoint in the system, regardless of whether you loaded it manually or the load was called by the scheduler. This data is stored in a special logging section of the PMF data mart.

The History tab on each derived datapoint displays the history of all loads that have been logged.

The history of the derived datapoint shows:


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Loadable Datapoints

Loadable Sources manage Loadable datapoints. You can drill into any datapoint on a Loadable Source to view the specifics about the datapoint, or you can access Loadable datapoints from the separate panel button for them.


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Generated Datapoints

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How to:

Reference:

Generated datapoints enable PMF to create sample data for your models. With generated datapoints, you can:

Generated datapoints are designed for the following situations:

Important: Generated data should never be treated as real performance data. PMF 5.3.2 does not yet mark generated data as “unreal,” so use generated datapoints only for non-production work.



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Procedure: How to Create a Generated Datapoint

To create a generated datapoint:

  1. In the Manage tab, click the Datapoints panel button.
  2. Click New.

    The New Datapoint panel opens.

  3. Select Generated from the first drop-down menu.
  4. Name the new datapoint.
  5. Click the Dimensions tab and specify the dimensions and levels for which PMF will generate data, as shown in the following image.

    Dimensions tab

    Setting dimensions affects some options on the Rules tab, so if you know the dimensions you want to use for generating, set them first.

  6. Click the Rules tab and specify the rules PMF should use to generate data. The following options are available:
    Decimal Format

    Specifies the decimal format of the data generated:

    • The first character can be D (Decimal) or I (Integer).
    • The next characters are numbers to specify the total length of the field.
    • You can indicate a period and number of digits of decimal precision.

    Examples of typical decimal formats are: D12.2, I8, D20.6 and, I32.

    Method

    Controls how PMF will calculate the sample values:

    • Normal (Bell Curve) Distribution. PMF generates a range of values that favors the center of the numeric range you type in under Lower/Upper Bounds.
    • Uniform Random Distribution. PMF generates an even distribution of values that favors no point in the numeric range.
    Lower/Upper Bounds

    The lowest and highest number for the range of possible values PMF will generate. The numbers will be formatted using the mask you entered in the Decimal Format field.

    Data Sparsity

    Controls the amount of data PMF generates by letting you focus the data on dimensional choices:

    • None. Generates a Cartesian cross-product of all possible dimension values.
    • Dimensional Filters. You can specify filters for the dimension levels for the generated datapoint. To specify the filters, select this option and use the drop-down menus, as shown in the following image.

      Filter options

    • Train. You can base the dimension level values along which PMF generates data on another datapoint. This lets you keep a limited amount of data together.

      You can specify any datapoint to train from a loadable datapoint, user-entered datapoint, derived datapoint, or another generated datapoint.

    Recalculate all Derived Datapoints

    This option should remain enabled, unless you have a very large data mart and want to reserve recalculation for overnight or other offline processing.

    Note: This option enabled by default. To disable it, see Load Settings.

    Description

    A description of the datapoint.

  7. Click Save. If minimum necessary entries are not set up to generate data, PMF will mark the generated datapoint as incomplete. Incomplete components do not participate in recalculation.

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Reference: Lineage and Recalculation With Generated Datapoints

Generated Datapoints are primary sources for data in PMF. They are treated as first generation in any lineage, along with loadable datapoints and user-entered datapoints.



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Promoting a Generated Datapoint

Generated datapoints are used when you lack real data to prove that your model works, or they are needed for a demonstration. Once you are ready to use a working model with real data, generated datapoints are no longer necessary to feed your metrics.

To promote the generated datapoint:


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User Entered Datapoints

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A user entered datapoint is based on data entered by the end user and typically belongs to a user entered source.

To create a user entered datapoint, you must first create a user entered source. For more information, see How to Create a User-Entered Source.



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Lineage and Recalculation with User-Entered Datapoints

User-Entered data differs from standard loaded data in the following ways:

Note: User Entered data is treated as updated on the date of entry, and the downstream Datapoints and Measure copies are treated as loaded on the day they were scheduled to update.


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