Data Flow Through Pricefx

Data is at the core of our Pricefx suite and essential for Analytics and other modules within Pricefx. Here we’ll provide a basic understanding of the data flow into the system.

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Raw, unprocessed data is loaded into the system through a Data Feed. This is then structured and presented as a data source, which feeds into a Datamart or data table containing all the information for use across the system.

Datamarts

A Datamart is essentially a way to join the two or more sets of data to allow you to run queries, set prices, create charts and optimize your pricing across both sets of data. But the Datamart doesn't contain the data, it simply, dynamically joins the data from the various data sources every time a query is run. This means that when you select a datamart for your query it refreshes with the latest data in the sources that it uses.

The process whereby the data moves from a Data Feed to a Data Source or Data Source to Datamart is called a Data Load and happens automatically, although it could be set on a schedule.

So now you have a datamart, that joins together the transaction history of your customers and you can interrogate the information based on what products the customer has purchased, how much they paid, what your gross margin was, etc…

If you have a look at the Analytics Menu you may see the Data Manager menu item, although this is predominantly presented to Administrators and is not something that you need to be concerned with.

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Datamart Viewer

Pricefx has created a Datamart Viewer for business users, under the Data Analyzer tab, which allows you to view the Datamart as well as the underlying Data Sources and data to ensure that you can view the data and be comfortable that you understand what information it contains before you create your charts or use it elsewhere in the system.

If you click on the Datamart Viewer on the menu, you can see it presents a dropdown menu where you can select various Datamarts that you have access to.

Select a Datamart and you're presented with the information from that Datamart. You can now see the data that you will have access to as you create your analytics.

You can see various fields available in this Datamart, like how many rows of data it contains and you can filter the information column by column, simply by searching below each column heading.

For example, if you need to filter the records by currency type, you can enter it in the Currency column to display a single currency and by simply clicking on the cross next to the filter you can remove that and it refreshes back to the default view.

You can also use the advanced Filter to filter by more than one currency, so you simply click on the advanced filter button on the top-right corner.

Then create a rule to filter the Currency column to equal [Currency 1] and add a second rule using the OR delimiter and add [Currency 2].

Click Apply and the results will now display only rows with the currency or other data you’ve filtered.

To remove the filters, simply return to Advanced Filters, remove the rules using the Delete button, and click the Apply button to return to the default view once again.

If you're only ever interested in the filtered information you can simply add the rules, apply the filters and then save this as a new preference, which will allow you to easily access this view next time without having to set up the filters each time.

You can also select fields to display and remove all fields that you may not want to view.

Across the top, you can see some more options. You can Refresh the data at any time if you think that there has been an update to the underlying information.

You can Truncate the data, so if you've filtered the data and want to remove all the other information clicking on Truncate deletes that data from the view. But remember that this is simply a dynamic datamart and so you're simply removing the information for the datamart and not from the data source. 

Purging a cache simply removes the last recently used set of data from the system memory, but you shouldn't need this as the cache is updated when the data changes.

The Status History button provides details of the latest data loads, what their status is, the number of items updated as well as when the data load started and completed.

This is useful to ensure that when you're using a particular data source you're sure that it's up to date or if it's updated infrequently, you can identify the date parameter that you can use when producing your analytics.

The option to Export XLS or CSV allows you to export the currently displayed data as you see it.

You can then also click on the Dropdown to Select the Data Source.

You now have the Datamart Viewer on the top half of the screen and the Data Source Viewer below.

The data source is the actual data table that the Datamart interrogates when you run a query and is the source data.

You can now compare the information, you can click on the Status History button to get details of the latest data loads, status, number of items updated as well as when the data load started and completed.

But because this is a real data table you can also apply mass edits and export the data as well.

You can also filter the information and save your viewing preferences as with the data mart.

So now if you head over to create one of the many charts in Pricefx Analytics, you can simply select the source of the data, in this case, the Standard Sales Data Datamart, apply the parameters and you have the chart you require.

But Datamarts can be used across the organization and you may not want to make changes to them that could impact how your colleagues use the data, so if you'd like to create your source of data where all the information you need is aggregated you can head over to Rollups.

Rollups

Rollups simply allow you to roll data up to a higher level of aggregation. It gives you the capability to select the data source and apply your filters to create a specific source of data for your work.

So let's click on Rollups and give it a go.

Here you will see a blank rollup screen, you must select your data source. In this example we select the Standard Sales Data Datamart from our demo data.

You can see the base currency is set to Euros, which means that all the information displayed will be in Euros. Any non-Euro values will be converted to Euros based on the currency exchange rate table.

You can use the Generic Filters button to set two or more generic filters. For this example, two generic filters were selected to filter by EUR or AUD, then you decide how you want to group and measure that data.

For this example, you can group everything by Customer ID and add the Gross Margin and Pocket Margin as the measures.

And you can see the aggregated information now appear in a data table. Save the Rollup and then head back to the Data Analytics. If you need to make any changes, you can click on the Load Rollup button to edit your rollup.

If you refresh the browser you can now see your saved Rollup as a new data source in the Chart Data Source drop-down listing and can select it to create your bar and line chart in Analytics.

You can add Customer Id on the X-Axis and Margin on the Y-Axis.

But you may also want to see the Pocket Margin, so you can go down and add a new series to add the Pocket Margin as the Y-Axis, apply and refresh and you will now have a chart that is exactly what you need, taking into account the EUR and AUD sales data, presented by the customer, displaying the Pocket Margin and Margin across a line chart.

You can now save the chart and reload it and refresh it whenever you need it.

You can use the rollup as a data source across all the charts to create the data visualizations as you need them. 

This covers data sources, the datamart viewer, and creating your data source with rollups.

You should now be confident using and creating data sources within Pricefx and if you need more information why not watch the accompanying video tutorial.