With our PaperCut MF data now nicely organised into our processed data table, we can start to make use of it inside of our datafeeds.
With Intuitive for PaperCut MF, we have 8 pre-defined datafeeds – each with its own unique purpose or format of aggregation.
Each of these feeds is enumerated, and is listed down below:
- Departmental Statistics – 12 Month
- Filter Print Log Attributes
- Filter Printer Attributes
- Filter Account Attributes
- Printer Analysis – YoY
- User Data – 12 Months
- Printer Output – 30 Days
- Summary – 12 Months
Starting at the top with Departmental Statistics, this is a datafeed that retrieves data from the SQLite database from the past rolling 12 months. It achieves this via a WHERE clause at the bottom of the datafeed editor. It bases the rolling 12 month on a parameter for ‘now’ and calculates from ‘now’ to the prior 365 days. The date of ‘now’ is from the point of the datafeed refresh, which is early in the morning around 4 am. Therefore, when showing data onscreen, the data is a snapshot of how PaperCut MF looked like at that point in time, rather than the ‘now’ of when a user accesses the dashboards.
Inside of this datafeed is a SELECT statement primarily from the Printer_Usage table. It retrieves the month (YYYY-MM not DD-MM-YYYY) along with the device information, broad-job information (such as the job type, colour composition and costing) along with the volume-level information.
The purpose of this datafeed, which is also its name, is to provide overall stats relating mainly to the Departments / Accounts from PaperCut MF.
One of the reasons as to why there are 8 datafeeds is to aid in performance of dashboard usage for on-premise systems. If the objective of the dashboard is to provide summary-level information without any granular detail, it would therefore be difficult to view and operate if that data has been retrieved from a job-level datafeed, as the dashboard would need to retrieve potentially hundreds of thousands of records, to then just aggregate it inside of the components.
The next three feeds “Filter Print Log Attributes”, “Filter Printer Attributes” and “Filter Account Attributes” are our filter-specific datafeeds. Where we use filter components in our dashboards, instead of using those components against the larger datafeeds, we instead create three separate filter datafeeds to aid in performance. Consider a scenario where we have two filter components for a “Job Type”. One has the data retrieved from the Departmental Statistics, and the other the Print Log Attributes. The first component would be scanning through potentially hundreds of thousands of records to retrieve a handful of unique entries for each of the unique job types. The second, given an aggregated view of filter-specific attributes, may only have to sift through hundreds of unique combinations. The outcome of this filter datafeed means that we can aid in dashboard refresh times and filter component operation.
The contents of those three feeds are specific to their areas. Whilst they all contain a “Month” for dataset linking (see the dataset module for more information), the Print Log Attributes contain the job types and colour compositions, the Printer Attributes contain the Printer/ Device information, and the Department / Account Name information.
Moving onto “Printer Analysis – YoY", this, as the name suggests, is a year-on-year datafeed. The structure is very similar to the Departmental Statistics but also contains additional calculations for the environmental values and other miscellaneous totals.
This feed is used by our Volume Analysis dashboard for comparing year-on-year trends, and in our Cost & Volume and Environmental reports for the same purpose. Detailed information has been scrubbed from this datafeed to instead give overall totals of information over the past rolling two years.
“User Data - 12 Months” is very similar to Departmental Statistics but instead has an aggregated view of the users that are performing jobs. There are crossovers in attributes that they both share, but again for the purpose of a dashboard, this feed is used when statistics need to be provided on a per-user basis, rather than just the cost-center.
One of the fields a lot of the feeds share is a null parameter / field. This is a flexible attribute for our datasets to use inside of components. It’s just a blank field that we can redefine based on whatever we need to show for that given purpose. For example, the datafeed may use the NULL Parameter, and where it’s blank (i.e. on every row), use some filler text for ‘Show All’ or ‘Show All Users’ etc.
The datafeed “Printer Output – 30 Days “ is our most detailed datafeed, which contains the rows of actual job-level information, such as the timestamp of when the job took place, the user who submitted it, the device it was performed on and the document name and extension. Naturally, as this is quite detailed, we therefore only request a rolling 30 day period. This datafeed is effectively an almost ‘raw’ look on the Printer_Usage table, since there is a small amount of aggregation taking place.
This datafeed is used by the dashboard “User Profile” and “User List”. These two dashboards need to be able to show users that have either performed jobs in the last 30 days and the exact job detail in that timeframe.
The last datafeed is the “Summary – 12 Months” datafeed. This is used exclusively by the Executive Summary dashboard for providing high-level statistics of the print estate over the last 12 months. Given the Executive Summary is the homepage for many users, it’s the dashboard with statistically the highest amount of usage. With that, performance is key when delivering this content to multiple users simultaneously. The contents of this datafeed are the months of operation, followed by the number of printers, users, jobs and accounts in that period of time, followed by the overall number of printed pages.
Regarding “Printed” pages, you may notice we refer to volumes by either the total pages, or printed pages. A shortcut to this is that if it states “Printed” it is usually the combination of “Print”and “Copy” pages. If it is a “Total Page”, it is all the job types, including Scan and Fax, but excluding Cancelled / Deleted jobs.