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Finding Your Gerta: Asking Who Broke What in Spatial Data Terms

Finding Your Gerta: Asking Who Broke What in Spatial Data Terms

Last week in the #MarcoMonday-verse, we introduced you to a cheat sheet for your Data Diagnosis practices. Sample questions to be considered when analyzing spatial data inventories and health of enterprise networks were handed out. Smiles were illuminated. There was much glad to be had.

If you missed out on the fun, this guide is still available for viewing or download in last week’s post – and we are still interested in the questions you often look to address in your own health assessments. We will never not be interested, pinky promise.

In the meantime, I thought a way we could help to explore and fully understand the importance of keeping data in tip-top shape would be to address those questions that were outlined in the cheat sheet. I mean…how useful is a question if you have no way to find the solution?

To begin our journey on this Q+A quest, we will be thinking over the following:

What user is responsible for the most broken map documents and layer files?

Another way to word this question may be: Whom can I effectively throw under the bus?


Looking at you, kmalone.

I kid, I kid. What I do not kid about, however, are the ways to approach this. Outlined below are several methods for solving this riddle…

  1.  Filter Inventory by Brokenness and Ownership
  2. Generate User Profiles

Good – Filter Inventory by Brokenness and Ownership

One of the easiest ways to find both which files are broken and to whom they belong is to filter for these details within Integrated Marco Mystic. With this method, only the basic inventory is required. I wish it were more difficult just so you feel the slightest bit challenged. However, it is a straightforward process assuming you have already run the marco container tool from either the Integrated Marco Commander or Integrated Marco Mystic interface to generate a Spatial Data Inventory.

Within Marco Mystic, navigate to the search results page, focusing on the available filters – especially within the charting interface of the application. For instance, by focusing on the Broken and Owner filters, you can create a graphical representation of the amount of healthy (or unhealthy) files attributed to a specific user account. This may then be further defined by specifying the Data Type filter, if need be.

Alternate: Find Same Owner

Another way of hunting down this information within Marco Mystic can be found within the item page for each individual entry. Within the Owner field, the option is provided to find those entries with the same owner. Although it does not attest to brokenness, results may be filtered to provide an overview of this information.

Alternate: Direct Database Sleuthing

If you are willing to do the dirty digging, these answers may also be found directly within the database. For instance, the STATUS_ID field within the CONTAINER table denotes the health of the file when the inventory was created. Those files attributed with a 3003, 3005, or 3006 value were found to be “missing” according to the lookup table, STATUS_TYPE. “Missing” is a valuable indicator of brokenness.

Better – Generate User Profiles

Outside of Integrated Marco Mystic’s search and filter capabilities, the next best way to discern those users who are responsible for the most broken Map Documents and Layer Files is to run the marco user tool available from Integrated Marco Commander - or its equivalent within Marco Mystic.

Designed specifically for this type of assessment, the marco user produces a series of spreadsheets breaking down the file count for each user account found. In addition, a summary table is generated to tie them all together.

At a high-level view, the summer spreadsheet shows all user profiles found, followed by numbers for datasets, map documents, CAD files, and…you guessed it…broken data discovered for that profile. This view allows a quick look at those contributing the most and least to this data dilemma.

Drilling down into the individual snapshots, we see which of these broken files are attributed to each user. For instance, a look at the example below will show the paths, data types, names, dates, etc. for those nearly 1500 broken files found under Gerta’s account.

This knowledge can then be used to fix or remove any and all broken data, helping to clean up the system and get Gerta the data help she needs.

About This Series

In the coming weeks, we will explore ways in which to answer these common questions and get the most out of your spatial data. Want to jump ahead and tackle these for yourself? Follow the links below or view the cheatsheet here.

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