Tuesday Tech Bytes - Adobe Analytics - Week 3 - Use Case/Success Story

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For this week's tech byte, I'm going to talk about the Data Dictionary and the importance of good documentation. If you missed the past weeks, you can check them out here:

Tuesday Tech Bytes - Week 2

Tuesday Tech Bytes – Week 1

When building your implementation one of the most important steps is keeping good documentation so that when you (or those that come after you) want to understand what data is being captured, you have a solid reference. In the past this would typically be done in an SDR (solution design reference) external to Adobe. There still are some benefits to having external documentation, but now Adobe has made it possible to keep some of your documentation within the workspace platform using the Data Dictionary.

What is the Data Dictionary?

The Data Dictionary contains a list of all your components, including your custom metrics and segments. It provides you an opportunity to add a description and tags, as well as “always include” or “always exclude” components for the frequently used with and similar to comparisons. Individuals with admin access can curate this information for their organization. For Adobe default components (like “Visits”), the description option isn’t available, but all of the others are still able to be edited.

How to use the Data Dictionary

There are two different views of the Data Dictionary – what admins see and what general users see. I’ll start with general users. When you open the Data Dictionary, you’ll see a list of your components, the standard search bar, and your report suites on the left, and on the right you will see some quick filters.

For general users, this is a great way to see what information your admins have made available about all of the components in your implementation. The quick filters on the right will limit the components list to just that specific type. Or you can use the search/filter option to find what you’re looking for. Once you click into a component, you’ll see the description (if one has been added), and whether or not it has been approved. For custom metrics and segments, you’ll also be able to see the definition of the component and a data preview like you would see in the metric/segment builder screens.

For admins, you get all of the above features, but you also have access to the Data Dictionary Health. This will give you a snapshot view of the completion level of the Dictionary. Adobe has some great documentation about keeping your Data Dictionary healthy. This view has the option to view all components with each type of issue, making it easy to find the ones that need to be updated.

One of the best options is to look at components that have duplicate names or definitions (if any exist). If they do, it helpfully groups them together based on the name/definition so you can easily compare them and clean up duplicates.

For all of the components you will see them either as approved or needing approval, and an option to edit them.

Once in the edit screen you can add a description, components that it’s frequently used with, components it’s similar to, and tags. Once you hit save all of the information that you’ve added will be available to all of the users in your organization that have access to that component.

Benefits of the Data Dictionary

If you’ve never updated any information in the data dictionary, doing so for the first time can seem like a daunting task. But even once you have it set up, maintaining it requires a lot of dedicated effort. Despite all the effort, there are reasons it’s worthwhile.

Imagine you’re new to an organization, it’s your first day looking at your company’s workspace. There’s hundreds (or thousands) of components that are specifically designed to fit the company’s needs. How do you know what to use to build your first report? The data dictionary is a great way to get familiar with the available components.

For both new and experienced users, documentation is vital to being able to understand the data and how to use it. One of the companies that I worked at had a very basic implementation that was set up years ago and hadn’t been maintained in a very long time. Cleaning up the components list, checking what was still working and what wasn’t, trying to understand the data each component was capturing, and documenting all of this information was a process that took weeks.

Part of what kept me driven to update the Data Dictionary was seeing reports that others had built. In a large company there can be hundreds of users in workspace, many of whom aren’t primarily analysts. With only a basic introduction to how to build reports in workspace, and a lack of documentation, creating reports with incorrect metrics was very common. Most of these were heading in the right direction, but needed metrics that were a bit more refined for their needs. The cornerstone of workspace is the ability to be able to build custom metrics/segments and create dashboards from scratch in a very short amount of time. But without the documentation behind it, other users may not know what they’re looking at and struggle to understand or replicate reports.

In the end, I was able to determine which components users should be using and eventually created a VRS with all of these to make it even easier for everyone. The Data Dictionary also works for virtual report suites. Once all of the components I wanted my users to see were added to the VRS, I updated all of them easily with the Data Dictionary. The result of all this work was more standardization across reporting, more accurate numbers, and more confident analysts.

Having a solid Data Dictionary will help all of the users in your organization to understand components and their functions, which ones they should be using for different types of reports, and which other components they should use with it. This is a powerful tool that can help you keep your implementation clean and well documented for the benefit of everyone.