Atlas Solutions

Atlas Best Practices: Tips for Handling Large Reports

By Frank Totera – Atlas Technical Support Team |

Welcome to the latest installment in our Best Practices blog series. This series is designed to help our customers get the most out of Atlas — from building media plans and trafficking campaigns to measuring and understanding results.

Today’s article is the second in a three-part series on Atlas campaign reporting. If you missed our first installment on time-saving reporting tips, give yourself a few minutes to catch up before diving into today’s piece.

This post covers key factors to be aware of when creating reports based on large amounts of data as well as tips to pull faster reports. Atlas reports are typically quick to generate, but there are a few things to consider before building yours.

For example, if the dataset you’re pulling is too large, the report could take several hours to populate so it’s helpful to know which variables are most likely to add time to creating your reports before you get started:

• Your requested date range.

Atlas standard reporting gives you easy access to data covering the previous 13 months. Selecting a large date range naturally increases the rows in your report — especially if the “Statistics Date” column is included, since it breaks out daily data. Scheduling a report in smaller intervals throughout your campaign can speed up report generation and eliminate manual work.





• The number of actions in the “Actions” filter when a conversion column is included.

Conversion data is processed at the time you run your report. For each action included in the filter, Atlas looks for an associated impression or click, then checks to see if it falls within the specified window. Advertiser reports that have hundreds or thousands of shared actions may require more time — which is why they can and should be narrowed down whenever possible. Remember that not including any actions in the “Actions” filter is the same as including all actions that exist in the advertiser. Narrowing filter actions to only campaign-specific requests will help speed up the process substantially.





• The use of granular reporting columns.

Detailed dataset columns such as “DMA Name,” “U.S. State” and “Country” give advertisers tremendous insight into the audience their campaigns are reaching. However, there are 210 DMAs, 50 U.S. states and 196 countries worldwide. This means that there is a lot of mapping needed to attribute these to each metric. When using such granular reporting columns in Atlas, you can save time by creating reports for only a few campaigns at a time.




Makes sense, right? The largest data requests are the ones that take Atlas the most time to pull. As mentioned in our first article, scheduling a report at smaller intervals is recommended and can save a lot of time in the long run. With a little practice, you can find ways to quickly get the results you need and spend less time waiting for your reports to generate.

We’ll be back in a few days with our third and final post in this series, “Managing Your Campaign Data.” And if you have questions about Atlas reporting or any other feature, please visit the Help Center or contact your Platform Solution Consultant for support.