If you’re new to using the Workiva Data Management Suite, you may be asking yourself - “what’s the best way to structure large data sets in a Wdata table?” If you’re asking yourself this, then you are in the right place!

Before you create your Wdata table and upload your data sets, it's import to consider the structure of your data and determine the optimal way to store that data within your table. If your data set is expected to consistently grow, spanning across multiple quarters and even multiple years, then it is recommended that you structure your data in a way that the data set will grow tall instead of wide. Meaning as your business grows, there will be more rows in your data than columns. We recommend avoiding listing out account numbers, entities, or the like as individual columns in your table. Instead, you will want to have one column for account number. 

The benefits of structuring your data tall instead of wide include:

• Ease of adding new accounts/entities in the future
• Simplicity of aggregating across accounts/entities
• Flexibility to pivot based on any field in the table
• Streamlined process to upload large data sets
• Less columns needed in any given table, so less likely to hit table limits

Some business users prefer to see their data in a pivot table in order to see more data at once. When you structure your data in a tall format, it is easy to accomplish this by using the crosstab functionality in queries. Crosstab queries can even be connected to sheets in Wdesk the same way that flat queries are.

If your data is already pivoted and you need to unpivot your data before loading into a Wdata table, you can do this by unpivoting your data in excel before uploading to Wdata. If your data is being pulled into a Wdata table using chains, you can use the unpivot command to restructure it before uploading to the Wdata table.

To learn more about uploading data to a table, check out this post!

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