There are many ways to get data in and out of Anaplan; some more involved than others. In our experience, starting simple is always the best approach, unless the customer has a large, dedicated data team. In addition, as previously mentioned, if the data needs cleaning in some way, recommend to the customer that it is best to start the data effort right from the beginning, or even before the project gets started. Suggest that the customer bring in expert help if that makes sense. Many organizations rely on external expertise to supplement the core team and many also bring in special data cleansing tools that help reconcile differences between systems. Here are some guidelines to keep in mind as you evaluate the steps you will take to manage and prepare the data for the integration process:
Assign overall accountability of the data work stream to a member of the customer team; ensure the customer holds the data work stream owner accountable throughout the implementation.
Start small (if you have to) and focus on data quality.
Automate later. It is best to begin with manual uploads. The fact that data and metadata loads are not automated will not stop the project. Poor data can.
Add data tasks as user stories in the Agile Implementation – The Anaplan Way app.
Pay as much attention to data as you do to building the model.
When you uncover data issues, document them clearly and socialize them broadly. It is important that the entire project team, including executive sponsor, understands the issues with upstream data. It is much better for people to have a clear understanding of the precise and specific data issues, than to say "the data is terrible, so the model won't work".