Data integration basics

How to prepare your data

There are many ways to get data in and out of Anaplan; some more involved than others. In our experience, starting simple is the best approach.

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 your team; the data work stream owner should be 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. Manual data uploads will not stop the project, but poor quality data can.
  • Add data tasks as user stories in the Agile Implementation – The Anaplan Way app.
  • Pay as much attention to data as you would building the model.
  • If 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."
  • Plan for data integrations early in your Anaplan implementation journey. This will give you time to determine source systems for data, plan for data staging, data transformation and data quality checks. You can also create sample integrations, test them and resolve data integration issues while you still have sufficient time during Anaplan implementation.

Which integration method should I use?

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Anaplan data integration supports typical operations such as importing, exporting, deleting obsolete data, and running a process that combines one or more imports, exports, or delete actions.

All integration methods are based on our Rest API, which is how the model builder will develop in the model. In order to import or export data in Anaplan, you will need to build an action then automate the use of those actions.

There are different levels of data integration. Below is a summary describing the three levels of data integration:

  • Point and click file import and export via Anaplan user interface
  • Triggering processes by button inside Anaplan
  • Anaplan Connect: On-premise bidirectional utility. Compatible with any scheduling tool. Simple and advanced file-based and direct relational integration
  • Anaplan ETL Connectors: Use predefined bidirectional Anaplan connectors available with MuleSoft, SnapLogic, Informatica Cloud, and Dell Boomi ESB tools
  • Fully supported and documented API
  • Use to build custom integrations or use your own ETL tool
  • Supports bi-directional integration

Generally, the level of data integration will depend on the type of user running the integration

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How do I find out more?

Start by taking the Data Integration Basics course on the Learning Center.

You can also learn more about third-party tools, or the Anaplan API in the Data Integration section of Community or read more about HyperConnect