• Why data integration is easy in OneStream

Data integration is an essential part of managing your Performance Management solution. More automatically transferred data makes your Performance Management processes faster and more reliable. How easy is this within OneStream? And what is striking about data integration within this solution?

By Walter Smit, Walter Smit, November 2017

Data integration in OneStream

The integration of data is often complex. Not only because data is often delivered from multiple sources, but also because there are different roles within the organization. Each role has its own perspective on data streams.

Clear separation between the roles

What’s striking about OneStream is the clear separation between the different roles surrounding data integration. The components that belong to the IT roles are clearly separated from the functional components. For example, the system administrator can create an integration with a database, but does not have access to the content of the application. However, he can check that the access works well and whether the accounts are correct. Here too, OneStream helps; inside the application, tools are built to see how a connection works, and what you can do with the data.

The other side of the coin – the user who works with the application from a functional angle – also enhances the data integration. Within the platform, this role has an environment with ample possibilities for influencing and controlling data.

Three layers of controls

With data integration, it is crucial that users can rely on the data. Data validation is therefore an essential part of setting up data integration with another system. In fact, you want to see at an early stage whether the data being read is actually the correct and complete data.

Within OneStream, this control layer is logically designed; In three different layers, control steps helpt to assess whether the data integration is going well.

Layer 1 – Technical Link

This involves the technical layer, such as infrastructure and server design. This layer is the domain of IT. Within OneStream, you can test the connection to the database in several steps; first to connect with the database, then the view and finally to get the data. If there is something wrong in this layer, you will see it immediately on the screen. For example, notifications like ‘no connection to database’ or ‘query not correct’ will appear. In the platform, you’ll also find an approach to set up an automatic data connection with a source system, such as ERP, Excel or SalesForce.

Layer 2 – Functional conditions

Within the application itself, you can validate the data with a dashboard. It’s nice that you can make a connection with the view without calculations. The big advantage of this is that you can see compare each item as is. Through this dashboard, you can check in an early stage if there are any problems with the query you are asking for, or if something is technically wrong. OneStream stores the data in a part of the platform; ‘Flash’. Flash is an access point, where you have the ability to check the data. If the data is correct and complete, the data is continued to the actual application that is configured in OneStream. This can be done automatically or manually, depending on the user’s wishes.

Layer 3 – Refine data

This stage is about the specific data that users need for their workflow. Within OneStream, it is possible to customize data integration by workflow. A workflow is a series of steps that an end user takes to support the workflow. By integrating workflow integration, you can flexibly handle different workflows within an organization. You incorporate this specific intelligence within in the work profile.

Simple data integration in OneStream

Within OneStream, you can easily solve the issue of data integration within your organization. The different control layers and the clear distribution of roles during implementation certainly help. In practice, we see that organizations independently manage and adapt the connections to the platform. Need for assistance from the IT organization or external support is reduced, allowing data integration to be handled more within the finance function. In the end, it is all about the flexibility for the user and the quality of the data. Not about the technique!

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