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Data integration is the new black, but data integration projects can be complex. Many companies wish to consolidate data and decide to perform ERP CRM integrations.
Most data integration providers have done a lot to simplify the data integration process. However, you can go far with a solid plan. How can you create a good data integration project plan?
Let's start by defining what we actually mean by data integration. Data integration means combining data with the integration of business systems. This could be a CRM ERP integration for example.
The primary purpose of this is to make sure data can flow securely and easily between two different systems. Each system has its own processes, but deals with data about the same people or things. In an integrated ERP CRM environment, you can have a unified view of your customer information. When you integrate your ERP and CRM software, you do it to share information about customers, contacts, items, quotes, orders, invoices and sales history.
Other forms of data can also be integrated - there are no limits. You might want to integrate master data, such as posting groups or other metadata that secure a consistent system setup and reporting. Any data that you want to map between two systems can be integrated. It is even possible to do it if you have large data warehousing systems.
In the past, data integration was often done using direct batch interfaces. This meant that data was extracted to a file and then sent to the target system. At the same time, it was imported (via a batch job). This method was pretty labour intensive, especially at the programming and testing stage.
It also had a couple of major faults. It was difficult to work out how to deal with incorrect data, and once the systems were integrated, they had to be kept in sync. Today, many integration systems use a logic that extracts, transforms and loads data.
Most businesses now use agile systems such as Microsoft Dynamics and Salesforce. With these kinds of systems, it makes much more sense to use a data integration platform that simply configures and maps data.
To combine data from different sources, you need a proper data integration plan with detailed data integration process flows. But it does not have to be over-complicated. In fact, there are three system integration project steps with this kind of systems.
To integrate your customer relationship management (CRM) and ERP solutions, you need to understand what your processes are and which transfers you would benefit from.
For example, usually the customer data in your ERP system comes from your CRM system. Often, ther are created in the CRM system from a lead conversion form. In this case, the CRM system is the data's source system.
To optimize business operations, the integration would result in this data integration flow:
Data transfers are usually analyzed to establish which data needs to be transferred, such as contact details or order history. When planning the implementation of your data integration system, you need to define which data you want to flow, and when.
The two systems being integrated need to be connected. System designs (that is, tables, fields and other relevant information) are read and stored to allow data to be mapped.
Then, data needs to be sequenced so that transfers between the ERP and CRM systems can happen in the right order. If transferring an order, you will probably want to transfer the items ordered first, as there may be a new item in the order. Not getting the sequencing right can lead to broken references.
You will also need to decide which of the two systems being integrated has priority if a piece of data has been updated in both systems.
Once set up, you’ll need to test your data transfer. Generally, it is best to start the testing process with just a few records. Often, you’ll see that your data isn’t as high-quality as you expected. In that case, you will need to do some data cleaning before you move on to testing the rest.
Sometimes, you will have data that has been entered manually into both your systems, leading to potential duplicates. If this is the case, there’s a simple fix: create a batch job or query that can update duplicated data automatically. Alternatively, you can look up duplicates manually and link them with an identifier, but this is a slow process.
Once testing and transfer is done, it is time to sync your systems. Do this in stages, making each area live as you go. You will start benefiting from the integration faster.
When you have finished syncing, switch to support mode. This is easy to manage with a data integration platform. Such system could send an email notification when something goes wrong, along with all the information they need to start fixing it.
Give us a call, we can help you with the planning of your data integration project. We will talk you through how RapidiOnline can help you create a data integration project plan that does the hard work for you.
Henning Lund
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