Salesforce Data-Integration

4 Steps to Successful Salesforce Data-Integration

Data integration is a process to streamline data from various sources into a single, unified view. The ultimate goal here is to pave a path through which businesses get information about a spectrum of subjects on a single Datasheet.

With the increasing use of a large amount of data or big data, analyzing each data source becomes hectic. You will require an automated system that provides access to real-time users information necessary for making decisions.

Statistically, 80% of business leaders think that data integration is crucial for ongoing business operations. Out of which, 67% rely on data integration to get support on business intelligence and analytics.

The data integration process has also evolved in the past few years. Prior, businesses used the batch system that extracted data from a file and transported it to the target source. Simultaneously, the same process was done to important data from the other side.

But, now businesses are using automated processes that extract, transform, and load data, keeping all the systems in sync.

Let’s get started; here are Four steps to a seamless data integration process:-

1. Define the Scope 

Your data migration process should start with defining what data you will migrate, its sources, current format, and core dependencies. This will help you grasp information on both parties to avoid any inconsistency or data loss.

Next, define clear objectives to measure its success after the integration is complete. For instance, a real-time data flow from Configuration Management Database (CMDB) to your CRM with 100% uptime can be your integration goal.  So, according to your business requirement, you can set your data integration goals, including the various parameters you will opt for in its testing.

Here, businesses should also list down the various risk factors associated with this data integration. This way, you are not overwhelmed when the problem arises, and you can map out the exact steps to solve it.

Various risks can arise during data integration, like:-

  • Data access issues
  • Unresponsive stakeholders
  • Server failure
  • Duplication
  • Uncategorized data
  • Data feed failure

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2. Understand your Systems & Create Backups

The systems involved during the data integration process from extraction to the final transfer need to be monitored.

You need to know your systems in and out, like if there is appropriate connectivity, any specific configuration required for the transfer, or is any part of the process in the cloud. Also, discover if any manual processes are being used and how they will contribute to the data integration system.

Secondly, the most crucial thing to consider during data integration is its security.

Each step in the data integration process affects various business operations. Businesses need to be on their toes to map out ways on how they will ensure data security with seamless data integration.

Consideration for Designing the Integration Flow

  • Authentication and Authorization
  • Type of Integration Supported
  • Data Security
    • Firewall
    • VPN
    • Proxy
  • Data Format
    • JSON
    • XML
  • Choosing the right Integration Pattern
    • Request and Reply
    • Fire and Forget
    • Batch Data Sync
    • Remote Call-in
    • Data Virtualization

Tip: The best way to secure-proof this process is to make regular backups. So, even if anything doesn’t go as planned, you will not lose any crucial business data.

3. Create a Data Integration Structure

Now that we are on edge to start our data integration process, defining the current data flow is necessary. It will tell you how the data will flow during the process and after it’s done. This way, you can also map out ways in which you will utilize that information in the future.

A standard data integration process involves extracting information from various sources, with ongoing real-time duplication and data filtration. The information is then processed and changed to the required data format for data delivery.

To make sure the process is error-free, you can conduct a sample data integration test. This way, you are prepared for any complications and confirm that the data is fit for the purpose.

The results should be monitored by the end-user, whether or not the data integration process was effective. You can also set up alerts for any system-level issues like data inconsistency, improper connectivity, etc.

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4. Implement & Test

The last step of your digital integration process is finally here. Before you implement the project, ensure that you have given proper access to both the original and the destination source. Check if the people involved in the process are ready and the affected departments are well aware of this integration and its adjoining consequences.

After the process is complete, our next step would be to comprehensively check data for any loss. So, even if it’s there we are prepared with risk mitigations strategies and backup to keep things on track.

We would suggest you not delete your backups until this digital integration process is complete and you are satisfied with the results.

Final Thoughts

Nowadays, every business wants a unified system that gives a holistic view of the data collected from various resources. Setting up data integration systems is quite common but is also prone to errors.

This is mainly because businesses neglect the steps taken for a successful data integration. You need to ensure that the original and destination source are well-aligned and secured before transferring data from any side.


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