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Data Integration Best Practices - How to set the framework for data integration projects

So far, in our blog series Data Integration Best practices, we have covered the different types of high-level and low-level problems occurring in data integration projects. We have also addressed the different types of integration, the systems that move data and even the pricing aspect of such a project. Ten articles later, we arrived at best practices moving forward. In this last chapter, we are going to talk about some tips that revolve around preparing for and running an integration project.

Data integration, iPaaS and elastic.io - How it all fits together (Explainer)

The number of applications that companies use hasn't stopped growing in the past years – quite on the contrary, it is now "exploding" more than ever before. Application integration comes from the desire to avoid siloed information in this scenario, but oftentimes, this is done only on need basis, resulting in cumbersome point-to-point integrations that only grow in their complexity.

Content Enrichment Demo

This screencast demonstrate how you could do a content enrichment integration pattern using elastic.io iPaaS. On the example integration where IoT device data got accepted by elastic.io integration platform, enriched with the Salesforce data and later on a new Zendesk incident report is created based on this information. You will see how you could efficiently combine multiple different data types as well as do a complex data transformation.