June 12, 2015
Article written by Naveen Hiremath, Sr. Salesforce Technical Architect Manager Bluewolf, an IBM Company
With the growth of cloud computing and big data, enterprises are dealing with more data — more types of data — than ever before. There has been a renewed focus on developing a better understanding of the value of this information, as it provides a crucial competitive advantage in today’s business landscape—the more relevant data a company can capture, process, and provide in one integrated system, the more competitive advantage and differentiation that company can generate. In this post, let’s consider some different data integration strategies.
Data migration is the process of moving data between systems. The process includes determining the scope of the data to be migrated, transforming the data set, and choosing a destination system where the data will be inserted. This is most commonly employed when companies are moving from a legacy system to Salesforce or from a Salesforce production instance to a sandbox instance; when backing up data; or when consolidating salesforce org (read Unify Your Data for a Successful Org Merge for more details on consolidation). For additional details about migration, read 4 Steps to a Seamless Salesforce Data Migration.
A one-way sync is when data is moved from a single source system to one or more destinations in an ongoing, near-real time, or real time basis. It is beneficial when data need to be kept up-to-date between systems across time. When compared to an automated migration pattern, this strategy is only for migrating data that has changed. Salesforce-1 Lightning Connect enables real-time data integration via clicks and makes it easy to take outside data and treat it like it is in Salesforce.
This process involves merging data from two systems to behave as one while respecting their need to exist as different datasets. In other words, this will capture items that exist either in one or both of the systems and synchronize them. An example use case is a company may want to enable bi-directional data flow from legacy system(s) into Salesforce and vice-versa.
Aggregation is the process of collecting or receiving data from multiple systems and merging it into one. This pattern comes in handy when we want to build an API or a report that furnishes Salesforce and any legacy systems in one aggregated response without the need to store duplicate data in multiple systems.
Consider a sales organization. The company wants to synchronize data about accounts and contacts with partners, but only for accounts and contacts that both the company and partners have, but they don’t want to send other data to each other. Correlation strategy is useful in the case where we have two systems that want to share data only if they both have a record representing the same item or person in reality.
Based on the specific business use case, data integration between Salesforce and other systems could leverage any of the above strategies with an integration tool provided by Informatica, Dell Boomi, MuleSoft, etc. However, if custom-built integration is a necessity, Salesforce offers a wide array of Open & Bulk APIs based on industry standards, such as REST & SOAP. The Salesforce Data Integration blog discusses these APIs in depth.
No one can ignore it: data is everywhere, both on-premise and in the cloud. To realize the full value of their data, organizations need to be able to integrate it across the entire enterprise. These integrations can be complex and expensive. In fact, according to a recent survey, 48 percent of CIOs said data integration is their #1 pain point. As trends like cloud computing, BYOD (Bring Your Own Device), and IoT (Internet Of Things) become pervasive, companies need to consider integrating not only structured data, but unstructured, semi-structured, and sensor data. To learn more, contact Bluewolf to connect with one of our IT experts.