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Episode 9 of Data Unleashed dives into how to make the most of your Salesforce integration process. There are a lot of ways to set up integrations, which can make it seem overwhelming at times. You may find yourself needing to get data from non-Salesforce data sources into a master org, or get data out of Salesforce and into your data warehouse.
With a self-hosted approach, you’ll have the most flexibility, no matter the scenario you find yourself in. This type of process means you have the control, speed, and security to set up your integration, allowing you to replicate the entire data model to your on-prem data warehouse in a SQL standard relational database environment. This means your team can access that data in a nonproprietary format and use it for whatever integration it is needed for.
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My name is Drew Niermann, and this is Data Unleashed, the video blog series dedicated to helping you get the most out of your investment in Salesforce.
So today we’re going to talk about Salesforce integrations. If you had to set it up, how would you do it? There’s a lot of things that could potentially be done. So in this scenario, that Salesforce is a primary system of record for your enterprise, maybe you need to get data from multiple non-Salesforce data sources or other production Salesforce orgs, into a master org that’s going to persist for a long time.
Or maybe you work for an organization where Salesforce is not a primary system of record. And you need to get data out of Salesforce and migrate it over to an enterprise data warehouse or something like that.
In either scenario, at Data Unleashed, we like to make the argument that a self-hosted approach to either one of these integration scenarios gives you the most flexibility, speed, control, and security to set up your unique integration.
So if you didn’t have a self-hosted approach, oftentimes, what people will do is they’ll pull a bunch of spreadsheets out of Salesforce and dump them in like maybe an S3 bucket or something like that, or build a bunch of scripts to turn spreadsheets into a quasi relational data model, so that they can integrate with some sort of Snowflake or Redshift BigQuery data warehouse. But if you have a solution that allows you to replicate the entire data model to your on-prem, or cloud-based data warehouse in a SQL, standard relational database environment, your enterprise data team, your integration architects, developers, consultants – they can get at that data in a non proprietary format, and move it into and out of Salesforce – upstream downstream – they can enhance it, transform it and basically get it to do whatever they need it to do for integration purposes.
In the event that you’re trying to get data into Salesforce, the advantage of having a copy of your target org schema living in a database that you control means that you can massage data from any other third-party data source, maybe it’s Salesforce, maybe it’s not, into that empty schema. And then, use loading tools to push the data to Salesforce that can handle all the referential integrity, record ID mappings, so that you don’t have to do it with spreadsheets.
So if this sounds like something that would be of value to you to enhance your analytics, or ETL processes, your integrations, reporting sandbox seeding or something like that, please let us know.
You can drop me a message on LinkedIn and I’d be happy to tell you a bit about how the company I work for is helping Salesforce’s largest customers do these exact same things every single day. My name is Drew Niermann, and this is Data Unleashed. Thank you so much for watching.