Think of it this way - you’re performing the data import job for a reason, to achieve an outcome.
If there are issues during the import then you’re quite simply not achieving the desired outcome. Ensuring you have properly prepared, you have organised the best tools, and you have selected the best possible method for the task is going to help ensure a successful outcome for your business.
Often when you think of importing data into Salesforce you’ll think of the more traditional method - preparing your data in a tidied CSV file, using Apex Data Loader to perform an Insert or Upsert job, sitting and waiting for the job to process, and reviewing the logs to make sure there were no errors. While this certainly works, there are other ways to go about it and other aspects of your requirements to keep in mind.
If you’re required to upload new Leads from a Google Sheet every week as it’s updated by the Marketing team, that means each week you need to download the sheet, convert it to CSV, ensure it’s formatted correctly, and perform your Salesforce data import job manually. Hypothetically, let’s say it takes you the better part of an hour to get this done each week - this equates to over 50 hours a year (depending on holiday periods, etc) or close to one and a half business weeks of effort. The cost to the business alone is enough to consider an alternative, let alone the headaches it causes you as the individual who needs to perform these monotonous jobs!
Instead of the above method, consider using a tool like Dataimporter to integrate directly with the source document and perform the job on a schedule. This way, once you’ve configured your template and the scheduled job you can sit back confidently and know that your Salesforce data import is being executed on time, accurately, and without digging into your time.
What About Salesforce to Salesforce Data Import?
Similarly, it doesn’t make sense to export data from one Salesforce org, export it into a CSV, and re-upload it into another Salesforce org. Salesforce themselves offer a function called ‘Salesforce to Salesforce’ but this is insufficient for most use cases. It also only supports Salesforce Classic, which goes to show the level of investment that Salesforce themselves currently have in it.
Once again, Dataimporter supports the ability to set up a Salesforce-to-Salesforce direct connection. To do so, simply navigate to the Connections > Instances menu in Dataimporter and connect the other Salesforce orgs that you wish to connect to. This may be other Production environments if you wish to keep data in sync, or Sandboxes if you wish to push data up or down from Prod to Sandbox. Once two or more instances are set up the final step is to build the Jobs that you require.
The ability to connect multiple Salesforce orgs, along with the Scheduled Jobs, Duplicate Management, and Formula functionality will streamline the process and significantly reduce the amount of effort required to share data between multiple Salesforce orgs.
Below is an overview of a handful of the services that Dataimporter connects to out-of-the-box. Please note that there is still active development in the product, so if there are any integrations that you would like to see added to the Dataimporter product please reach out to us.
Instead of having to download your data from Google’s cloud, cleanse/organise the data on your computer, and re-upload it to Salesforce on a regular basis, you could instead be using Dataimporter.
To set up Google Sheets integration you’ll need to sign in with your Google account to authenticate the connection. Then when you’re setting up the job you’ll use the easy navigation that Dataimporter offers to navigate to the Sheets you wish to work with (note - Dataimporter supports the ability to export directly to a Google Sheet as well!). Then continue with your field mapping and Job Schedule as per normal.
Google Drive integration is very similar. After authenticating with your Google account to connect with Dataimporter you will then be able to navigate through folders and select the file you wish to use for your Salesforce data import or export job. Then simply continue building out the job as you usually would.
Connecting to Google’s services directly saves you from needing to manually download and upload files to or from Google storage. You’re also able to leverage the functionality that Dataimporter offers such as the deduplication of records, replacement of null values, and formulas.
Click here to learn more about Google Sheets integration and Google Drive integration.
You can directly interface with Microsoft SharePoint and automate your Salesforce data import or export jobs using Dataimporter. When importing data into Salesforce from SharePoint you will often need to clean the data, reformat it to align with your data standards within the CRM, or remove duplicates. When doing so through Dataimporter, this can all be performed automatically on a recurring schedule with no human input.
This means that instead of needing to pull files from Microsoft SharePoint and manually prepare them, you can determine what processing is required for these files and configure them once as a scheduled job.
Click here to learn more about Microsoft SharePoint integration.
Rather than using a cloud service, your business may require that you connect to a server that your business has set up themselves, or a legacy system that exports to a local computer. In these circumstances, it is often quite a bit more difficult to integrate with these machines, but not in Dataimporter’s case!
You’ll need to use SFTP to connect to these servers. Doing so is a breeze with Dataimporter; simply navigate to the Integrations menu, click New Integration, select SFTP, and provide the required details. Your SFTP integration will then show up in Dataimporter just like any other connection.
Once SFTP is set up in Dataimporter you can benefit from the advanced automation features to make your Salesforce data imports a breeze.
Click here to learn more about SFTP integrations with Dataimporter.
Salesforce’s own cloud database service, Heroku, can also be natively integrated with Dataimporter for all your Salesforce data import requirements. Similar to the other options above, you simply need to provide relevant information (Name, Host, Port, Username, Password, and Database) and your Heroku database will be connected to Dataimporter.
You can use SQL filtration natively in Dataimporter as well, which will save you time in automated data import jobs. This, in addition to Dataimporter’s other features that have been built to streamline your data import processes, will save significant time and energy when it comes to moving data from Heroku to Salesforce.
You can learn more about Dataimporter’s Heroku integration here.
Amazon’s Simple Storage Service (more popularly known as Amazon S3) is yet another storage service that Dataimporter natively supports. You’ll be able to import and export your data to or from Salesforce directly with S3.
Similarly to the above options, Dataimporter’s advanced features are available to you. You’ll be able to query your S3 bucket, use Dataimporter’s features to format data the way you need and remove bad values or records before importing them.
Click here to learn more about Amazon S3’s Dataimporter integration.
There are a series of common challenges when it comes to performing a Salesforce data import job with data from multiple sources - time, resource cost, and dirty data being three key ones. Dataimporter has been designed specifically with these problems in mind. Automated data importing will save your business time, but data isn’t always ready to be imported. This is why Dataimporter’s advanced automation tools such as formula, deduplication, and null value removal were added.
The final piece to the puzzle is the ability to directly connect to external data sources and push or pull data automatically, without needing to take ongoing manual steps. Your data will flow from your external service through Dataimporter, be cleaned and prepared, and be pushed into Salesforce all without requiring your users’ time.
If you’d like to learn more about setting up integrations with Dataimporter you can read the integration documentation in our Help Center. Alternatively, if you’d like to give Dataimporter a try for free, click here to register for free.