Author: Gaurav Dhimate & Akshata Sawant
With the amount of customer data volume growing exponentially every day, exploring data manually has become a bigger challenge, and analytics has become more important than ever before. To address this challenge, we have Einstein Analytics.
- Einstein Analytics
What is Einstein Analytics? This is a question that we get from so many people who have heard Einstein being talked about.
So from the name itself, you can guess it has something to do with analytics.
So in simple terms, Salesforce Einstein Analytics seeks to collect, analyze and transform the critical business data to create meaningful insight, which in turn allows you to explore data quickly and easily.
Powered by AI it’s a very powerful tool that gives you analytics on the go.
In addition to offering pre-built apps for Sales, Service, and Marketing, the Einstein Analytics Platform gives you the flexibility to:
- Build your own custom, intelligent analytics apps.
- Utilize our APIs and SDKs to enhance your app.
- Connect to outside data sources to see all your data in one place
And a lot more 🙂
- MuleSoft
Now let us understand what is MuleSoft and how we will benefit using MuleSoft with Salesforce’s EA
- MuleSoft is an Integration Platform as a service (iPaas).
- MuleSoft provides a larger ecosystem when it comes to Integration.
If you’ve worked with an ETL tool before you can relate it to MuleSoft but Mulesoft it much more than just an ETL tool
- Provide 100+ inbuilt connectors for easy integration with different systems which makes coding minimal with drag and drop feature
- It provides easy cloud hub or on-premise deployments.
- It comes with Amazing enterprise-level robust security features like Oath, TLS 1.2.
- It supports complex data transformation using Dataweave and DataSense.
- It’s also capable of Managing the whole API lifecycle using the super popular Anypoint Platform.
So now let’s see the power of both when combined.
- MuleSoft + Einstein Analytics
So why use MuleSoft when we have different options to integrate data into Einstein such as APEX programming, Data Import Wizard.
So suppose we need to load data is coming into Einstein and it’s coming from different end sources and it’s in really huge volumes and also the data is complex
You might be having critical data operations, transformations to simplify the data, and it can be helpful to Enhance and synchronize data with salesforce.
Also, MuleSoft provides an in-built connector for Einstein Analytics, which makes our integration much easier.
Two ways in which we can effectively use Einstein with MuleSoft
- We have an inbuilt Einstein Analytics Connector. So it’s just dragging and drop
- Another way is to load data into Salesforce using the Salesforce Connector and then we can pull in data from Salesforce to Einstein Internally.
We also know that now MuleSoft is part of Salesforce so that’s why it makes it more compatible.
4. Use Case
I am a Sales manager for one of the top retail clients and I want to generate new opportunities with existing customers so that I can increase my sales. But I have problem: all data for past purchases by my old customers are in ERP (NetSuite) and I want it in Salesforce so that I can have better Analysis report at my hand with which I can create better strategies to target my customer.
5. Demo
In this demo we are going to get Customer data from Netsuite and send it to the Salesforce Account dataset and then we are going to use this enhanced dataset to create different analytics in Einstein Analytics.
With this enhanced dataset our sales team will be able to generate better sales.
For our demo purpose we are going to use one of the downloadable template from MuleSoft exchange.
So let’s download Netsuite to Salesforce template from Exchange.
Once added to your Anypoint Platform you can see the structure below.
Now let’s configure the source and target system, which in this case is Netsuite and Salesforce.
As discussed previously we are going to get Customer data from Netsuite so lets select Customer as a key in Netsuite.
Now let’s move on to Salesforce where we will be creating a new Dataset using Mulesoft , and wherein we will have all the Customer data from Netsuite.
So let’s search for salesforce Einstein Analytics connector in Mule Palette.
You will get multiple options e.g. create data set , delete data set …………..
Here we are going to use “Upload external data into a new data set and start processing”.
Lets configure the Salesforce Einstein connector.
Once configured lets test the connection.
Now we are ready to configure it for our purpose , which is to create a new dataset into Salesforce and start processing it into Salesforce.
We have 2 sections which we need to configure.
General:
Type – Here we have to provide schema type for our dataset which we need to be created in Salesforce , here i have used metadata_erp.json which contains data structure for my dataset.
E.g.
{
“fileFormat”:{
“charsetName”:”UTF-8″,
“fieldsDelimitedBy”:”,”,
“linesTerminatedBy”:”\r\n”
},
“objects”:[
{
“connector”:”CSV”,
“fullyQualifiedName”:”tdxdatafromERP”,
“label”:”tdxdatafromERP”,
“name”:”tdxdatafromERP”,
“fields”:[
{
“fullyQualifiedName”:”Account_Name”,
“name”:”Account_Name”,
“type”:”Text”,
“label”:”Account_Name”
},
{
“fullyQualifiedName”:”Account_ID”,
“name”:”Account_ID”,
“type”:”Text”,
“label”:”Account_ID”
} ]
}
]
}
Dataset info :
Operation – UPSERT , since we want to create a new dataset we have chosen this option.
Data set name – tdxdatafromERP13 , Name for your dataset which needs to be created in Salesforce.
We are now done with configuring the template now lets run it.
After successfully running we should be able to see new dataset under Einstein Analytics.
If you see in the above picture you can see a new dataset with name tdxdatafromERP13 and number of records inserted is 707.
Now we can create new Recipes in Salesforce with customer data from NetSuite ERP and already existing accounts data from Salesforce.
Once we create Recipes we are ready to create different customs dashboard , one of which i create is a bar chart diagram showing opportunities for sales with our imported data from NetSuite.
6. Conclusion
We have seen how MuleSoft can be useful in integrating data from different systems into Salesforce and enhance its core data to provide much better analysis of Opportunities which can lead to better sales for our client.
7. References
