configuration Attributes(CPQ)

 Configuration Attributes are a great feature that enables users to input a value directly in the configuration page of a bundle. This makes user a lot easier  instead of keeping separate SKUs for all possible combinations of sizes and colors a company could have for its products.

 

There are two types of attributes in Salesforce CPQ that are

 Configuration Attribute

 Global Attribute

 

When we wish to add a configuration attribute and assign it to a bundle product, we will construct a record with the record type configuration attribute.

A record called Configuration Attribute with the record type Global Attribute is created whenever we want to create and assign any attribute to an option product.

What is a reasoning engine?

 A reasoning engine is an AI system that mimics human-like decision-making and problem-solving capabilities based on certain rules, data, and logic. There are three types of human reasoning or inference mechanisms reasoning engines tend to emulate: 

Deductive reasoning – makes an inference based on universal and generally accepted facts. For example: “All birds lay eggs. A pigeon is a bird. Therefore, pigeons lay eggs.”

Inductive reasoning — derives a conclusion from specific instances or samples. This might look like: “Every dog I meet is friendly. Therefore, all dogs are friendly!” 

Abductive reasoning – makes a probable conclusion from incomplete (and often ambiguous) information, such as: “There are torn papers all over the floor and our dog was alone in the apartment. Therefore, the dog must have torn the papers.” 

Einstein Copilot

 Einstein Copilot is not just any Copilot. It is unique for 3 reasons:

==> It is Conversational means you can interact with it in natural language

==> It is Extensible by virtue of Einstein 1 platform with access to trusted and complete customer data and metadata.

==> It is Autonomous and acts as a reasoning engine to address a vast variety of user needs.

PreventDefault() method in Javascript

 In Lightning Web Components (LWC), we can use the preventDefault() method to prevent an event's default behavior.

The PreventDefault() method is available on events (Such as button clicks,form submission etc.).

When you call PreventDefault() on an event, it stops the default action 

that the browser would normally take for that event.

Common Use cases include preventing form submissions, link navigation or 

button clicks from triggering their default behavior. 

List of Data Cloud concepts and Terminologies

Data Stream : 

This is where we start with the data. When you create a data stream you select the data source you want to bring into Data Cloud, this could be Salesforce data or external data. Furthermore, a data stream can stream data or process it in batches.

Data Lake Object : 

Once data has been loaded into Data Cloud it is stored in a Data Lake Object (DLO), this will contain all the fields from the Data Stream objects as well as the additional custom fields created in the Data Stream setup.

Object Category : 

Each data object you bring into Data Cloud (DLO), must have a category of “profile”, “engagement” or “other”. This is important as it helps determine how you can use and map your data downstream. Any data used to identify and describe a customer is categorized as "profile" - this could be lead, contact, account etc. Any data directly related to a customer or account and related to actions is categorized as "engagement" - this could be activities, opportunities etc. Any data that doesn't fit into these buckets should be categorized as "other" - this data is often static reference data and could be a product catalog.

Data Model Object :

Data Model Objects describe a data model that DLOs are mapped to, it is a way of organizing all the data making sure data is grouped and related where relevant as this makes it easier to act on. The data is mapped to Data Model Objects (DMO) that is a logical grouping with a collection of fields or attributes including lookups. It's important to note that data is not store in DMOs, it's just a schema. Consider using Data Cloud for multi-org, where the same type of object will exist multiple times, the DMO makes sure all contacts or opportunities are appended even though they are stored in different objects. Note that some features in Data Cloud demands that DLOs have been mapped to DMOs for you to leverage them.

Data Kit :

Data Kits are a selection of metadata that are packaged and can be used again and again. For instance if you connect a Salesforce environment and want to add Sales data there is a data kit available that will create the DLO, DMO and relationships, thus you don't have to create them from scratch.

Data Space :

When many people are working with data in Data Cloud you may want to restrict the data a user can see, this can be achieved with data spaces. You select the data sources and data filters are available. In other words, data spaces determines what data you can see where standard permission sets determines what you can do with the data you have access to. All orgs will have a default data space, but more data spaces can be created if you want them.

Identity Resolution :

The likelihood of you having the same profile multiple times in your Data Cloud environment is great especially considering how profiles often are fragmented with one record having the phone number and another having an email. In the scenario of fragmented data there is no way to join the data based on two different contact points. To help resolve this, we can leverage identity resolution that based on rules you set up to join fragmented data into a unified object. You can only use the individual DMO or the account DMO in identity resolution rules.

Profile & Unified Profile :

There is a standard DMO for individual and account, each one of those can have identity resolution applied to them which creates a unified account DMO or unified individual DMO. All profile data should be mapped to the account or individual DMO which gives you a total list of your customers and through that engagement related to them.

Calculated Insights :

You can use calculated insights to aggregate data for your customers such as a lifetime value calculation based on transaction data. These calculated insights can be used in segmentations and actions.

Data Transformations :

Data Transformations (streaming and batch) are great for preparing and cleaning your data for consumption. You may want to clean country and state to a specific standard you are using. If you are familiar with CRM Analytics' recipes it's similar as it's based on the same components.

Data Actions :

Data Actions are a process that is triggered in Data Cloud. For instance when you want to update records in Salesforce CRM with data from Data Cloud, the process is managed by a data action. Data Actions can also kick start a flow or Apex code.

Segments :

Segments are an marketing add on to Data Cloud. Segments are a group of customers targeted for a campaign based on rules you define with your profile data.

Activations :

Activations are a marketing add on. Activations are used when you have created a segment that you want to pass on to another system. For example you want to add individuals to a journey in Marketing Cloud or a Facebook campaign, thus segments can be activated to Salesforce as well as Salesforce partners.