Data Cloud
Pricing Use Case

Horizon Supply Chain Solutions will primarily leverage Zero Copy to access large volumes of operational and usage data residing in their Snowflake data warehouse and combine that alongside their data from Sales Cloud.

Based on their use case, the volume of data accessed, and the complexity of required transformations on federated Snowflake data, here's an estimate of the key data access and processing activities:

• Salesforce Sales Cloud: to ingest customer records and engagement such as contacts, opportunities, # of meetings etc.
• Website Data: to capture customer interaction from their website (e.g. browsing behavior)
• Data Federation—Rows Accessed: Operational and usage data of accounts and individuals using their software application

To understand the credits and cost related to connecting and transforming this data we must first start by understanding the scope of data they’d like to bring in from these destinations, which is outlined below:

• Profile Data: 8 million non-unique records. Based on this scope, we can determine the total amount of data to be processed in year one related to profile records:
  • From Salesforce Sales Cloud — 1/3rd of profile records: 2.7 million profiles ingested with 5% updated daily, totaling roughly 51 million rows annually
  • From the website— 2/3rds of profile records: 5.3 million profiles ingested with 5% updated daily, totaling roughly 103 million rows annually
    
    
• Engagement Data: 15 million records annually. Based on this scope, we can determine the total amount of data to be processed in year one related to engagement records, assuming Horizon initially uploads one previous quarter’s worth of historical engagement data to start (represented by 25% of the total):
  • From Sales Cloud: 1.3 million historical records ingested initially with another 5 million records expected throughout the rest of year one, totaling 6.3 million rows annually
  • From the website: 2.5 million historical records ingested annually with another 10 million records expected through the rest of year one, totaling 12.5 million rows annually
    
    
• Data Transformations applied to 1% of all ingested data. In order to get the data into a proper format for harmonization, Horizon runs data transforms on a small portion of the records ingested, processing a total of 98 million rows annually
  
  
• Federated Data (accessing data from Snowflake): 25 million engagement records annually. There is no cost associated with connecting this source via Zero Copy. Costs are only incurred when the data is accessed to run identity resolution or specific features within Data Cloud tied to activating the data (Calculated Insights, Segmentation etc.)
  
  
• Data Sharing (sharing data to Snowflake) applied to 5% of Data Cloud data: Given this scope, Horizon will process 55.5 million rows annually for data sharing between Data Cloud and Snowflake via Zero Copy. This total includes the initial set of records to be shared plus 20% of that data requiring daily updates

Summary Table for Credits and Cost
The "Credits Consumed" column is calculated using the following formula: (Rows Processed * Credit Multiplier) / Unit of Multiplier

To create a single, accurate view of each customer and account, Horizon Supply Chain Solutions will unify data points from across sources using Data Cloud's identity resolution capabilities. This process involves taking an estimated 154 million profile-related records annually and applying matching rules to link and unify them into comprehensive profiles, resulting in 2.6 million unified profiles across accounts and contacts annually. The credit consumption is based on the volume of records processed for unification.

Note, in this use case all Snowflake data being accessed for Zero Copy is assumed to be engagement data so it does not impact the cost of identity resolution and profile unification.

Summary Table for Credits and Cost
The "Credits Consumed" column is calculated using the following formula: (Rows Processed * Credit Multiplier) / Unit of Multiplier

With unified profiles, Horizon creates Calculated Insights to derive actionable information about their Accounts and Customers. Through the use of Data Queries these insights are surfaced directly to sellers within Sales Cloud. The following outlines each activation and its estimated data processing volume.:

• Calculated Insights: Horizon builds five key insights such as a daily "Module Adoption Score”, a daily “Service Risk Indicator”, and a monthly "Expansion Opportunity Score" score
  • Processing data for Calculated Insights involves two distinct costs, stemming from different data sources. We estimate processing 3 billion rows annually for profile and engagement data brought in through batch pipelines. An additional 28 billion rows annually are estimated for data federated from Snowflake
    
    
• Data Queries: Through the use of Data Cloud related Queries, Horizon surfaces these insights directly onto corresponding Account or Contact records in Sales Cloud. This ensures sales reps see the most critical information instantly within their familiar workflow. Horizon anticipates roughly 3,000 queries daily
  • Again, these Queries process data from two distinct sources, batch pipelines and federated data from Snowflake. Horizon will process 1 quadrillion rows annually of batch profile and engagement data annually. An additional 85 billion rows annually will be processed by accessing shared data federated from Snowflake.

Summary Table for Credits and Cost
The "Credits Consumed" column is calculated using the following formula: (Rows Processed * Credit Multiplier) / Unit of Multiplier

Based on a large portion of the data being supplied via Zero Copy , Horizon Supply Chain Solutions will require the minimum amount of storage for DData Cloud., representing 1 TB of storage.

The monthly cost for storing data in Data Cloud is based on a flat rate per terabyte (TB). Each TB of storage costs $23 per month.

Summary Table for storage needs and costs