Salesforce Data Cloud and Customer 360: Free Consulting Workshop

Salesforce is now offering Data Cloud to its customers for free!

Recently announced at Dreamforce 2023, all existing Salesforce customers with Sales Cloud or Service Cloud (Enterprise or Unlimited licenses) now have access to Salesforce Data Cloud. This complimentary package includes two Tableau Creator licenses at no additional cost and Data Cloud licenses for up to 10,000 profiles.

Salesforce Data Cloud is a rapidly evolving product within the Salesforce ecosystem, built natively on Salesforce Lightning, and seamlessly integrates with existing orgs. Salesforce is democratizing access to their customer data platform, ensuring that businesses of all sizes can harness the power of a data platform to connect, unify, and harmonize data, and thus creating a single source of truth for customers (Customer 360). This encompasses external data from company websites, mobile apps, and various business applications/products, as well as internal data from Salesforce orgs. In turn, this will facilitate improvements in sales, marketing, and operations through enhanced personalization, advanced segmentation, improved customer experiences, and more accurate predictions and recommendations. Salesforce Data Cloud offers advanced capabilities to make customer data management seamless.

The complimentary Tableau licenses offer access to a best-in-class business intelligence tool that is leading the adoption of AI and specifically Generative AI with the recently announced AI assistant called Einstein Copilot for Tableau. Tableau integration with Salesforce offers unparalleled opportunities to accelerate data discovery and new insights.

It's worth noting that Salesforce Data Cloud doesn't store data within native Salesforce Objects; instead, it resides in an off-core data lake as an integral part of the packaged solution.

Source: Salesforce

Key Salesforce Data Cloud Integrations

Here are some noteworthy native Salesforce Data Cloud connectors:

- Salesforce CRM
- Marketing Cloud
- Marketing Cloud Personalization (formerly Interaction Studio)
- B2C Commerce

Companies can also benefit from the pre-built Customer 360 Data Model, which serves as the standard data model for Data Cloud. The Customer 360 Data Model is designed to enhance interoperability and streamline the integration of data across various cloud applications. It can be extended to establish data lakes, support data analytics, facilitate machine learning, and more.

Salesforce Data Cloud serves as a pivotal entry point for capitalizing on AI investments. Specifically, AI is seamlessly integrated into Data Cloud to facilitate the harmonization of data from diverse sources and formats, automatically detect and rectify data discrepancies and anomalies, enhance customer data through enrichment, and elevate insights by predicting customer churn, forecasting, and making customer recommendations. Additionally, customers have the capability to leverage Salesforce Einstein Discovery for creating their own bespoke AI models. We consider this approach a pragmatic means of aligning business objectives and goals with the power of AI.

In addition to the Customer 360 features and AI capabilities, a standout feature is the pre-built connectors to both Google BigQuery and Snowflake. These connectors enable effortless access to data with zero duplication. Essentially, this means that you can access your BigQuery/Snowflake data without the need for replication or an ETL (Extract, Transform, Load) process.

Explore Salesforce Data Cloud with Kenway

If you are considering how Salesforce Data Cloud aligns with your Salesforce roadmap, Kenway Consulting is delighted to offer you a complimentary one-hour workshop. These workshops can assist you in understanding the value proposition and making informed decisions regarding your Salesforce product roadmap. To schedule your workshop, please contact us at [email protected].

FAQs:

1. Is Salesforce Data Cloud Secure?

Yes, Salesforce Data Cloud is indeed secure. Salesforce boasts a robust track record of prioritizing data security in Salesforce, with substantial investments made to safeguard their customers' data. Salesforce Data Cloud incorporates a range of security measures to ensure the protection of customer data. These measures include:

Encryption: Salesforce employs encryption for customer data both at rest and in transit. This means that even if unauthorized access is gained to customer data, it remains unintelligible without the encryption key.
Access Control: Salesforce utilizes role-based access control to guarantee that only authorized users have access to customer data. Customers also have the flexibility to configure Salesforce to implement additional security measures, such as multi-factor authentication.
Security Monitoring: Salesforce maintains round-the-clock security monitoring of its systems to detect potential threats. Should any security threat be identified, Salesforce takes immediate action to safeguard customer data.

2. When Was Salesforce Data Cloud Released?

Salesforce Data Cloud was released in 2023, as a rebrand of Salesforce Customer Data Platform (CDP) and Genie. It was first announced at Dreamforce 2022 and became generally available in early 2023.

3. What are some tips for using Salesforce Data Cloud effectively?

Start with a clear plan: Before you start using Salesforce Data Cloud, it is important to have a clear plan for what you want to achieve. This will help you to choose the right features and tools, and to get the most out of your investment.
Get your team on board: Salesforce Data Cloud is a powerful tool, but it is important to get your team on board before you start using it. This means training your team on how to use Salesforce Data Cloud and explaining the benefits of using it.
Monitor your results: It is important to monitor your results after you start using Salesforce Data Cloud. This will help you to identify what is working and what is not, and to make necessary adjustments.

4. Can Salesforce Data Cloud help with data privacy compliance?

Yes, Salesforce Data Cloud can help with data privacy compliance in a number of ways.

Data unification: Salesforce Data Cloud can help you to unify your customer data from across multiple sources and create a single view of each customer. This can help you to better understand your customers and their privacy preferences and enable quick response to privacy inquiries.
Data quality: Salesforce Data Cloud provides tools to help you identify and correct data errors, and to ensure that your data is complete and accurate. This is important for ensuring that you are complying with data privacy regulations, such as the General Data Protection Regulation (GDPR) and the California Privacy Rights Act (CPRA).
Data access control: Salesforce Data Cloud provides role-based access control to ensure that only authorized users have access to your customer data. This can help you to prevent unauthorized access to your customer data and to comply with data privacy regulations.
Data encryption: Salesforce Data Cloud encrypts your customer data at rest and in transit. This helps to protect your data from unauthorized access, even if it is intercepted.
Data audit logging: Salesforce Data Cloud provides audit logging to track all access to your customer data. This can help you to identify any suspicious activity and to comply with data privacy regulations.

In addition to these features, Salesforce Data Cloud also includes a number of tools and resources to help you with data privacy and compliance. For example, Salesforce provides a Data Privacy Center that provides guidance on how to comply with various data privacy regulations. Salesforce also provides a number of pre-built data privacy reports that can help you to assess your compliance with these regulations.

Overall, Salesforce Data Cloud is a powerful tool that can help you to improve your data privacy and compliance posture.

Top Innovations from Snowflake Summit 2021

Over the past year, Kenway has continued to invest in its partnership with Snowflake through a variety of experiences and certifications such as Snowflake SnowPro Core. Snowflake is a cloud data warehouse that unites siloed data, discovers and securely shares data, and executes diverse analytic workloads. We believe there are many opportunities for our clients to reap the benefits of this innovative cloud warehouse and data lakehouse platform.

As one of Kenway’s certified Snowflake SnowPro Core employees, I recently had the opportunity to attend Snowflake’s two-day virtual summit, which provided me significant insights into all the new features they will soon be releasing to the public. Here are some of the overall themes and highlights that were discussed:

Connected Industries

Every Snowflake user can access data across the cloud, regardless of region, which provides organizations a better means for data collaboration. Some companies are using Snowflake to bring in their data in real time, which allows them to get up-to-date insights on transactions. Snowflake has substantially increased the data sets available on its Data Marketplace. The Marketplace is where companies can share their data rather than make copies of it and then move it around. Another key topic in the Connected Industries domain was Snowflake’s new integration with ServiceNow. This native integration allows the ServiceNow data to be readily available in Snowflake for companies to manage consumer relationships and become part of a central data repository, rather than being siloed.

Another powerful feature in Snowflake that helps industries stay connected is its improved data sharing capabilities. There are three methods for organizations to share data: share it with other accounts, publish to a private exchange, or publish to the public marketplace. The new API will help guide users through the process to make entire databases, tables, views or functions available to those with whom they’d like to share. Snowflake sharing eliminates the need to create and build processes to move data inside or outside of an organization. There is one copy of the data created, and data updates are made available to consumers in real time.

Global Governance

Last year, Snowflake released a feature that allowed users to mask data dynamically. To add onto that, they have been working on row access policies and object tagging. Personally identifiable information (PII) is difficult and tedious to identify in data, and is usually done manually. Snowflake now has two key features that allow its customers to tag data automatically through classification and anonymized views. They can then apply functions to the table that will either generalize or suppress that data. These features still provide the analytical value needed to generate insights and protect customers’ information.

Security has also been front and center when talking about storing data in the cloud. To address this concern, Snowflake has a layered security model that includes network security, identity authentication and access management, and single sign-on. One of the latest improvements is the private connectivity to users’ Snowflake internal stages. The staged data that is accessed through client apps remains on the private network. On AWS, users access Snowflake’s S3 PrivateLink capability where the data stays on the Amazon private network which eliminates the need for proxies. Azure has a similar capability called Azure Private EndPoint. Another important security feature is the new session policies that can be set at the account level or individual users, as well as database and UI timeouts.

Platform Optimization

Snowflake continues to improve its performance and efficiency, and the most recent updates made are better compression and query acceleration. All new data being written to a warehouse is compressed even more, resulting in some customers benefiting from a 30% cost savings for user storage. The query acceleration service boosts performance which can result in 15 times performance improvement and less latency, giving users better predictability on query response times. These new features are being done behind the scenes so that there is no impact or downtime to Snowflake users. In conjunction with performance and storage improvements, users will soon have a new administrative experience with improved admin screens to better track usage, storage and costs for their organizations.

Data Programmability

Snowflake users have been utilizing task scheduling to help with their data pipelines. One improvement to this feature is serverless tasks which allow for serverless execution, and automatically determine the appropriate amount of compute resources. Another new feature in this domain is schema detection which can determine the schema for semi-structured file types of Parquet, ORC or Avro. Users will soon also be able to store and process files as they do with structured or semi-structured data, eliminating the need to load data from files in the data lake. Developers will now have the ability to create functions and stored procedures in a SQL based language rather than just JavaScript.

Another new feature built to make developers’ lives easier was Snowflake’s SQL API. This allows them to submit SQL calls through the API, which supports standard queries, DDL and DML statements. These API calls are lightweight with little overhead. Why is this important? If organizations migrating their applications use Snowflake as their data warehouse, there will be no need for them to refactor the code since Snowflake already includes REST API. This key benefit ultimately helps reduce migration costs.

There were many more great discussions at Snowflake Summit 2021, all of which are now available to watch on-demand. We’ve already begun to share some of these insights with our clients, and look forward to helping them leverage these capabilities.

If you attended the Summit or have a chance to watch the recorded sessions, I encourage you to share your thoughts and favorite takeaways. Please connect with me on LinkedIn to discuss what you found most interesting – I’d love to compare notes!