• June 14, 2022
  • By Jamie Peers , vice president of business development and alliances, Synatic

Why You Should Use a Data Warehouse with Salesforce

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Salesforce has more than 150,000 customers, making it one of the most popular and most powerful customer relationship management (CRM) platforms on the market. Organizations need a 360-degree view of their customers to better serve them and to make better business decisions.

However, storing non-operational customer data in a CRM system such as Salesforce is not ideal.

Salesforce is designed to provide easy access to comprehensive customer information, but it is not a data warehouse. First, storing all your customer-related data in Salesforce is expensive. Second, Salesforce does not have robust analytic tools. Businesses can gain better insight using purpose-built tools such as Tableau and PowerBI. That is why there are Salesforce connectors, to provide support for third-party data support tools.

Best practice is to use Salesforce to access customer data for transactional purposes and integrate a separate data warehouse to store additional data for analytics.

Salesforce Is Not a Data Warehouse

Businesses that decide to do a cost-benefit analysis will quickly realize that storing all of their customer data in Salesforce is impractical, inefficient, and expensive.

Salesforce is designed to handle transactions. It wasn’t designed to be a data repository or to perform data analysis. That is the reason organizations use data warehouses to store and organize data from multiple sources. Unlike Salesforce, most data warehouses are structured in a multidimensional format or star schema to organize data for complex analyses.

Some operational data, as well as non-operational data, can be more effectively stored outside of Salesforce. For example, email messages with large file attachments can consume a lot of storage space. Offloading such data to a data warehouse reduces costs, and using Salesforce Connect makes that data readily available to support real-time queries.

Ingest Information into a Data Warehouse:

The volume of data businesses store continues to increase, but only some of that data is for operational purposes. Both operational and archival data may be needed for analytics to reveal long-term trends or business opportunities. Data warehouses are designed to hold the large amounts of data needed to create custom reports from different data sources. The challenge is extracting that data and transforming it into the necessary formats.

There are typically three steps required to ingest information into a data warehouse:

  1. Extract the data from the source.
  2. Store the data in a staging database where the data can be validated, cleansed, and transformed into a suitable, readable format.
  3. Load the data into the data warehouse.

Normally, the process of converting and storing data can be expensive since it requires specific expertise. However, there are vendors that specialize in extracting and normalizing data. Since Salesforce is such a widely used CRM platform, many vendors provide a business intelligence data layer that provides native Salesforce support.

Features You Want in a Salesforce Data Warehouse

When considering how to pair Salesforce with your data warehouse, you want to use a data warehouse that makes it easy to ingest and manage data while providing real-time data access from within Salesforce. When shopping for a data warehouse, here are some considerations:

Data source extraction. You want to be able to easily access, manipulate, and integrate data. Ideally, businesses want to be able to handle batch processing and have connectors for real-time integration. The objective is to make data extraction easier. Businesses that can find a solution that offers a user-friendly drag-and-drop graphical interface are normally more empowered to rapidly create and deploy data automations.

Database staging. Ingesting data into a warehouse requires data transformation and augmentation. Inbound data also needs to be validated and altered to ensure it is error- and duplicate-free. Most solutions require a separate data storage for transformation, although some vendors are using a temporary storage approach. This approach involves caching, querying, validating, and manipulating data before it is stored in a data warehouse. This makes for faster, more efficient data transformation.

Data loading. Once data transformation is complete, the data is transferred for storage. Performance is a concern, so businesses will want to be able to load data in bulk, eliminating the need for repetitive, costly data reloads. Businesses also need to plan for the future by making sure data management systems can handle the growing volumes and varieties of data.

Salesforce is ideal for providing a complete view of customer interactions, but sometimes you need more data to gain further insights. With the right infrastructure, businesses can take advantage of both data stored in Salesforce and data archived in the data warehouse. It pays to find a nimble, simple, and powerful solution that minimizes or eliminates the complexities and costs associated with data warehousing. When businesses can access data in real-time for analytics, it makes Salesforce data more valuable and empowers business to make better business decisions.

Jamie Peers is the vice president of business development and alliances for Synatic (www.synatic.com), overseeing strategic partnerships, business growth, and GTM strategies.

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