The CRM is no longer seen as the definitive source of trust for enterprises when it comes to collecting customer data. Instead, it has become just another SaaS tool that is unable to handle the complex data architectures that modern enterprises have created.
Warehouses have emerged as the new system of records, revolutionizing the way
we approach data management. The CDW industry has grown from $36B to $80B in the last 5 years. One of the main benefits of a data warehouse is its flexibility, security and ability to grow with your business.
Several apps have realized the true potential of data warehouses and have harnessed their power by building on top of them, enabling business applications to go beyond just business intelligence.
In the last 5 years, the number of SaaS tools used by companies has been multiplied by 10.
To face the ever-growing complexity and volume of their data, businesses are increasingly adopting data warehouses as their source of truth, and shifting to modern data stack technologies.
It helps organizations to centralize and manage large amounts of data from various sources, such as transactional databases, log files, and external data sources (ie: third-party tools).
Some specific benefits of data warehousing include:
integrity of the data by enforcing data standards, performing data cleansing, and providing a consistent view of the data.
There are several common applications of data warehousing, including:
insights faster and to drive the business with a data driven approach, not intuition.
Data warehouse native applications are the go-to softwares for maximizing the potential of data warehouses, the place where all your data lives. They are optimized for working with large amounts of data, and custom business entities.
These applications are used for data analysis and reporting and more recently, for orchestrating sales processes and customer engagement.
Different arena of tools understood the potential of this new generation of SaaS, and start leveraging the CDW for specific usecases. Some example includes the BI tools that were originally among the first to do it or more recently tools like Pocus in the
They are software applications that does not have its own data backend, are just an application layer on top of your company data. No need to set new data pipelines to sync data back to your destination app.
Why should you care about this new wave?
Glad you asked.
Well, one of the biggest advantages is that the data doesn’t need to be synced or replicated on the vendor’s application, which is typically the case with traditional SaaS solutions.
We shouldn't have to pay for the same data multiple times. We should be able to get it once and use it for any purpose without paying more.. Or I hope you don’t have 100 tools 😅
Another advantage of these apps is that, because they don't replicate your data, they don't have ownership of it. This means you have complete control over your data, as well as enhanced
They also benefit from the data warehouse qualities like greater data accessibility for end users, reliable data integrity that also help bridging the gap between data teams and business folks.
Data engineers ensure data quality, business folks leverage it to drive revenue.
Ultimately, you don't have to be tied to a fixed schema, you can create and own your data models & business entities definition.
As we said earlier, there are several tools leveraging the power of the data
warehouse. Those are idiosyncratic softwares having a standalone approach. Conversely, at Cargo
We are unopinionated by design - Opinionated by usecases.
Cargo let mature organizations build their own internal go-to-market apps on their own, fully customizable and way more effective to tackle their use-cases.
Those mid-market & enterprise companies deal with high volume and ever-growing complexity of data. By sitting on top of their warehouse, we make it easy to build applications that answer their business-specific needs.
The main usecase today for enterprise companies is lifecycle marketing like sending a personalized promotional or product update email to a specific segment, as well as building nurturing automation based on users behaviors.
For mid-market and SaaS companies, the primary use-cases are around building
scoring system, for account grading or churn scoring, or doing lead routing according to their own territories and rules.
Interested to learn more? Join the movement here