A Salesforce Admin’s Guide: Data Lakes vs. Data Lakehouses
Salesforce Admins are increasingly finding that their responsibilities extend beyond just managing the application. While your primary focus has always been to ensure the integrity and security of your Salesforce data, you’re now playing a key role in helping your organization effectively use and consume its data. Data-driven decision-making is no longer just a buzzword—it’s becoming a rapid reality. To derive actionable insights, it’s crucial to understand the differences between data lakes and data lakehouses.
This post builds on our previous discussion about data lakes and introduces the concept of data lakehouses, helping you determine the best solution for your Salesforce environment.
Quick Refresher: What is a Data Lake?
In our previous post, “A Salesforce Admin’s Guide to Data Lakes,” we explained that data lakes are dynamic repositories designed to collect, store, and secure a wide range of data types. To briefly recap:
- Data Lakes collect, store, distill, process, and make data available for consumption. They serve as vast repositories for large volumes of structured and unstructured data, allowing you to maintain data from various systems in its natural form for scalability and flexibility.
- Customer 360 Data Lake takes a specialized approach by ingesting data from all customer interactions and touchpoints to create a comprehensive view of the customer. This centralization of customer data enhances analytics and enables rapid, informed decision-making.
- Salesforce Data plays a crucial role in enriching the Customer 360 view, ensuring that your data lake is built on a strong foundation of customer data.
- Generally, data lakes are more cost-effective for storing large amounts of data compared to traditional databases, making them suitable for backup storage and data analytics.
For a more detailed overview, refer to our previous post and video on data lakes.
Now that we’ve revisited data lakes, let’s explore how data lakehouses build upon this concept and extend these capabilities to offer an even more versatile and scalable solution.
Introducing Data Lakehouses: The Next Evolution
What is a Data Lakehouse?
A data lakehouse is a modern data architecture that combines the best features of both data lakes and data warehouses, offering a cost-effective, flexible, and highly performant solution. This evolved approach provides greater versatility and control over your data, enabling more effective use of machine learning, business intelligence, and predictive analytics.
Data Lakehouse vs. Data Lake vs. Data Warehouse
Although data lakehouses blend elements of both data lakes and data warehouses, it’s essential for Salesforce Admins to understand their similarities and differences. This knowledge will help you select the best data strategy for your organization’s customer data.
How Does a Data Lakehouse Work?
At its core, a data lakehouse is a hybrid solution that merges the advantages of data lakes and data warehouses, allowing you to benefit from both without compromise. Key features of a data lakehouse include:
- Data Management Functionality: Enables schema management, enforces data governance, and supports ETL (Extract, Transform, Load) processes and data cleansing.
- ACID Transaction Support: Ensures data consistency when multiple users are updating, deleting, reading, and writing simultaneously.
- Unified Data Storage: Supports various data types, accommodating diverse data and analytical workloads.
- High-Performance Query Engine: Optimized for advanced analytics and lightning-fast queries, reducing latency and enhancing data operation performance, including near-real-time analytics.
- Business Intelligence Tools Integration: Tools like Tableau, Salesforce Data Cloud, CRM Analytics, AWS QuickSight, and PowerBI can directly connect to the data lakehouse with ease, streamlining data-driven decision-making.
With a data lakehouse, your organization can leverage Salesforce data to create a comprehensive Customer 360 view, enabling complex queries and advanced reporting based on your entire Salesforce history.
How to Get a Data Lakehouse With GRAX
GRAX offers a solution that covers your entire Salesforce data lifecycle, from data protection (backup and recovery) to data reuse. The GRAX Data Lakehouse simplifies the process of leveraging your Salesforce history for reporting, training, and decision-making, allowing you to focus on answering business questions instead of managing complex data operations.
The GRAX Data Lakehouse combines the flexibility and performance of a data lake with the capabilities of a data warehouse, giving you full control and access to your data under a unified data platform that:
- Deploys a data lakehouse quickly and easily, without the usual headaches.
- Makes data available the same day for timely advanced analytics.
- Delivers lightning-fast query results, enabling you to explore your history effectively.
- Provides unlimited data replay without additional Salesforce API calls.
- Automatically handles schema changes by capturing all your history.
- Maximizes data reuse, allowing you to use your data with any industry-standard BI tools without building integrations.
As the role of Salesforce Admin continues to evolve, it’s critical to invest in a solution that not only protects your data but also ensures you get a return on your investment. A data lakehouse allows Salesforce Admins to manage and protect data more effectively while unlocking its full potential, driving innovation, and achieving business goals.
Explore the GRAX Data Lakehouse to see how GRAX can help you create a seamless, secure, and scalable data strategy that empowers your organization to make better, data-driven decisions.
