The Evolution of the Modern Cloud Data Warehouse

Someone starting a small business – think custom t-shirts, candlemaking, etc. – could probably operate out of their home, keeping their basic supplies and inventory in a spare room, closet, or garage. If their business were to take off and experience exponential growth, however, this type of operation would quickly become ineffective. As supply and demand grow, they’ll need to adapt their storage and manufacturing resources accordingly to scale their business to the next stage.

In the same fashion, the burgeoning supply of and demand for business-driving data is requiring modern organizations to reassess their capacity to store, access, and analyze these resources at scale.. To keep up with the most recent era of cloud-based technology, more businesses are rapidly transitioning their data warehouse architectures to the expansive and flexible cloud.

In this blog, we’ll assess the evolution of the modern cloud data warehouse, exploring the differences between traditional and cloud-based solutions, and sharing how teams can reap the full benefits of these dynamic platforms and tools.

What is a Data Warehouse?

A data warehouse is a system of data management that supports business intelligence-related activities such as data analytics (check out our blog to read more about data intelligence vs. data analytics). These warehouses bring together various disparate data sources into a single integrated repository. Typically, data warehouses contain large amounts of historical data and are used exclusively for querying and analysis.

Data stored in data warehouses can come from a variety of sources, including application log files, transaction applications, and more.

In general, data warehouses consist of:

• A relational database for storing and managing data
• An ELT (extraction, loading, and transformation) platform for preparing data
• Analysis tools for presenting data in a visual format
• Statistical analysis and reporting tools
• Data mining capabilities

Data warehouses tend to be subject-oriented, stable, highly integrated across data sources, and capable of providing analysis of how data changes over time.

A quality data warehouse will be capable of performing fast queries, delivering a high level of data output, and being configured for maximum flexibility to meet an organization’s unique needs. It should also be able to provide a ‘bird’s eye’ view of data, as well as granular analysis at a more detailed level.

What is a Traditional Data Warehouse?

What exactly is the difference between a traditional data warehouse and a modern cloud data warehouse? For starters, cloud data warehouses are growing in popularity and use, while traditional data warehouses are being used less frequently. But there are other key distinctions that differentiate one from the other, both in the way they’re used and the features and structures they offer.

A traditional data warehouse is built based on a three-tier structure:

1. Bottom Tier: On the bottom tier you’ll find the database server, which is used to pull data from a range of sources such as front-end transactional databases.
2. Middle Tier: Next is the middle tier, which houses an OLAP (online analytical processing) server designed to transition the data from its raw form to a structure that is more accessible and interpretable for querying and analysis. The OLAP server can either serve as a relational database management system or as a multidimensional model that directly implements data and operations.
3. Top Tier: Finally, the third tier acts as the client interface layer. This is where user interaction with the data takes place. On this tier, high-level data analysis, querying, reporting, and data mining are all possible.

Traditional data warehouses can be virtually composed of separate databases or use a data mart model, wherein data is collected from a range of systems specific to lines of business, such as finance. There’s also the enterprise data warehouse model, wherein the data warehouse contains an aggregate of all data pertaining to the entire organization.

What is a Modern Cloud Data Warehouse?

While the traditional data warehouse architecture has been the de facto method for many years, a growing number of organizations are moving their warehouses to the cloud to leverage their more dynamic and scalable capabilities. Not only do these modern cloud data warehouses not follow the structures outlined in the previous section, but each individual cloud data warehouse platform offers a completely different structure and feature set.

There are many emerging cloud data warehouse platforms, but some of the most widely used include Amazon Redshift, Azure Synapse, and Google BigQuery. The Snowflake Data Cloud also supports data warehousing initiatives, and the Databricks Lakehouse combines the benefits of data warehouses and data lakes, another popular cloud management model.

Modern Cloud Data Warehouse Architecture

Modern cloud data warehouse architectures may look different from one platform to the next, but they’re all designed to meet the same core need — managing all types of data, unique workloads, and advanced analysis. Each component of the modern cloud data warehouse is designed to integrate closely to serve IT, analytics, data science, or engineering teams. And while they may differ in their overall designs, most modern cloud data warehouse architectures include:

• A converged database, which is one that has native support for all modern data types.
• Self-service ingestion services that automate ingestion and make it simple for non-technical users to collect data from a range of sources and direct it to a shared location.
• Support for machine learning (ML), spatial processing, and SQL.
• Options to simplify data analysis without having to move the data, in order to centralize to one source of truth and enhance ease of access and effective security.

Benefits of a Cloud Data Warehouse

Wondering whether the transition from a traditional data warehouse to a modern cloud data warehouse is worthwhile for your organization’s needs? Low-overhead cloud-based solutions have made the transition process seamless, but there are five additional benefits of making the switch:

Expanded Data Access

Data stored in a modern cloud data warehouse can be accessed and analyzed from anywhere, providing data analysts and company stakeholders with real-time insights from the full range of data sources. This can help democratize data access and use across teams, quickening time-to-data for faster business-driving insights. In today’s business environment, fast analysis enables more streamlined decision-making and less waste.

Ease of Maintenance

Modern cloud-based data warehouses don’t require software upgrades, can be easily expanded or retracted based on evolving data needs, and are able to be monitored from anywhere. They don’t require physical maintenance or upkeep and aren’t beholden to limited on-premises storage spaces.

Cost Savings

Since cloud data warehouses don’t require physical hardware onsite or constant software updates, and because they can be run remotely, they’re typically far less costly to setup and maintain than traditional data warehouses. Scaling is also extremely cost-effective, and the risk of irreversibly allocating too many resources to data storage is virtually eliminated.

Seamless Scalability

A modern cloud data warehouse can be scaled much more quickly, simply, and inexpensively than a traditional data warehouse. Why? Modern cloud data warehouses don’t require organizations to acquire additional hardware in order to scale, like traditional, onsite data warehouses do. Additionally, scaling can be automatically adjusted based on a company’s unique and ever-changing needs.

Flexibility When Choosing Cloud Vendors

Maintaining a modern cloud data warehouse also means enjoying the ability to choose from a wide array of vendors in the cloud data management space. For example, the Immuta Data Security Platform is designed to integrate seamlessly with your modern cloud data warehouse to provide continuous protection and simplify access management at any scale. The ability to scale across platforms without vendor lock-in allows you to choose best-in-class solutions that are suited to your organization’s specific needs.

How to Migrate to a Cloud Warehouse

Looking to migrate your traditional cloud warehouse to a cloud-based solution? Immuta can help. Our data security platform integrates across cloud data warehouse platforms, so you can select the vendor of your choice, seamlessly integrate technologies, and ensure that your data – even the most sensitive – is always kept secure and accessible only by those with authorization.

Want to learn more? Check out our white paper Best Practices for Securing Sensitive Data for a deeper dive into data security throughout the cloud migration process. To dig deeper into secure cloud warehouse migration, request a demo from the Immuta team.