Data warehousing as a service (DWaaS) is an outsourcing model that provides data warehouse configuration and management. Like other software-as-a-service (SaaS) offerings, DWaaS offers many benefits, including improved usability and removing the responsibilities associated with setting up a data warehouse. Many industries use DWaaS to stay ahead of the curve, including retail, healthcare, and insurance.
Read on to learn more about data warehouses, data warehouse architecture, and the differences between data warehouses vs. data lakes vs. databases. We'll also cover how DWaaS providers work, the pros and cons of DWaaS, and examples of DWaaS in action. By the end of this guide, you'll know whether DWaaS is worth it.
What Is a Data Warehouse?
Before diving into DWaaS, let's look at what a data warehouse is.
Also known as an enterprise data warehouse (EDW), a data warehouse is a data management system that supports and enables business intelligence (BI) activities, such as analytics.
Data warehouses contain large amounts of data and are used to perform queries and analyses. Data flows into a data warehouse from various sources, including relational databases and transactional systems. Data engineers, business analysts, data scientists, and decision-makers access the data via SQL clients, BI tools, and other analytics platforms.
Examples of data warehouses include:
- Azure and Amazon data warehouse as a service
- IBM DB2 Warehouse
- Oracle Autonomous Data Warehouse
- Teradata Vantage
Data Warehouse Architectures
There are three types of data warehouse architectures:
Single-Tier Data Warehouse Architecture
These data warehouses are rarely used. Companies can use them to reduce the amount of data stored.
Two-Tier Data Warehouse Architecture
Two-tier data warehouses have two layers: a staging area for all data sources and a data warehouse layer. The staging area is responsible for cleaning and transforming the data into the right format.
Three-Tier Data Warehouse Architecture
The three-tier approach is the most common architecture for data warehouses.
The top tier is the front-end that shows results through data mining tools, reports, and analyses, while the middle tier is the analytics engine that is used to access and analyze data. Finally, the bottom tier is the database server that stores and loads data.
What's In a Data Warehouse?
Data warehouses typically contain multiple databases.
Databases are organized collections of data stored in columns and tables. Each column contains a description of the data, such as data fields, integers, and strings. Tables tend to be organized within schemas, which describe how the data may relate to other data models or tables. Database query tools use schemas to determine which tables to access and analyze.
Data Warehouses vs. Data Lakes vs. Databases
Although they sound similar, data warehouses shouldn't be confused with data lakes and databases.
Databases contain less data than data warehouses and are often used to support Online Transaction Processing (OLTP). Data scientists and other professionals can use database management systems (DBMS) to store and access data in databases.
Common databases include:
On the other hand, data lakes are repositories of data from different sources that are stored in their raw, original form. Like data warehouses, they store much more data than databases. The main difference between data warehouses and data lakes is that the latter can store a wider variety of data formats, including Avro, JSON, CSV, Parquet, BSON, and TSV.
Examples of data lakes include:
- Amazon Web Services S3
- Google Cloud Storage
- Azure Data Lake Storage Gen2
When Should You Use a Data Warehouse?
You should use a data warehouse to:
- Store large amounts of historical data
- Perform thorough analyses of your data to generate actionable business insights
Extracting data from a data warehouse is quick and easy due to the highly organized structure of data warehouses. Note, however, that data warehouses are not the best choice for OLTP. If you need a data warehouse and something to power OLTP, consider getting a separate database or databases. Databases are a much better fit for OLTP.
What Are the Benefits of Data Warehouses?
Data warehouses provide many benefits, including:
- Informed decision making
- The ability to store and analyze historical data
- Improved data quality, accuracy, and consistency
- The ability to consolidate data from multiple sources
- The ability to separate analytics processing from transactional databases
How Does Data Warehouse as a Service Work?
Now that you know what a data warehouse is, let's look at how data warehouse as a service and cloud works.
DWaaS is a business model where a service provider manages and configures a data warehouse on behalf of the customer. In return, the customer pays for the service and provides the data.
Companies with small or limited tech teams should consider using DWaaS to derive actionable insights and perform analytics in the cloud. DWaaS are also a great way to:
- Cut hiring costs
- Ensure data quality
- Access data faster
- Make predictions faster
- Consolidate data from various sources
DWaaS services vary depending on the vendor. Here are some of the most common DWaaS offerings:
1. Data Warehouse Configuration and Development
First, the DWaaS provider will look at your business strategy and provide a customized data warehouse solution. They will then configure and develop the data warehouse according to your company goals and values.
2. Data Warehouse Integration
Next, the provider will seamlessly integrate your data warehouse with your existing analytical and data sources systems.
3. Data Migration and Cleaning
The DWaaS provider will create a customized migration strategy and apply it to your IT systems. This will quickly process and transfer your data to the data warehouse. The provider will also clean and test the data for completeness and accuracy.
4. Continuous Administration and Support
After data migration and cleaning, the DWaaS provider will continue providing data administration and support services. Specifically, it will continue:
- Ensuring high data quality
- Integrating new data sources
- Ensuring high data warehouse performance
5. On-Demand Data Warehouse Configurations
The DWaaS vendor will scale with your needs and provide on-demand data warehouse configurations when needed.
DWaaS Pros and Cons
Data warehouse platform as a service has many advantages, including data consolidation, high-quality data, proactive alerts, and quick disaster recovery. Unfortunately, it also has some disadvantages, such as security issues, high costs, and third-party costs.
DWaaS platforms provide many pros, including:
DWaaS services consolidate data from different sources, acting as a "single source of truth" for your company. With DWaaS, users no longer need to connect to dozens of systems to access data — they can just go to the DWaaS and pull the information they want. Stakeholders can also use DWaaS to perform ad-hoc queries on the same dataset from different locations.
DWaaS provide highly accurate and consistent data. Unlike their in-house counterparts, DWaaS are more likely to apply a consistent set of semantics to data, such as codes for different currencies and product types and naming conventions. Accordingly, data is easier to find, query, and analyze.
The best DWaaS programs proactively send you alerts about data discrepancies. They can also rectify inaccuracies and other problems before and after you enter data.
Quick Disaster Recovery
Like other SaaS, DWaaS providers are an excellent way to backup your data.
Because everything's in the cloud, you will continue to have access to your data even if your computers, servers, and office are hacked or destroyed. Moreover, DWaaS don't require additional hardware — they typically have built-in data duplication. In other words, they can instantly copy your processes and save them to the hub. Some DWaaS service providers may also provide specialized networks for additional security.
High Data Storage Capacity
On-premise storage are expensive and time-consuming to scale. Think about it: the more data you have, the more storage you have to buy. In contrast, cloud solutions like DWaaS are much easier to scale. Just pay more and your provider will instantly give you more storage.
Finally, DWaaS tend to be much less expensive than on-premise data warehouses. Unlike their in-house counterparts, DWaaS don't require:
- Manual updates
- Expensive hardware
- Server or networking rooms
If your business is entirely online, you won't even have to invest in office space. All you need is a DWaaS subscription and a computer with the right amount of computer power and storage.
The drawbacks of DWaaS include:
DWaaS usually have ironclad firewalls and other security measures, but they're not 100% safe. Any relationship with third parties can lead to cyberattacks since their cybersecurity policies may have exploitable gaps or loopholes.
Data warehousing as a service is usually less expensive than in-house data warehousing solutions.
However, that doesn't necessarily mean DWaaS solutions are cost-effective. Depending on the complexity of your data, your industry, and the size of your organization, implementing a DWaaS solution can cost anywhere from $300 to 3 million. Additionally, some vendors may charge exorbitant amounts for additional tools and features.
Lastly, you may need to hire a third-party data science or BI team to use DWaaS solutions. Although most DWaaS are user-friendly, some are notoriously difficult to use, especially if your tech team has limited expertise and experience.
Examples of DWaaS in Action
Many industries use DWaaS for their day-to-day operations. Here are the top industries that use data warehousing as a service for their day-to-day operations.
DWaaS are commonly used in the healthcare sector to:
- Create treatment reports
- Research trends
- Predict outcomes
- Share data with insurance providers and other parties
- Manage billing and documentation
- Reduce errors in medical management and operation
Healthcare providers also use DWaaS to document compliance with third parties, such as clients, the Health Insurance Portability and Accountability Act (HIPAA) enforcement agency, and the Office for Civil Rights (OCR). They accomplish this by using the DWaaS to:
- Control access to Protected Health Information (PHI)
- Log and archive data usage according to HIPAA requirements
- Create, test, and securely store backups
- Store PHI in high-security infrastructure that is fully HIPAA-compliant
- Encrypt all health data in transit and at rest
Retail service providers use data warehouses for marketing and distribution. They use them to:
- Identify and differentiate customers by their behavior, products purchase, and other factors
- Identify customer needs
- Examine competitors' pricing policies
- Analyze customer buying trends
- Track promotional deals
- Track items throughout the store
- Forecast industry trends
- Optimize ads and marketing spend
Insurance and Investment
DWaaS are primarily used in the insurance and investment sector to analyze market and customer trends. Data warehouses are especially important in stock and forex markets, where they're usually used to share and stream real-time information.
Is It Worth It?
Are DWaaS worth it? The answer depends on your industry and budget.
If you have a large budget and you're in an industry where DWaaS are ubiquitous, consider getting a DWaaS. A DWaaS solution will empower you to stay ahead of your competitors, especially if you're in a highly-competitive niche like eCommerce and insurance.
On the flip side, if you have a small budget and your competitors don't usually use DWaaS, you can hold off on getting a DWaaS. As covered above, DWaaS can be prohibitively expensive, especially if you have a lot of complex data.
In the meantime, you can hire a data science team to gather and analyze data. You can also get a BI platform to meet your basic data needs. Modern BI platforms provide many DWaaS-adjacent solutions, such as:
- Extracting data from multiple sources: Most BI tools integrate with a range of data extraction tools.
- Creating a single source of truth: Like DWaaS, modern BI systems empower you to gather information into a single hub that all users can access.
- Optimizing data into visual dashboards for reporting: Data scientists, data engineers, and other professionals can use dashboards to evaluate progress.
Hire First-Class Data Warehouse Experts With Revelo
DWaaS platforms provide many benefits, such as data consolidation, high-quality data, and reliable disaster recovery. However, they can be challenging to use, especially if you have limited data warehouse and data science experience.
That's where Revelo's data warehouse experts come in. As Latin America's premier tech talent marketplace, we have thousands of pre-vetted data scientists, data engineers, and other DWaaS experts who can help you derive actionable insights from data.
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