Modern day enterprises depend on efficient gathering, storage, integration, and analysis of business data that comes in from multiple sources. These analysis activities, which were once considered good to have practice, are today playing a major role in how businesses generate revenue, contain costs, and optimize profit.
The need of the hour is robust cloud solutions that would enable managing and analyzing big data quantities across organizations. These solutions should be reliable, scalable, and secure to support a variety of use cases and data types. This is where cloud data warehousing comes into the picture.
There is an evident sign of growth in the segment. So much so that the cloud data warehousing market is poised to grow by USD 10.42 billion from 2021 to 2026, at a CAGR of around 22.56%.
What is a cloud data warehouse?
A cloud data warehouse is a database that is stored as a managed service in the cloud and is optimized for analytics and scalable business intelligence. Unlike traditional data warehouses, which were not engineered for explosive data growth, cloud data warehouses allow you to grow or scale down the warehouse depending on business needs and budgets.
It stores data from a range of different sources like CRM, IoT, finance system, etc. and because the data is placed in a highly unified and structured manner, it comes ready for application of analytics and business intelligence.
What is a cloud data warehouse used for?
Cloud-based data warehouses bring in a lot of use cases for businesses. Some of the top applications are:
Consolidation of siloed data
Cloud data warehouse solutions enable pulling of data from a variety of structured sources across a business. These sources can be emails, websites, point-of-sale systems, and then bring them into one place so that analysis can be performed on them to gain insights.
Making decisions in real-time
Cloud data warehouse architecture helps analyze data in real time. This helps in proactive addressing of challenges, identification of opportunities, better efficiency, reduced costs, and better response to business events.
Enabling custom reporting
Generally, cloud data warehouse services keep the historical data on a different server compared to where they keep the operational data. This way, the end users can access them and run their own queries without leaving an impact on the operational systems’ performance or help from IT.
Incorporation of machine learning and AI
A well-thought of cloud data strategy enables collection of both historical and real-time data for building algorithms which can offer predictive insights like anticipation of the spike in traffic, suggestion of relevant products to the customers, etc.
While these are surface level use cases of the technology, there is a reason why there is a rise in the cloud data warehouse market size and its application. And those reasons lie in the benefits of cloud data warehouse solutions.
What are the advantages of using a cloud-based data warehouse?
Modern cloud data warehouse architecture merges the abilities of data warehousing, scalability of big data and the cloud elasticity at a portion of the traditional data warehouse cost. Let us look at the benefits that this cloud computing combination brings to an organization.
Speedier insights: Cloud data warehouse platforms provide powerful computing abilities, and are built to deliver real-time analytics through data coming in from multiple sources at a much faster rate compared to the on-premise warehouses. This enables businesses to access insights much faster.
Scalability: A cloud based data warehouse comes with real-time, more or less unlimited data storage which is easy to scale as the business need grows. What is great about cloud data warehousing is that you don’t have to buy new hardware to accommodate the explosive growth of data..
Overhead: Managing the traditional warehouse called for having a specific server room filled with a range of expensive hardware, and the inclusion of skilled employees to manage, manually update, and solve issues – a recipe for great costs. Cloud data warehouse architecture requires zero hardware or office space, bringing the costs significantly down.
I know up until this point you would have established that cloud data warehousing would be the best choice for your organization. But, how does it work on the cost front? Let us look into that next.
What are the components of cloud data warehouse cost?
There are several elements that make up to the cost of a cloud data warehouse. Here are what those are:
The most direct price you will have to pay will be around software and hardware infrastructure costs. For the traditional data warehouse, you have to pay for the servers, licenses, and storage. In the case of cloud data warehouses, however, the pricing is often decided upon the computing power since there is no infrastructure cost involved. And this price range varies from one warehouse provider to another.
When adopting cloud, accounting for a team of skilled people becomes equally important. Now, whether you plan on hiring a cloud computing service agency or employ an internal team, you will have to factor in the cost for –
- Data engineers – They will model data and optimize warehouse for performance
- Analysts – They will help define the problem the data warehouse will solve
- Managers – They will look over the data warehouse setup and oversee development and maintenance.
The last cost element that you will have to account for is the opportunity cost. Imagine it takes you one year to set up a cloud data warehouse, what would be the business cost in this duration when you are deprived of the insights. You should also account for the cost of the team that will be working on this while they could be working on some other project.
If you are using SaaS data warehouse, you will have to add in the SaaS vendor price and measure them against your needs. For example, if the vendor is charging for per terabyte of storage, you will need to identify the storage your cloud data warehouse will be needing.
Maintenance and engineering costs
In case of a cloud data warehouse which is usually managed, the maintenance costs tend to be a part of the monthly fees. However, there are two parts to this cost. Part one is the ongoing cost like performance tuning and then there’s the unanticipated costs of when you’ll have to restructure the parts of the data warehouse according to business needs.
The last cost you will have to consider is the cost of tools. Based on which vendor you choose, you would have to purchase tools which make it easy to transform data. A number of data engineers use tools like Fivetran, Stitch, Matillion, etc, to perform data transformation. These tools, in turn, come with a cost.
An amalgamation of these elements would together define the cost of implementing the cloud data strategy. To make things a little easy, here’s a snapshot of cloud data warehouse comparison based on cost.
If your warehouse needs are less than 1TB, the cost would run anywhere between $0.25/hour to $4.80/hour. If you need more storage, you would have to pay around $0.85/hour to $6.80/hour, with an extra charge of $0.024/GB/month for storage purposes.
Google BigQuery estimates the warehouse costs on the basis of computation and storage. Storage would cost around $0.02/GB/month. All the data which is left unused for 90 days gets moved to long-term, which would be somewhere around $0.01/GB/month.
In the case of Azure, the data storage cost is estimated at $122.88/TB/ month. It also enables you to buy systems for disaster recovery and threat detection for additional costs.
Snowflake cloud data warehouse
Snowflake comes with a unique computation price. It asks you to buy a virtual warehouse that either has one server or a mix of servers. The cost of these virtual warehouses are based on the version you choose. The most cost effective one is two credits/hour, which comes out to be $2/hour.
Snowflake cloud data warehouse storage starts at the flat rate of $23/TB/ month.
So here was the basics of what is cloud data warehouse and the benefit and cost of cloud based data warehouse.
While this was a primer article, we wanted to limit it to the basics of the technology and the cost elements if you decide to ditch the traditional data warehouse route. However, the cloud data warehouse as a technology is far reaching. There are a number of different aspects that an entrepreneur needs to consider when migrating from traditional to cloud data warehouse. We can make the process simple for you. Get in touch with our cloud data experts today.