Why Building A New Data Warehouse Is A Bad Idea (7 Things To Consider)

As companies scale, so do their data storage needs to handle the increasing amount of information and data that’s being generated.

From experimenting with data marts to data lakes, organizations usually settle on a data warehouse solution as it provides a whole host of benefits – from enhanced data quality and consistency to better utilization with business intelligence solutions.

However, one of the biggest mistakes companies make is to undertake the building of their own on-premise data warehouse without fully realizing the full enormity of the task.

Even with the rise of cloud computing and cloud data warehouse solutions such as Snowflake, Amazon Redshift, and Cloudera, many companies still entertain the idea of developing their very own on-premise data warehouse.

While this might initially seem like an exciting task to physically ‘own’ and house your proprietary data, building one brings with it more challenges that many organizations do not anticipate.

If you wouldn’t build your own accounting software, CRM platform, or physical office space, building a new data warehouse shouldn’t be on the cards!

In this article, we will bring you through why building a new data warehouse is a bad idea that will likely drain your financial and manpower resources even before you can utilize it for any meaningful data analysis.

7 Reasons Why You Shouldn’t Build Your Own On-Premise Data Warehouse

1. Huge Upfront Capital Investment Needed

Unlike cloud data warehouses, building an on-premise data warehouse will require you to fork out huge capital costs upfront before a single byte of data is even stored.

This includes a myriad of capital investment that will go towards:

• Purchasing the necessary hardware: This includes the data storage servers and networking cables to name a few
• Designing the data warehouse: This will entail everything from requirements gathering to the drafting of disaster recovery plans
• Setting up the physical environment: From purchasing a physical location to outfitting the server rooms with the required hardware and racking

Depending on your initial storage requirements, the cost (including labor and technical expertise) can easily mount up to hundreds of thousands or even millions of dollars.

This makes building a new data warehouse highly prohibitive to startups and growing companies as well as poses a significant financial commitment event to established organizations.

However, for a cloud SaaS data warehouse, you’ll only need to pay for what you use, the upfront capital burden is already borne by the service provider.

2. Continuous Operating & Maintenance Cost To Factor In

With an on-premise data warehouse, the costs don’t just stop at the upfront investment to get it up and running.

Owning an on-premise data means the burden of keeping it operational 24/7 is on you. It is estimated that the cost per kW for data centers between 500 and 5,000 square feet can reach above S$26,000, which adds up quickly for any organization.

Additionally, like any hardware system or machinery, your data warehouse will have to be maintained to ensure optimum utilization, especially when it’s time to analyze the data for insights generation.

Depending on the configuration and storage size of your on-premise data warehouse, it could easily start from thousands of dollars a month and spiral to tens of thousands as your needs grow.

3. Requiring An IT Support Team To Operate Your Data Warehouse

A key component of data warehouse design is setting up the right data models which are essential for visualizing data distribution throughout your warehouse.

This will require you to hire the necessary IT personnel to execute this vital step. 

In addition, your data warehouse will require the combined expertise of a team of IT experts that include an information systems manager, developer, and data analyst in order to perform ETL operations and ensure your data warehouse is up and running at all times.

An experienced information systems manager for example will cost you on average US$84,000 while a data analyst will likely set you back US$61,000.

This will easily translate into a high operating cost which will likely be unfeasible for smaller companies to take on.

4. Limited Flexibility To Scale Up Or Scale Down Your Data Storage Needs

Unlike cloud data warehouses, the storage availability on your on-premise data warehouse is likely to be fixed and can only be scaled to the limits of the initial set-up.

As companies grow and evolve, so do their data storage needs. An on-premise data warehouse limits the ability to scale your storage requirements as and when you need them.

Looking to triple your data storage capacity? 

Not only will you have to allocate more space in your physical premises (if any), there will also be additional upfront investment costs and a lag-time before your additional data storage space becomes available.

Perhaps you desire to only use half of your total storage space? 

While that is possible, you’ll still be paying maintenance costs (as well as suffering depreciation costs) as a whole for your entire data warehouse. At the very best, you will be underutilizing your facilities that translate into an opportunity cost of your initial capital investment.

With cloud data warehouses such as Snowflake, you only pay for the storage that you use, allowing your organization to rapidly scale up your data storage needs or shrink it depending on your situation.

In addition, cloud data warehouses allow you to independently scale your storage needs without disrupting your other computer and cloud services layer. This allows you to avoid additional costs on capabilities that don’t need to be scaled up and focus only on storage.

5. No Seamless Integration To Data Analytics & Business Intelligence Tools

The purpose of storing your data in a data warehouse is to analyze it and gain actionable insights to improve your business.

Building your very own data warehouse will require you to create a backend online analytic processing (OLAP) cube and your own front-end visualization or at least utilize 3rd-party tools that will help you meet your analytics needs.

Many self-service BI solutions require data analysts to help with the initial configuration and the integration of your data warehouse to the analytics tool – this means the need for an IT team as well as time to execute it.

However, with a cloud data warehouse solution, this integration will be much easier, allowing you to reap the full benefits of modern business intelligence.

Many cloud BI tools today, such as QBO, can be seamlessly integrated into the data warehouse, allowing the average user to get started with data analytics without much delays or technical hassles.

6. Data Warehouse Reliability & Security Issues Will Have To Be Handled In-House

Having 24/7 access to your data is essential, especially when your business relies on it to run and business processes become more interconnected.

If you notice a recurring theme, when you are building your own data warehouse, every aspect of its creation, maintenance, and yes, security will fall on your shoulders. 

From mitigating security and privacy breaches to providing the right authorization for user access, the expertise and cost needed to maintain enterprise-grade security for your data warehouse shouldn’t be taken lightly.

While it might seem more secure that your data is safely stored within your premises and not a third-party SaaS storage solution, your data could be copied (intentionally or unintentionally) by your employees and vendors by means of a physical hard drive.

This could result in a potential data breach which could have dire consequences for your organization, especially if sensitive data such as customer details are leaked out.

Additionally, physical security is necessary that could include the procurement of surveillance cameras, physical fences, and security personnel will be necessary to prevent any unauthorized access to the premises.

However, with cloud data warehouses, the responsibility of securing your data falls on the provider themselves. A robust SaaS data warehouse will provide enterprise-level data security and a whole host of security features such as:

• Network and site access
• User and group administration roles
• A variety of user authentication methods
• Data encryption security
• Security compliance validations

By selecting a cloud data warehouse option, you’ll not only save on security costs but also have peace of mind that the vendor will be utilizing the latest security measures to safeguard your data and your business.

7. Longer Deployment Time

Unlike a cloud data warehouse, a physical on-premise option will entail a much longer deployment time.

This comes from the need to design and develop the warehouse and testing it before it goes live, a process that could take months and cannot be skipped. 

The need to test security practices to ensure ETL protocols work smoothly is important to prevent sudden downtime due to server overloads or errors. This necessary step will cause a delay in your data warehouse’s deployment time, preventing your organization from analyzing your data.

A longer deployment phase leads to idle time and potentially missing time-sensitive business opportunities that might never arise again.

Skip The On-Premise Data Warehouse Project

In today’s competitive environment, utilizing data swiftly and in real-time is key to capture opportunities to chart your business forward.

This means placing a premium on data warehouse capabilities such as scalability, reliability, and speed. The future of databases and data warehousing is in the cloud.

With a SaaS data warehouse, you’ll enjoy faster deployment, pay only for what you use, and be reassured that your data is safe and secure. This allows you to focus on what matters – utilizing your data to generate insights for better business decision-making.

Maximize Your Data Warehouse Investment With QBO Today

At Unscrambl, we seek to transform organizations with our BI tool, Qbo. Powered by conversational analytics, users will be able to ask questions to their data to gain actionable insights that move the needle.

Ready to unlock true data democratization for your organization?

Embark on a free 14-day trial of Qbo and see for yourself how easy it is to unleash the true potential of business intelligence.