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We have seen an unprecedented increase in modern data warehouse solutions among enterprises in recent years. Experts believe that this trend will continue: The global data warehousing market is projected to reach $51.18 billion by 2028. 

The reason is pretty obvious – businesses want to leverage the power of data to make winning decisions, and a robust data warehouse makes it possible.

A data warehouse’s definition is quite simple. It is a system that allows combining data from multiple sources and stores it for analysis, reporting, and business decision-making.

If you have been planning to adopt a data-driven approach to make your company agile and forward-looking, it’s essential that you do your homework to pick the right solution. 

Choosing the Right Data Warehouse Solution Is a Critical Decision

A data warehouse allows you to centrally store all your business-critical data and run queries to perform analytics. It unifies the valuable information trapped in silos to get a holistic view of the operations and performance of your organization and make data-driven decisions. 

All in all, a robust data warehouse serves as a centerpiece for data analytics and helps you keep up with changing business requirements. Choosing the right solution will help you take new business initiatives, provide exceptional customer experience, and introduce new revenue streams.

On the other hand, a lot can go wrong if you take this decision lightly. It can result in wasted time and resources. Another concern would be inaccurate, outdated insights that can lead to the wrong business strategy, affecting the bottom line of your business.  

Factors to Consider When Choosing a Data Warehouse Solution

Here are some of the critical factors that you should keep in mind when choosing an enterprise data warehouse solution:

1. Business Requirements

It is imperative to determine your business needs and specific use cases. Understanding the requirements of a data warehouse project can be tricky, as enterprises must deal with changing business conditions. 

You may consider evaluating data warehouse solutions based on capabilities instead of their ability to provide specific report outcomes as your business requirements will evolve over time.

For instance, the primary objectives of health care facilities are improved operational efficiency and quick access to insights. But their requirement keeps changing due to uncertain conditions, like a spike in the number of patients due to COVID-19.

For that, an automated data warehousing tool can be helpful. It will offer shorter iteration periods that allow adapting to new requirements quickly.

Remember, a data warehouse is more than a system just to satisfy the reporting requirement. You will want to view and analyze data in different ways to gain meaningful insights and make data-driven decisions. 

The identified business processes will help you create a baseline to evaluate different data warehouse solutions and make an informed decision.

2. Cost Estimations

A detailed estimation of data warehouse costs is essential before investing to ensure a positive return on investment (ROI). 

Many costs associated with a data warehouse are often ignored or understated, including deployment costs, data management costs, opportunity costs, procurement costs, maintenance costs, etc. 

The total costs during a lifecycle of a data warehouse system must be estimated to ensure it adds value to the company. The total cost of ownership may vary, depending on whether you decide to buy or develop your own data warehouse.

Keep in mind that cost estimation is necessary, but it is essential not to get solely fixated on costs and evaluate the project based on the value it can bring to your business. 

For instance, an agile cloud data warehouse solution can minimize the time-to-market for your enterprise and help generate more revenue, potentially offsetting the extra costs and investment. 

Moreover, using an automated data warehouse builder can reduce costs and eliminate infrastructure, human resources, and maintenance overhead.

3. Capabilities and Technology 

It is crucial to learn about the capabilities you’ll need to ensure that you’re getting the best data warehouse solution for your organization. Each provider will offer you different data warehousing tools and technologies. You must pick the one that satisfies your business requirements. 

In today’s digitized environment, organizations have data coming from different sources. Data from SaaS products, data stored in JSON format, structured and unstructured data from various data lakes – there is no limit to it. 

Therefore, you need a data warehouse architecture that offers built-in connectivity to all the different sources, allowing you to integrate data seamlessly. After all, data warehouse technology is all about eliminating data silos and having a repository of information to support business intelligence. 

For that, you need a data warehouse solution with advanced capabilities like Data Modeling, data mapping, Data Quality and profiling, ETL/ELT capabilities, job scheduling, connectivity to BI tools, and more. It will ensure you can load data into the warehouse and perform analytics to derive meaningful insights. 

Some other valuable capabilities may include the ability to generate OLAP cubes, data vault, documentation, and source control for team-based development. Moreover, features like data profiling and pushdown optimization can also add tremendous value to your business. 

4. Accessibility and Speed 

Accessibility and speed are also crucial factors when deciding between different data warehouse solutions. The faster a data warehouse can load and export data, the quicker the users can draw critical insights to make timely business decisions to improve the bottom line. 

As such, a data warehouse solution with parallel processing ELT/ELT capabilities and high processing power will allow you to load millions of records to your data warehouse, so you can perform analysis and generate statistical reports quicker.  

Accessibility to accurate, updated information is necessary to stay competitive. Having a solution that offers maximum availability and uptime ensures that your analysts can provide timely information for critical decision-making. 

5. Scalability

Scalability is among the data warehouse considerations that can play a significant role in determining the financial feasibility and viability of your investment, as well as your ability to continue as a data-driven company. 

You must look for data warehouse solutions that can meet your analytic needs in years to come, so you don’t have to reinvest every time your business grows. For that, cloud data warehouse solutions are your best bet.

Cloud data warehouse services have massive parallel processing (MPP) systems, which means you can scale up when computing demands are high and vice versa.

We may see typical data volume shifting from terabytes to petabytes in upcoming years, so it is essential to keep scalability a primary factor in your data warehouse considerations.

How a Data Warehouse Can Add Value to Your Organization

The whole idea of employing data warehousing is making valuable insights available to business users. There are plenty of data warehouse use cases that can add value to your business, such as:

• Understanding consumer behavior by analyzing large volumes of customer data
• Performing market research using information available in different large databases
• Analyzing sales patterns to obtain a better understanding of customers across product groups

Regardless of the industry, every company can take advantage of data warehousing solutions for in-depth analysis and reporting. 

For instance, a financial institution can consolidate reporting and improve access to data for better decision-making. Similarly, a hospital can analyze health care data to enhance the quality of care and increase operational efficiencies.

It is essential that you do your research before choosing an enterprise data warehouse solution for your organization.

Cloud vs. On-Premises Data Warehouse

When looking for the best data warehouse solution available in the market, you will come across an important question: Should you opt for an on-prem or cloud-based data warehouse solution? Both approaches have pros and cons and suit different use cases. 

On-prem solutions sit on your local network. You can control every aspect of the repository, but it requires extensive investment to buy all the hardware, as well as a team of IT professionals to manage the system. 

On the other hand, cloud data warehouse solutions are entirely online and do not need any physical infrastructure. Cloud solutions are easier to deploy, easily scalable, and less costly than their on-prem counterparts. 

Examples of popular cloud-based data warehouse solutions are Microsoft Azure SQL Data warehouse, AWS Redshift, Snowflake, and Google BigQuery.

On-prem data warehouses offer greater control, alleviate concerns over network latency, and make Data Governance easier to achieve. Organizations with strict data security policies in place might prefer an on-prem infrastructure. 

But cloud warehouse solutions provide better flexibility, scalability, and security. It ensures quick deployment and access to business intelligence, resulting in faster time to market. 

Why You Should Consider Building a Data Warehouse Using a DWA Tool

There are many data warehouse tools available in the market, but you must look for an automated solution that will provide you the flexibility to customize data as per your specific use cases. 

Rather than opting for a manual approach and building a data warehouse in-house, you should consider using a data warehouse automation (DWA) tool. It will help you set up your data warehouse much quicker.

It can help achieve faster time-to-value to support your analytics initiatives. Also, it can be a cost-effective option, saving you real and opportunity costs in the long run.