10 Questions to Help Define a Successful Data Warehouse Strategy

Moving your business from disparate data sources and ad hoc reporting to a single source of truth data warehouse solution is a sign of growth in the right direction.

However, data warehousing requirements differ from one company to the next, and service providers often assume users already fully understand the industry. Therefore, it’s crucial to have a data warehouse strategy that clearly outlines your requirements and expectations before you begin researching solutions. 

So, how do you get started?

We’ve curated a list of questions in this post to help you define a successful data warehouse strategy.

1. Will we see ROI with a cloud data warehouse?

Depending on initial costs — which vary from one vendor to the next — your returns could trickle in as soon as data flows into the data warehouse for storage and processing. Then, with the right data in place, you can focus on making smart business decisions that drive revenue and reduce costs.

Find out more about where your money goes in our detailed overview of cloud data warehouse costs and returns.

TL;DR: Using data warehouse technologies will push your business toward new levels of profit.

...when you use a modern data warehouse, you spend less on overhead and more on uncovering insights hidden in your business data—insights that can make the difference between failure and success.

2. Can we adopt a pay-as-you-scale price model?


No two companies approach data warehousing with exactly the same workloads (and objectives).

Data warehouse providers know this, which is why they often set pricing based on your requirements and consumption. As you scale, keep in mind how high data volumes and processing will cost you.

The same is true of data warehouse management.

Data warehouse providers typically offer tiered pricing models whose costs vary based on your usage and size. But you wouldn’t have this flexibility if you decided to hire technical talent to manage your data warehousing in the cloud.

For this, you'd have fixed costs as you'd pay engineers on a recurring basis.

3. Should we use a cloud or on-prem data warehouse solution?

In the past, on-premises infrastructure and other overhead costs made data warehousing prohibitively expensive. But thanks to data warehouse as a service (DWaaS) providers, infrastructure, setup, and maintenance costs are now much more affordable.

Whether you opt for a cloud or on-prem data warehouse solution, you’ll get the same level of memory redundancy and security.

That being said, there are pros and cons to each option.

For example, a cloud solution generally offers quicker and more cost-effective scaling.

But an on-prem solution comes with complete governance and the ability to choose your tech stack. Plus, depending on where your on-prem infrastructure is located, you could avoid network latency issues.

When defining your data warehouse strategy, you’ll have to decide what’s most important to you and whether a cloud or on-prem solution will best serve your needs.

But remember that you’re not required to pick one or the other. A hybrid solution like our parent company SQream gives you the best of both worlds.

4. What does data warehousing offer beyond storage?

Databases and data warehouses are different.

If data warehousing were solely a storage solution, your on-prem infrastructure would be a close contender. But data warehouses facilitate complex ETL analytics and calculations, and the reports created from complex queries within a data warehouse are used to make business decisions.

Here are just a few of the benefits you can reap from data warehousing:

  • Data pattern (trends) recognition from copious amounts of data
  • Correlation recognition for better decision-making
  • More varied analysis of your data than single departments and specialists can provide
  • A single source of truth derived from your business’s structured and unstructured data
All these (and more) are immediately available when you implement a data warehouse strategy. Check out our Data Warehouse Guide for more details about the two.

5. Can a data warehouse solution automate scaling and data input processes?

The best data warehouse solutions scale automatically.

Automatic scaling is essential both when there's a temporary spike in workload and storage capacity requirements and when your data expands organically.

But beyond automatic scaling, you want to look for a data warehousing partner that automates data input, processing, and the presentation of analysis results.

Effectively, this becomes a managed data warehouse solution, cutting many expenses.

6. Who’s responsible for your data warehouse strategy?

Who's responsible for your data warehouse strategy will depend on what type of solution you choose.

If you opt for a self-hosted data warehouse strategy, you'll need a team of IT managers, data specialists and engineers, and data analysts.

Each of these roles plays a critical part in managing your data warehouse.

  • Your managers from various IT disciplines are the experts who set up the infrastructure from the outset and maintain it during warehousing. Think of these teams as managers of the physical components of your data warehouse.
  • Your data specialists and engineers should have skills and knowledge that correspond with the data warehouse platform you implement. For example, if you decide to use Google's data warehousing services, your engineers should be GCP certified. The same goes for Redshift, Azure, AWS, and other vendors.
  • Last, your data analysts translate your ETL requirements into actual processes on your data.

Having these teams isn't a prerequisite when you go with a managed data warehouse solution. Instead, the automation and regular housekeeping happening behind the scenes achieve the same (if not better) results as having a full-fledged team on the ground.

7. How many data sources can we integrate with our data warehouse solution?

Data warehouse solutions often have a long list of data integration options. These include mainstream databases and custom information storage solutions. 

The exact number of sources you can integrate will depend on your solution. But, typically, these are some data sources you can integrate into a data warehouse solution:

  • Websites and social media pages
  • ERPs and accounting packages
  • Relational databases (PostgreSQL, MySQL, etc.)
  • Unstructured databases (NoSQL, MongoDB, etc.)
  • Document data lists (CSV, Google Sheets, etc.)

Using APIs and one-off authorization, you can create data bridges that offer high performance yet require very little maintenance.

Basically, if it has an API, it can push data to your warehouse.

8. We don't have a central database; can we still get started with warehousing?

Yes—data warehousing is a perfect way to collect information from all your data sources into a central location. A data warehouse allows you to pull all your company’s data to a single source of truth, regardless of where the data comes from and its format.

Once inside your data warehouse, your data will be in predictable shapes and have well-understood properties. This makes analyzing that data or integrating other data sources much easier going forward.

9. How do we onboard a data warehouse solution?

Onboarding is key to maximizing your use of a data warehouse solution.

Most data warehouse providers offer product tutorials and documentation. With these, you can start using the services you want at your own pace.

That said, you can also schedule demos and custom onboarding experiences.

10. Do we need an official data warehouse strategy document?

Not really.

No doubt, documenting your data warehouse implementation is a must. And answering the questions we’ve outlined here is a good start in defining your strategy.

But a more important step toward success is to speak with data warehousing experts on how best to implement your data warehouse strategy.

A personalized conversation and demonstration of Panoply with real data is a better way to approach building out your company’s data warehouse.

Take your first steps with data warehousing

In this post, we've covered what you can expect from a data warehouse solution, whether you should go with on-prem or cloud data warehousing, and how to get started with a data warehouse strategy and solution.

If you run a trial of a data warehouse solution, you’ll start seeing benefits as soon as you finish importing data.

In answering the questions above, you should have a clearer idea of what you need in a data warehouse solution. But, understandably, you may have a few more questions as you develop your data warehouse strategy.

For these, reach out and speak with the pros at Panoply. With our experience serving companies from diverse markets, we can help you take your first steps with data warehousing.

Get a free consultation with a data architect to see how to build a data warehouse in minutes.
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