10 Questions to Help Define a Successful Data Warehouse Strategy

When defining your data warehouse strategy—or moving from on-premise to cloud—you’ve got lots of options. But your data warehouse is only as good as the strategy you use to put it in place. Bottom line: You simply can’t tackle today’s data management challenges—including big data analytics—without a clear plan.

When looking at your choices, take a minute to ask yourself these 10 questions.

Ask Yourself This . . .

1. Can the DW handle diverse data sources with structured, semi-structured, and unstructured data?

It’s no big surprise that we’re facing exponential growth in unstructured data (email, video, audio, multimedia, etc.) and that 93% of the digital universe will be unstructured by 2022. Smart data warehouses need to be able to easily gather and analyze all types of data, from diverse data sources. And they need to not only collect and convert that data, but turn it into valuable insights that can enable business decisions.

2. Can it easily manage massive—and rapidly increasing—data volumes?

This is an incredibly important question—especially when you consider that the world’s data is doubling every two years, with 50-fold growth from 2010 to 2020. Look for a data warehouse that can not only handle the velocity of data growth but also do this without compromising speed, usability, cost, and performance.

3. Can you gather data from any source? Does it deliver out-of-the-box integrations?

Ideally, you want a data warehouse that lets you quickly and easily consolidate the data from your databases, cloud services, and applications into a single data management platform—without the hassle of coding. Look for a platform that includes out-of-the-box integrations with the leading data source applications (think Salesforce, Google Analytics, Hubspot, and more). 

4. Will it streamline data management?

One of the biggest challenges of running a data warehouse in any fast-paced environment is to continuously manage capacity and performance as schemas and workloads rapidly evolve. With a data warehouse solution that automates manual tasks like vacuuming, your IT staff can save a lot of time that was previously spent on maintenance and trial-and-error tuning.

5. How does it automate data collection, scaling, and modeling?

Look for a data warehouse solution that provides automated end-to-end data management—from initial data collection to analysis and reporting. The data warehouse should be able to automatically scale to support any increase in data, workload, and concurrent users and applications without the need for data movement, data marts, or data copies. 

6. Will it let us go from raw data to insights quickly

It makes sense to ask for real-world examples—or better yet a demo or free trial—to see how the data warehouse can take your raw data and convert it into actionable insights. Dashboards and visualization tools are crucial here, so make sure to actually see what you’ll be able to do with them.

7. Will it support advanced analytics, such as machine learning and natural language processing (NLP)?

Being able to accurately analyze increasing amounts of unstructured data is one of the significant benefits of tools like machine learning and NLP. If your data warehouse can't keep up with those next-level tools and you're ready to invest in them, it's a bad fit.

8. Does it make sense to use cloud services or should we stay on-premise or hybrid?

A cost-effective data warehouse should be able to scale compute capacity to match demand, and then quickly and easily scale back when usage decreases. The cloud can help solve this problem, but only if the underlying architecture of the warehouse supports it. Most businesses today are gradually moving to the cloud, and for good reason.

9. If we’re not ready to go all in, can we have usage-based pricing to pay as we grow?

Yes. Many cloud data warehouse solutions offer flexible pricing to meet your precise usage needs. Ask about specific plans. Usage-based pricing  means that you aren't overpaying for upfront costs or data that sits idle.

10.With a cloud data warehouse, when does the payoff come? Where is the ROI?

Work with your data warehouse vendor to do a simple calculation of the cost savings you can achieve through better use of IT resources and cloud vs. on-premise storage.

When you’re ready to define your data warehouse strategy, talk with us. Panoply is a cloud data warehouse built for analytics professionals by analytics professionals. 

Get a free consultation with a data architect to see how to build a data warehouse in minutes.
Request Demo
Read more in:
Share this post:

Work smarter, better, and faster with monthly tips and how-tos.