Five Key Questions You Should Ask About Your Data Strategy and the Cloud

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Click to learn more about author Mathias Golombek.

Using the cloud in the right way for your data strategy can help you realize the value of your data faster, easier, and more cost effectively – especially when combined with a high-performance, cloud-first analytics database. So, what are the questions you should ask when considering the cloud?

1. How does the cloud influence data analytics and data strategy?

While a cloud solution can change your business’ infrastructure, it isn’t the only option. And who can predict what platform will be best suited to get the most from the next generation of game-changing technology?

Your data strategy might change at some point with applications better suited to run on-premise. So always choose flexible technologies that can work with different cloud solutions – and always keep your own data center in mind. 

2. What’s the best cloud strategy for the enterprise?

The cloud is currently best for scalable applications, data lapse, and creating an extension of your own data centers.

But most of our customers adopt a hybrid cloud strategy – getting the best out of each deployment option for their specific needs. For example, some use a public cloud but still find that the operational analytics layer of their high-end enterprise data warehouse (DWH) is more secure and performs better with on-premise solutions.

3. How do you get maximum value out of your data?

It’s important that standard DWH techniques work efficiently with the data you use. You can increase the potential of this power with today’s data science, artificial intelligence (AI), and algorithms.

And better still, if you have the technology to apply statistical models directly using data science you can really get the best out of your data.

4. Why are speed and performance so important?

Speed and performance are key to helping organizations become truly data-driven. They enable you to create insights in near real-time. This allows your business to react in an instant. Instead of sending a query, and then having to wait ages for a response, you can interact with the data then and there.

Users can apply analytics databases to transform how they work with data. Being able to scale up and let dozens or even hundreds of users access data at the same time democratizes the usage of data analytics and optimizes business processes.

5. Is cloud analytics cheaper than on-premises?

Cloud services often look affordable on paper, but a heavy load of high-performance data analytics can make them very expensive. So, keep an eye on the pricing model – no data-driven company should be penalized for applying data analytics.

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