Maximize business efficiency with these cloud data warehouse best practices

Just how important is data within the context of the modern enterprise? According to one recent study, the big data analytics market is expected to reach a massive $103 billion in value by as soon as 2023. Not only that, but in 2020 alone, every person on the planet generated about 1.7 megabytes of new data every second all day, every day. If you needed a few statistics to underline just how important this concept is, let it be those.

For businesses of all shapes, sizes and in every industry, data is the key to their competitive advantage. It helps them understand their customers in a meaningful way that builds trust and loyalty. It gives them insight into what products and services they need to be bringing to the market. It allows them to capitalize on opportunities quickly in an ever-changing marketplace. The list goes on and on.

That is largely where a cloud-based data warehouse enters into the conversation. A data warehouse is a chance to collect all of this insight and intelligence in a single place, making it easier to process. Being based in the cloud also means that this information is available anywhere, at any time and on virtually any device. When putting together one of your own, however, there are a number of best practices that you’ll want to follow.

Building a better data warehouse: An overview

One of the most important best practices to follow when building a cloud-based data warehouse involves coming to an understanding of why you need one in the first placeAs is true with the application of any new technology in an enterprise environment, decisions can’t be made in a vacuum. That is to say, you shouldn’t invest in something for the sake of it – you should invest because it will help you accomplish some type of strategic goal.

Are you trying to standardize your data, meaning that you want to make it all easier for business leaders to analyze and interpret? Are you trying to break down the types of data silos that commonly exist, making it easier for different departments (or even various locations) to communicate and collaborate with one another? All of these are critical questions that you need to answer before the process begins, all so that you can have a strategic measure of success to head towards during your initiative.

Along the same lines, you have to get comfortable with the fact that building a data warehouse to serve your organization will require an iterative approach – meaning that it isn’t something that you can just pay for and expect to go into effect overnight. As the old saying goes, “Rome wasn’t built in a day.” It can take months – or, depending on the size of your organization, even years – to build a proper data warehouse. Therefore, an agile approach to the proceedings is typically recommended.

This means that instead of building one massive solution that goes into effect all at once, you’re building things in smaller chunks that all come together to form something more powerful over time. This is also important because over time, your business will continue to grow and evolve – meaning that your business objectives and priorities are likely to change given the conditions of the marketplace. Taking a more agile approach to what you’re doing goes a long way towards supporting precisely that, making sure that you don’t have to suddenly start all over again as things shift.

Finally, you’ll want to make sure that you understand as much about your data as possible in a few different ways. You need to know A) what your most valuable data is in terms of what you’re trying to accomplish, and B) where that information is currently stored. That will make it easier, not to mention more efficient, to move everything over to a cloud-based platform.

How to do more with Lytics

This will all give you valuable insight into how often you’ll actually need to load that data to derive the most value from it. Keep in mind that organizations are creating massive volumes of information on a daily basis – to the point where it can quickly become overwhelming to understand and interpret it at all. With the cloud, real-time data processing is absolutely possible – but you still need to separate what is important from what isn’t (along with what is structured from what isn’t) to derive the maximum impact.

At Lytics, we offer a customer data platform that allows businesses to leverage machine learning, artificial intelligence and similar technologies for all of their data-based needs. Not only does this improve one’s ability to process and interpret that data, but it also lets them make progress in terms of improving things like data governance and security as well.

To find out more information about how to maximize business efficiency with the use of a cloud-based data warehouse, or to speak to someone about your own needs in a bit more detail, please don’t hesitate to contact us today.