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Betting on the Cloud to Manage Massive Volumes of Data

Written by Vincent Lam, Head of Cloud Product Marketing at Talend

When you're in a competitive industry, it's imperative to have timely access to enterprise data to make informed decisions. To deliver on experience, companies need to manage massive volumes of data, and access and serve it with very low latency.  The increasing amount of data in a wide variety of environments must be processed and analyzed efficiently; in addition, there is an enterprise necessity to be able to change cloud providers and servers as easily as possible.

However, it's not easy to keep with growing business needs using legacy infrastructure-let alone scale as needed. You don't want your data management tools to hold you back from your digital transformation goals. Plus, with the greater number of people wanting access to data, having tools that are easy to use becomes very important to providing access to all the lines of business who want and need data for their analytics operations.

That's where a cloud-based architecture comes in. More than often, an organization will end up with a multi-cloud infrastructure in which different IT components and services are delivered by different cloud providers. One of the biggest benefits this provides is flexibility. The most appropriate resources can be sourced and deployed in such a way that they precisely match the organization's particular requirements. As a result, it will find itself much more able to deal with changes in demand, scaling IT capacity up and down as needed.

This type of strategy can also assist an organization to shift some applications and data stores to an external service provider while retaining core systems within its existing data center. Termed a hybrid-cloud approach, this can help to reduce operational costs as well as the need for large capital investments as requirements grow. Choosing a multi-cloud or hybrid-cloud strategy can also serve as a precursor to the adoption of a cloud-only strategy. Applications and data can be gradually migrated over time, rather than requiring a "big bang" approach that could be seen as too risky.

Let's take Paddy Power Betfair (PPB) for example. It's the world's largest publicly quoted sports betting and gaming company with five million customers worldwide. Sports betting and e-gaming companies operate in a fast-paced, highly competitive and regulated market. They're open 24/7/365 and are constantly striving to provide customers with the best online sports betting experience or risk seeing those customers go to a competitor.

When Paddy Power and Betfair merged in 2016, it created an additional data challenge for an already highly data-driven organization. The merged company had to bring together 70TB of data, from dozens of sources, into an integrated platform. To solve this, they adopted a cloud strategy leveraging big data technologies and scalable cloud-based services to deal with the huge spikes in usage on days with popular sporting events. In the end, PPB cut data delivery times in half.

This is just one example where moving to the cloud has its benefits. In this case, PPB was able to get a 360-degree customer view, drive customer engagement and optimize the betting experience only after migrating to the cloud. During this process, PPB was able to come away with valuable takeaways:

Watch out for dirty data

It is important to gain a quick understanding of just what you are dealing with-to get a sense of how "dirty" the data is, whether date formats are invalid, data requiring preprocessing to remove punctuation, to capitalize, etc.

If you're sitting on a trove of data that is not qualified, governed, or trusted, then you're working with unusable bits and bytes. You can't possibly scale any kind of enterprise data strategy if you don't have quality data at the start-but qualifying data can be a time-consuming process. In fact, current industry stats indicate organizations report spending more than 60 percent of their time qualifying or preparing data, leaving little time for actual analysis.

Require near real-time access to very large data sets

Agility is important especially in a world where minutes and hours can have an impact on your bottom line. Real-time streaming data and analytics is rapidly becoming the lifeblood of today's data-driven economy. Why? Because customers live in an age of information immediacy. To meet this challenge, businesses must leverage real-time information to understand customer needs and deliver them.

Building a strategic, scalable cloud-based architecture is achievable. A multi-cloud strategy can deliver significant business benefits as long as thorough planning and evaluation are completed prior to adoption. By carefully considering all factors, an organization can enjoy the benefits offered by the strategy while keeping challenges and risks to a minimum.

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About the Author

Vincent Lam is Head of Cloud Product Marketing at Talend. Throughout his career, he has held leadership roles in marketing, product management, and product development involving innovative technology solutions to complex problems. Mr. Lam is author of several patents and his background includes innovation across technology firms, Wall St, and entrepreneurship.

Published Tuesday, December 11, 2018 8:01 AM by David Marshall
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