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.