Unlocking Business Value with a Modern Data Strategy

Computing as we know it has changed: major advancements in processing, networking, and storage have opened the door to a whole new set of possibilities for how to leverage data. Whether it’s self-driving cars, automated financial planning, legal help, factory automation, medical diagnoses, or any number of other applications, data and advanced analytics are working their way into virtually every corner of our personal and professional lives.

A common thread woven through all of these use cases is big data. Yes, the term “big data” is already a cliché, but it’s also reality. But big data is about more than just acquiring data and the technology needed to store, process, and analyze it. To take advantage of all your data and drive meaningful impact for key business use cases, you need to make the most of your data by devising a modern data strategy. It’s a strategy inclusive of all the people, process, and technology changes you need to consider when transforming your business to become a data-first organization.

So how do you get there? Let’s walk through three key steps in the journey to a modern data strategy.

Step 1: Think about your business first.

IT teams don’t just embark on technology projects for the sake of it; there’s always a purpose behind it. With that thought in mind, the first and perhaps most important step in the journey to a modern data strategy is to identify the key business impact that will be realized from the end result. Commit yourself to solving any business problem.

There are hundreds of use cases to which big data can be applied, so oftentimes it’s difficult to pinpoint just one. Fortunately most, if not all, businesses have a finite set of concerns, so identifying the business priority isn’t as difficult as it might seem at the outset. Talk to your business leaders and listen to what they are saying about the goals of the company—therein you’ll find the right area to focus on.

Here are three ways that a modern data strategy can help solve business problems:

Drive customer insights.As markets evolve, the business that wins is likely to be the one that uses data most effectively to understand customer behaviors and build long-lasting relationships that lead to a generous revenue stream. By building a “segment of one” view, you can understand both past and future customer behaviors, constantly staying one step in front of their next action.

Improve product and services efficiency. Many enterprises are using data to improve their current offerings and develop entirely new products or services. For example, some companies are selling customers’ comparative data on their own use of your products, or selling completely new services based on combining live, historic, and public data in novel ways. The possibilities are limitless.

Lower business risks. Perhaps one of the most powerful byproducts that comes from analyzing huge amounts of data is the ability to spot trends and anomalies that were previously invisible. That capability can be directly applied to problems like defending your network against cyber-attacks, understanding the behavior of your customers more deeply, and improving the efficiency of your supply chains.

Step 2: Modernize your architecture.

Most companies still rely on systems that were conceived several decades ago, systems that are deeply entrenched, or systems that are highly reliable but hard to scale economically—or to scale in a way that can cope with the modern world of data. Enter Apache Hadoop.

Hadoop has emerged as the de facto solution for managing the challenges associated with the 3V’s of big data—volume, velocity, and variety. Hadoop’s distributed processing and storage nature makes it cost effective and technically feasible to store, process, and analyze as much data as you choose. It’s one of the essential keys to a modern data strategy.

Beyond the data dynamics of the 3V’s, architecture modernization enables a completely new way to think about analytics. Today we can not only look backwards to see what happened, but also understand why what we see happened in the first place. And now machine learning allows us to take analytics one step further: predict or actually cause outcomes to occur. All of this is powered by an enterprise data hub that allows you to handle any data (at rest or in motion), anywhere (on premises and in the cloud), and scale analytics and data science to the masses. You might call this the 3A’s of big data—anything, anywhere, and anyone.

Step 3: Put together the right team to move forward.

Implementing a modern data strategy with Hadoop is not a trivial undertaking. The technical issues are complex, and there is no such thing as a one-size-fits-all solution. That’s why you need to be sure you put together the right team from the outset. Partner with people who can provide training aligned to your goals, expert services to help you get started, and enterprise-class support to keep your environment up and running.

Here’s the bottom line: A modern data strategy unlocks your data potential so you can solve your most demanding business problems. So start your journey today. Put your organization on the path to better business outcomes.

Clarke Patterson is the senior director of product marketing at Cloudera.

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