The Keys to Big Data are to Start Small, Think Big, and Grow Fast

If you do any reading on the benefits of big data, you probably want it all and you want it now. Better protection against fraud, lower operational costs, richer business intelligence, a finely tuned customer profile and the ability to predict future customer behaviors and market trends — where to sign up? But the thing that most often takes a company from big data adoption to big data disillusionment in 2.5 seconds, it’s the sheer complexity of such an initiative. Big data is easy to underestimate in terms of magnitude, work, knowledge, and security.

But just because you aren’t ready for a full-blown big data undertaking today doesn’t mean you can’t at all. The ideal way is to begin small, think big, and grow toward becoming a truly data-driven organization. Here’s how.

Focus on the Availability of Your Data

Although many of the tools you need to begin a big data program are free and open-source, a big data initiative can rack up serious charges rather quickly. Starting small helps you keep control of those costs until you begin reaping a return on the investment.

The availability of your data is tied directly to your ability to report on it. What insights can you glean right now that will deliver immediate and meaningful ROI? Start here; with a small and manageable initiative. Then gradually scale your big data analytics into other facets of your business. For example, perhaps you need to improve your marketing operations, or maybe you could use a better tool for detecting fraud. Develop a big data initiative to do just this one thing. Choose your tools carefully and partner with vendors wisely. When you’re able to generate useful reports on your data, it’s time to scale up and take on a new project with big data.

Focus on the Performance of Your Big Data Tools & Services

As you identify and accept small challenges with data analytics, you need to use this easy entrance to familiarize yourself with the tools and services available. For example, would it be better to house your data in a cloud-based data warehouse or data lake instead of investing in the massive IT infrastructure needed to store big data in-house? Often, a cloud data storage service can keep your data more secure than you can. Determine if Hadoop is right for your needs (hint: the answer is probably yes), and whether you’ll try to use MapReduce (which requires strong Java programming skills), or an alternative like Spark, Hive, or Pig. It’s much easier to begin working with these complex and sometimes confusing tools with a small project. Then you’ll have an idea how everything works when you’re ready to take on something bigger.

Focus on the Security of Your Data

In many cases, a cloud service can provide a higher level of security for your data than you can. Consider a cloud-based data warehouse or data lake instead of the expensive and high-maintenance infrastructure you need for a big data initiative in-house.

One of the most frequently underestimated aspects of owning and using big data is security. Whether you are working with data on consumers, healthcare, finance, or most any other industry, it is valuable to someone. There’s actually a pretty price on the black market for many types of data. Even if you are in compliance with all the regulations, that doesn’t mean your data is truly secure How will you provide adequate security? You’ll need to answer this question to everyone’s satisfaction before you move your small data operation into a big one.

Ready to learn how to start small, think big, and grow fast with big data? Then Big Data Week is perfect for you. See the full conference schedule here.