Any business leader that isn’t living under a rock knows about Big Data. I’d say most of them are terribly interested in learning how to make Big Data work for them, whether it is to increase their customer base, make improvements in their business, or anything else. However, many are still unaware of basic concepts like data streams and how smart data management builds competitive advantages. We are here today to tackle that.

No matter how smart you are, you can’t use Big Data without understanding it first. And the first thing you need to understand about it is that data is constantly being created. Practically every action in the digital world produces some form of data that is stored somewhere in a database (which also translates into privacy concerns, but that falls off-topic for this article).

The real challenge is to extract this data and make it work for what you want to achieve.

What You Need to Know as a Business Leader

The role of a business leader has evolved quite a bit in the past few years, and one of its new areas of focus is data itself. As a business leader, it’s on you to be on top of whatever data the company is collecting and how it is being used. Your goal, obviously, should be to make the most out of it.

But here’s the catch: Big Data is tremendously disorganized. Imagine the largest mess of jumbled pieces of information you can and put it in tons of different places. That’s Big Data. And that’s exactly why being good at extracting quality data and using properly is so crucial to building a competitive advantage in your industry. These are the top 3 things you need to know about Big Data as a business leader.

1. Know What Type of Data You Are Collecting

Whatever data you can get your hands on is most likely raw. That means that you will need to process and analyze it before reaping any sort of benefits from it. Your first step in embracing Big Data in your company should be to know and understand what type of data your company is able to collect. In general terms, there are three main types of Big Data: structured, unstructured, and semi-structured.

Structured data is all data that can be processed, stored, and retrieved in a fixed format. Often, a simple search engine algorithm is enough to access and retrieve relevant information from a structured dataset. An example? The list of all the people who work at your company and their personal information (names, positions, time in the company, etc).

Unstructured data describes all data that lacks any form of structure. This is the type of data that requires the most time and work to analyze, and it is also the most common around the world. Sometimes, you can also have semi-structured data that merges both of the types above. If you wanna learn more, this article should get you on your way.

2. Extract and Refine Big Data Extraction

Once you know what type of data you’re collecting, it’s time to make sense of it. Your internal IT department or an outsourced Big Data team should be able to lead this part of the process. They would be responsible for analyzing and organizing all of the gathered datasets via Big Data extraction methods and, once that’s done, that’s where you come in.

Your role as a business leader is to determine which datasets bring the most value to the company. You need to think about your client demographics, where your sales are coming from, and which data-driven decisions have been most impactful so far. Using some of the most popular databases should help you out with this process. Your actions at this point will determine how the extraction of Big Data evolves in future iterations.

3. Generate Value and Monetize Big Data

This is the part most business leaders are interested in. Once you understand what type of data you are collecting and you have refined the extraction process, you’ll be in a great position to start generating tangible value and monetizing Big Data. However, this is a very creative process and you’ll probably need some extra minds on the topic.

I’d recommend setting up meetings at least twice a month to revise all of the interpreted data and determine the best uses for it. Not all data is useful (in fact, a very large part isn’t), but when you can pinpoint that piece of information that is actually critical for an upcoming decision, the return over investment is insane. Your job at this stage is to turn spreadsheets into valuable insights that lead to action.

Wrapping Up

All in all, we must remember that Big Data is nothing more than a tool. The only way it can yield results is if you analyze and use it properly. Whatever output comes of it will depend on how well your business can implement the interpreted data into the respective processes or operations.

And don’t forget that, to take it the extra mile, you must make the interpreted data accessible and easy to understand for your employees. That way, they will also be able to integrate it into their tasks and, hopefully, innovate on their own.

So be aware of what data you are collecting, be mindful of the efficiency of the process you are using to make it work, and be creative to monetize it. That’s a straight path to success.