Big data has firmly established its key role in modern business operations. At this point in time, simply questioning its far-reaching necessity is putting you behind the curve.

2018 has certainly been an interesting year in regards to how we perceive big data – both in the business world and our everyday lives. As it appears, the market for big data will continue to grow at exponential rates in the foreseeable future.


For entrepreneurs looking to launch a new business in 2019, understanding the finer details and benefits of big data is not just advantageous knowledge, it’s a requirement for survival.

As 2018 starts to come to a close, there are a handful of takeaways and insights that need to be carried over into 2019 and beyond. Here are three major truths that new startup owners need to understand about big data.

1. Most (If Not All) Future Employees Will Need Big Data Skills

At this point in time, big data has infiltrated nearly every facet of business operations. While it has long played a momentous role in areas like supply chain management and logistics, big data has been an increasingly large factor in revolutionizing processes related to customer service, recruiting, and user experience. Plain and simple, big data is not just for analytical teams these days.

Regardless of what startup business ideas you are entertaining for the upcoming year, if you plan on expanding, it will be essential that the people you bring onboard have (at the very least) a basic understanding of big data.

Keep in mind, being “data-literate” goes beyond software, tools, or programming languages. Most importantly, it’s about having a holistic view of which datasets are important, as well as the ability to read between the lines to get actionable insights. Moreover, employees will need to be able to communicate these big data insights in a way that benefits the big picture. In other words, having people who can effectively visualize data results will be extremely important to growing startups.

For example, in customer service, AI-powered chatbots are becoming incredibly popular – a trend that will likely continue in the coming years. These machines need to be thought of as a constant working progress, in the sense that the big data generated from customer interactions should serve as the basis for refinement. That being said, the person you bring onboard to manage customer service will need to understand how conversational datasets can be used to improve how the chatbot answers queries. This would likely involve pinpointing patterns around factors like intent, location, issue, fulfillment, etc.


Now, not ALL future employees will need to be bona fide data scientists. However, a simple understanding of how big data can be used to find business solutions will be a crucial capability of new employees moving forward.

2. Cybercrime Will Continue to Rise

Cybercrime has been a growing problem over the past few years. The rise of ransomware and data breaches across the world needs to be a concern for ALL businesses these days. To give you an idea, Microsoft estimates that the average cost of a data breach to a company is around $3.8 million!

As you likely saw on the news, Facebook’s recent data breach has thrust this harsh reality further into the spotlight. As a startup, data security needs to be one of your primary investments. Even though you are likely working on a shoestring budget, going the cheap route here can ruin your startup before it even gets going.

Now, there’s no denying that it can be confusing to know where to begin when looking into data security. The best place to start is examining your possible risk exposure.

  • What data will you be collecting?
  • How big is your inventory?
  • What is your projected revenue?
  • About how much will the average transaction be?
  • Where are the customer touchpoints?

In most cases, there is a limit to how much money can be lost. Furthermore, there is typically a limit on how much money you can lose based on what you do with customer data and how you monetize it. When you are determining your investment in data security, you need to have an understanding of these figures.

While you certainly don’t want to comprise the quality of your data security, in the startup stage, you want to avoid security measures that will bog you down. Start by choosing a reputable third party to run your server/infrastructure. By the time you are ready to do this on your own, you will ideally be in a position to hire a security specialist. Other things you need to do as a startup include:

  • Purchasing a cost-effective anti-malware program for work computer(s).
  • Using two-factor authentication for sensitive information.
  • Getting an SSL certificate for your website.

It never hurts to talk to a security consultant before you get your business up and running. They will be able to assess your current situation and give you guidance on what exactly you need. Unfortunately, the threat of data breaches appears to be getting worse. Not taking the proper measures is a fatal mistake.

3. “Humanizing” Data Will Be an Essential Process

Unless your background is in data science, you are likely going into your startup with only a basic understanding of how big data works. That said, a Business Intelligence (BI) system that is able to “humanize” the datasets relevant to your business goals will be a crucial piece of the startup puzzle.

Now, humanizing data is about creating intuitive visualizations that can be easily understood and interacted with. In other words, it’s all about getting to the “why” and establishing context.

In the current state of BI, many companies are using Natural Language Processing (NLP) programs to help make sense of their data. The underlying goal is to leverage the context within analytical reports and eliminate ambiguities behind user intent. For example, let’s say you need to know the median income for Burbank in California. Once the BI software gives you this figure, you could ask, “what about Laguna Beach?” without needing to reformulate the entire context of the query.

Over time, machine learning gives NLP systems the ability to gain a deeper knowledge of a company’s data and the types of answers needed. This opens up areas of the information pipeline where the everyday users are not limited by their knowledge of data science. While this advanced concept of BI might seem like a luxury for startups, it is critical for breaking down barriers of analytics adoption – especially while resources are tight.

The Wrap

There’s no denying that starting a business these days is intimidating. As many entrepreneurs do not have an in-depth knowledge of big data, developing a checklist will require a great deal of research.

The universal truth these days is that big data will continue to influence business operations as time goes on. If used properly, knowledge and understanding in this area can do wonders to improve efficiency, reduce risks, and boost your chances of long-term survival.