Businesses are generating massive amounts of data from a wide variety of sources. Some call data “the new oil” because it’s so valuable. But a giant collection of data merely sitting on a server is useless. To fulfill its potential, it must be processed, organized, managed, and analyzed in useful ways and presented in formats that business leaders can understand. The need for the ability to perform these processes is the crux of today’s big data challenges.
Below we explore more about common challenges in managing data that companies across industries struggle with, as well as how to address them. But first we’ll describe how big data is currently defined, discuss more about the benefits of big data, and examine some of the barriers to taking advantage of those benefits.
The Four Wheels of Big Data
What is meant by big data has changed over the years. Currently, it is defined by four characteristics, also known as the “four Vs” or “four wheels”: volume, velocity, variety, and veracity.
- Volume refers to the amount of data, which is no surprise given its descriptor, “big.” Experts estimate that trillions of gigabytes of data are generated each day.
- Velocity refers to the high speed with which data is generated, shared, and processed. Velocity continues to increase along with the capabilities of electronic infrastructure, such as the internet and 5G.
- Variety refers to the considerable number of sources from which data is derived. It includes companies, individuals, platforms, and more.
- Veracity refers to the truthfulness of data. Volume, velocity, and variety help to ensure companies have plenty of raw information, but if it’s outdated or inaccurate, it can hinder rather than support smart decision-making.
The Benefits of Big Data
Big data properly handled can support company growth in innumerable ways, including those listed here.
Improved customer experience. Today’s consumers expect a high degree of personalization and convenience, also known as a positive customer experience (CX). Companies can use big data to deliver it by gathering and analyzing information about customers’ habits and preferences. Such efforts pay off in higher rates of loyalty and new customers through referrals.
More effective promotional campaigns. Much of the same information that helps companies anticipate and meet customer needs can be used to create highly targeted — and therefore more effective — promotional campaigns. In this way, big data helps businesses reduce wasted efforts and money on promotions that miss the mark and deliver little value and ROI.
Targeted products and services. Properly processed and analyzed, big data can provide clues as to what products and services customers will be most likely to purchase. Such information can drive innovation that will propel companies to the next level of success, whatever that may be based on their unique targets and goals.
Increased efficiency. Big data can be useful not just for outward-facing customer concerns, but also for internal improvements. Companies can collect information about how machines and people are operating and analyze it to find inefficiencies. They can use those insights to increase productivity and reduce expenses.
The following video presents additional benefits of big data.
What Are the Barriers to Big Data Analytics?
As this field continues to grow, companies continue to find issues with big data. Here are a few of those challenges. In the next section we discuss how they can be resolved.
The needle in a haystack phenomenon. Without proper processing, data is like a haystack, and actionable insights are like a needle you are trying to find there. Your data collection might be so big, in fact, that you might not know exactly how much there is, where to start looking, or even what to do to make it digestible.
Inaccuracy. As we mentioned, veracity is one of the cornerstones of quality data. Unfortunately, data may be outdated or inaccurate, leading to worse decisions rather than better ones.
Silos. Data collection is not always a coordinated effort within a company. It can happen separately in each department, putting data into silos when it could be more useful to have some or all of it together. For example, a company might want to understand how marketing and customer care affect sales. But these departments may have separate data repositories that don’t necessarily connect.
Lack of security. With great power comes great responsibility, and with the power of data comes the responsibility to protect it. Yet, many companies don’t prioritize security or customer privacy, potentially resulting in data breaches, loss of reputation and business, and regulatory issues.
Lack of expertise. The shortage of IT experts is well known, and data engineers are part of this group. Companies are struggling to find talented professionals to fill this highly specialized role.
How to Meet Today’s Big Data Challenges
Businesses that want to make the most of big data must address the barriers mentioned in the previous section, as well as others, such as lack of storage, unfamiliar tools, low data quality, and high data management costs. One of the primary ways to do so is to initiate a big data governance strategy and implementation plan. Hiring a chief data officer (CDO) is becoming increasingly common as companies recognize the importance of this role.
With a program in place, some of the next steps are to bring disparate data collections together, choose the right platform to use for data management, pursue data quality and accuracy, ensure security and privacy, and train data engineers if necessary. Depending on where a company starts in these efforts, implementation could be a multi-month or even multi-year process. Given that the role of data is only growing, these steps will eventually become well worth the effort.
Big Data and Big Decisions
Big data risks and challenges will always be present when companies start to work more intensively with this technology. Businesses must carefully consider what makes sense for their operations. But, in one way or another, all organizations should look at the role big data can play in their operations and the potential benefits they can realize from the process.
