In one way or another, all organizations must analyze the role that big data can play in their operations and the potential benefits they can obtain from the process.
Volume Velocity Variety Veracity refers to the truthfulness of the data. Volume, velocity and variety help ensure that companies have a lot of raw information, but if it is out of date or inaccurate, it can hinder rather than support intelligent decision-making.
The benefits of Big Data
Properly handled big data can support company growth in countless ways, including those listed here.
Better 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 provide it, gathering and analyzing information about customers' habits and preferences. These efforts pay off in higher loyalty rates 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 companies reduce efforts and money wasted on promotions that miss the mark and add little value and ROI.
Targeted products and services. If properly processed and analyzed, big data can provide clues about which products and services customers are most likely to purchase. This information can drive innovation that will propel companies to the next level of success, regardless of what their unique goals and objectives are based on.
Greater efficiency. Big data can be useful not only for external 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 these insights to increase productivity and reduce expenses.
The following video presents additional benefits of big data.
What are the barriers to Big Data analysis?
As this field continues to grow, companies continue to encounter problems with big data . Here are some of those challenges. In the next section we will discuss how they can be resolved.
The needle in the haystack phenomenon. Without proper processing, data is like a haystack and actionable insights are like a needle you are trying to find there. In fact, your data collection may be so large that you may 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 pillars of quality data. Unfortunately, data can be out of date or inaccurate, leading to worse decisions rather than better ones.
Silos. Data collection is not always a coordinated effort within a company. This can happen separately in each department, placing data in silos when it might be more useful to have some or all of it together. For example, a company may want to understand how marketing and customer service 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. However, many companies do not prioritize customer security or privacy, potentially resulting in data breaches, loss of reputation and business, and regulatory issues.
Lack of experience. The shortage of IT specialists 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 face today's Big Data challenges
Companies that want to make the most of big data must face 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 key ways to do this 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 together disparate data collections, choose the right platform to use for data management, strive for data quality and accuracy, ensure security and privacy, and train data engineers if necessary. Depending on where a company begins these efforts, implementation can be a multi-month or even multi-year process. Given that the role of data is only growing, these steps will ultimately be 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. Companies must carefully consider what makes sense for their operations. But, in one way or another, all organizations must analyze the role that big data can play in their operations and the potential benefits they can obtain from the process.
