Every organization in the modern world relies on data to inform decisions, support operations, feed automation, innovate, and scale. Every year, the amount of data we collect and store grows exponentially. When managed appropriately, you can translate this data into insights that fuel business intelligence and create the type of knowledge that can generate sustainable success.
But, if you’re not equipped, the sheer volume of data coming into your organization can also create complications. And that’s where the intersection of big data and knowledge management comes in.
We’re sharing a refresher on these two key elements and diving into how they can work together to help your business meet and exceed its goals.
What Is Big Data?
Like most buzzwords, the term “big data” is a nebulous idea with several different definitions that leave people confused and a bit overwhelmed. But, at its core, big data refers to giant data sets that are too large for traditional software tools to capture, manage, and process, and thus require special technologies and expertise.
And big data is only getting bigger. By the end of 2025, experts predict we’ll reach 181 zettabytes of data created, captured, copied, and consumed worldwide, according to data from Statista. (That’s up from a mere two zettabytes in 2010.)
If you’re not impressed, remember that just one zettabyte is 1,000,000,000,000,000,000,000 bytes (or the equivalent of about five quadrillion Word documents).
It’s hard to wrap your mind around the mammoth amount of data in the world, but we’re getting better at learning to manage, store, and use it.
Organizations are leveraging data warehousing, or the process of collecting data from different streams into a central repository where it can be analyzed and used in reporting. The resulting “big data analytics” helps us identify trends and patterns within a company or entire marketplace. Big data is why emerging tech like artificial intelligence (AI) has evolved from a sci-fi dream to a legitimate field with practical business applications.
Big Data Applications and Benefits
Think of big data like one of those massive 3,000-piece puzzles. When you dump the contents of the box, you have a mess of tiny cardboard shapes. It’s chaos. But after you’ve done all the work necessary to complete the puzzle, you’re left with a clear picture. The science of big data and big data analytics is essentially taking all of the countless bytes of data and organizing them into something valuable and usable. The resulting actionable insights become the knowledge you and your workforce use to improve business performance and automate key operations.
Take Amazon, for example. The e-commerce giant changes its prices millions of times each day based on factors like competitors’ prices, users’ shopping patterns, and whether a product is rare or common. Because Amazon can collect, manage, translate, and analyze massive data sets in real time, the organization can make sure it’s charging the best possible rate for each item.
Or consider Netflix, which compiles data from its more than 200 million users to tailor suggestions based on each viewer’s habits and behaviors. Thanks to the organization’s ability to not only collect but also analyze its inconceivably large data sets, Netflix can identify what’s most likely to hook each user and serve the right content at the right time.
In addition to dynamic pricing and targeting, companies can use big data to solve all sorts of unique challenges, including:
- Informing product development
- Forecasting revenue
- Anticipating customer demand
- Creating more personalized marketing campaigns
- Setting ambitious but attainable organizational goals
Of course, it all comes down to having the right technology to collect and manage your data and share new insights across the organization.
What is Knowledge Management?
There are three types of knowledge within an organization:
- Explicit: Information that’s easy to record, store, articulate, and share, such as research reports, documented policies, and product information.
- Implicit: The practical application of explicit knowledge. For example, understanding how to operate a software application thanks to a “how-to” document.
- Tacit: Information gained from personal experience. For example, identifying when a prospect is ready for a sales pitch.
Knowledge management (KM) is the process of collecting, sharing, and managing information, as well as ensuring your workforce can access all three types of knowledge. In most cases, this means leveraging a knowledge management system (KMS)—a platform that allows you to store and organize information so employees and teams can learn, collaborate, and become better aligned. Knowledge management works best when the tech you use is centralized and accessible from anywhere.
A powerful KMS is essential to creating an efficient and agile organization where employees feel empowered to work autonomously and consistently deliver top-quality service. When everyone has instant access to all the information they need via a user-friendly, searchable platform, they perform better and make smarter decisions.
Knowledge management also facilitates skill-building and faster onboarding while breaking down departmental silos. Additionally, it fosters collaboration regardless of whether your workforce is remote, in-office, or hybrid, making it especially useful for our rapidly evolving work styles.
How Do Big Data and Knowledge Management Work Together?
Knowledge management and big data are linked in that big data is the raw material that must be refined into something that can be analyzed and translated into actionable insights, and knowledge management is the process for collecting and publishing those insights—and, of course, making them actionable. Think of it this way: big data is a collection of ingredients, and the insights you glean are like the cakes and cookies you make from those ingredients. A knowledge management system is like a 24-hour pastry shop where your workforce can choose the insight “treats” they want whenever they want them.
And like the customers at a bakery, your workforce doesn’t need to know each individual ingredient (or even the process for turning those ingredients into something useful) so long as they can access the finished product.By adopting the right knowledge management strategy and KM platform, you can ensure all the data you’ve been amassing and processing will be put to good use.