The term “big data” is used commonly now, whether in business or other industries.
But if you’re not a techno-geek, how are you supposed to understand big data? What exactly is big data? How is it used, what’s it good for, and what does the future hold?
Here we’ll look at everything you need to know about big data, in our big data beginner’s guide.
What Is Big Data?
Let’s start with a definition.
While the term “big data” tends to be thrown around to explain any kind of information, the definition of big data is really about extremely large datasets, usually too large to process or store on a traditional computer or with regular systems and tools.
But big data is also about the process of handling the reams of information.n other words, it is the technology that collects information, organizes it, and analyzes it to provide relevancy. Using big data is about finding patterns and other valuable insights in datasets.
So the “big” in a dataset may vary depending on the organization, and it may change over time.
But it’s more than size.
It’s also about the speed at which the analysis is done by the system looking at the datasets. And, it’s about gathering data from disparate sources and bringing it together.
In fact, Gartner defined big data using three Vs: volume, velocity, and variety. A large volume of data may be gathered from many sources; data is often processed with great velocity, even in real-time, to provide the most valuable analysis; and, the data can come from a wide range of sources, even in a variety of formats.
Recently, two more Vs have been added – veracity and value. Is the data consistent and complete, or can its veracity be trusted? And just because it’s classified as big data, does its analysis bring value to an organization?
The key point to remember is that big data refers to a significantly large volume of information and the processes used to analyze and store it.
Where Does Big Data Come From?
The rise in the volume of data has followed the digital transformation of our society. As we’ve moved into a digital age, our use of technology has risen rapidly. And, the volume of data that is available because of our digital lifestyle has also risen.
Think of the data created by an individual. You generate data every time you go online and do a search on your computer; every time you shop online or even browse a shopping platform; every time you use your GPS on your smartphone; every time you interact with a social media platform; the list goes on.
Every digital transaction leaves a digital footprint, and the organizations with which you interact collect and analyze that data.
Here are some other examples where data is collected in massive amounts:
- Huge retail chains like Walmart and Costco store customer transactions.
- Social media sites like Facebook and Twitter store and access user data.
- Amazon analyzes customer data to provide product recommendations.
- Spam filters go through millions of emails every day.
- Mobile phones generate information through calls, texts and browsing, as well as GPS data.
- Satellite technology stores and collects thousands of images every day.
How Can Big Data Provide Benefits?
So a lot of information is gathered all over the world every day. So what?
The analysis of that information is where the benefits can be gained. The whole point of storing, processing, and analyzing data is to make predictions and guide decisions.
Let’s look at some of the ways big data can be used beneficially:
In the agriculture sector, big data can support increased and improved production. Crops are planted and tested against a variety of environmental conditions. That information is stored and used in making decisions about crop timing, crop rotation, and maximizing yields, as well as tracking fertilizer usage and more. This can reap big benefits particularly in feeding hungry areas of the world.
Cities can use the information gathered from traffic sensors to improve traffic flow and plan for road improvements. As cities become increasingly populated, planning for the movement of people will become more important. In a similar fashion, law enforcement can use data analysis to determine areas that need increased policing, for instance, or to prepare for major events.
Healthcare records can be analyzed to look for patterns of disease, helping with early detection, development of medicine, and even prevention efforts.
The retail sector sees huge benefits from big data. Amazon tracking customer transactions is one example of how retail can increase its sales by providing tailored advertising with customer recommendations. Retail outlets can also monitor customer transactions to determine what products to bring into which stores.
What Are the Challenges of Big Data?
Storying and analyzing all that information doesn’t come without challenges.
Here are some of them:
Security: Obviously, the storage and use of data, some of it personal, comes with security concerns. Organizations must ensure the data is protected by encryption, and that only those authorized to use it have access to it. That means putting in place safeguards such as user authentication, restricted access, and more.
Storage: The more data an organization collects and stores, the greater the need for secure storage of the information.
Quality: Mentioned earlier as one of the Vs of big data, there can be challenges to ensuring the veracity of data and knowing that it’s complete.
Competence: Because big data is new and emerging, there is a lack of talent in the workplace. There’s a need for more people choosing careers in the field of big data, including data scientists, analysts, and developers. Having enough knowledge in the domain is a challenge for many organizations.
The ever-growing world of big data is an exciting new frontier. The possibilities that come from collecting and analyzing data are just beginning to be uncovered.
As we learn more about big data and use it more, those possibilities, despite some challenges, will continue to grow.