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4 July 2023 - 7 minutes

Myths and Misconceptions About Big Data

Are you sure you know what big data is? Let’s debunk some common myths.

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You’ve heard about big data; after all, it would be nearly impossible to not know what it is today! Big data is all the rage, propelling progress forward and allowing us to reach unforeseen progress in the field of technology. But what exactly is big data? What does it do? Is all that we’ve heard really true? We’ll tackle these topics and much more in this post. 

What is Big Data?

Let’s explain big data: on a very high level, big data refers to the tools and technologies developed to manage large quantities of data. Made up of structured, semistructured, and unstructured data, big data is used in machine learning and data analytics projects to process, interpret, and draw conclusions from these large amounts of data. There’s no specific quantity of data that big data demands; instead, any sort of data that simply cannot be processed by humans is grouped into this category. 

The three different types of big data are: 

  • Unstructured data: this type of data is not ordered or categorized, therefore making it harder to interpret by machine models. Examples include video and audio files, dates, and satellite imagery. 

  • Structured data: this data is pre ordered and structured, facilitating the sorting process. Because it's already organized, drawing conclusions from the data and interpreting results is much easier. Examples include transactions and financial records.

  • Semistructured data: semistructured data is just what it sounds like--it’s not completely unorganized like unstructured data, but still lacks the clear parameters of structured data. Examples include streaming data and web server logs. 

Examples of big data

Curious about how big data manifests in the real world? Check out some of these examples of big data in six major sectors: 

  • Marketing: major companies like Amazon receive astronomical amounts of data every single minute and through innovative data storing and processing, they can see what clients are searching for and suggest similar objects, or sell the same product again, delivering an ultra-personalized customer experience

  • Healthcare: long gone are the days of sifting through case studies to find similar symptoms or treatments; doctors and medical professionals can now use big data to access previous patient records in just moments, allowing them to quickly and efficiently find a solution. 

  • Transportation: has your phone ever suddenly changed your route, alerting you of traffic or a car accident ahead? Using massive amounts of real-time data stored on databases, big data can help you get to your location as quickly as possible.

  • Government: even at a local level, elected officials have tons of constituents and things to keep in mind; with big data databases that are dedicated uniquely to organizing and making sense of local finances and crisis information, government officials are better able to understand the entire picture. 

  • Cybersecurity: big data has advanced to a point where we can program the system to detect peculiarities; this is very helpful for detecting possible cyberattacks and unusual behavior. 

  • Business: companies have a wide variety of things to keep track of: operations, people and HR, financials, and sales are just a few. So when big data can step in and organize that data and bring conclusions to leadership, it greatly lightens the workload and allows leaders to make data-driven decisions.

Why is big data important? 

You know that making data-driven decisions is an absolute necessity when it comes to business. As companies receive more and more data from even more sources, being able to actually put that data into practice and make better decisions from it can mean improved productivity, higher revenue, better customer services, and overall better company performance. 

Here’s an example: big data can track and store client experiences on their website, looking at how long they spend on a certain page, the products they search for and buy, and what promotional tools are bringing customers to their site. But for big and small companies alike, manually processing this data in real-time is impossible; there’s simply too much. With big data, however, companies can receive updated and accurate assessments, which can help them guide their future decisions. 

The five V’s of big data 

Big data boasts five advantages, frequently referred to as the five v’s: volume, variety, velocity, value, and veracity: 

  • Volume: big data can handle just that--lots of data, much more than your typical device or computer, making it extremely valuable. 

  • Variety: big data is capable of receiving and organizing a wide range of types of data, even if the sources are quite varied. 

  • Velocity: big data has to be able to quickly and effectively receive, store, and process real-time data.

  • Value: these large quantities of data have to be valuable for companies, meaning it must be properly evaluated and stored.

  • Veracity: authenticating the value of the data and its reliability is a crucial part of depending so heavily on big data. 

Now that you’re clear on what big data is, how it’s important, and what it brings to the table, let’s explore some of the biggest myths and misconceptions surrounding it. 

Myths and Misconceptions About Big Data

You’ve probably heard a lot about big data and it can be hard to sift between what’s real or fake. Well, we’re here to clear up a few of them:

Big data is too big

Lots of people doubt that big data can actually handle the amount of data it receives! And while we get that concern, remember that tools and techniques have been developed alongside big data to automate the processing steps and experts have devoted their entire careers to understanding big data. If you’re still not convinced, try speaking to an expert so that they can show you how artificial intelligence and other tools help decipher this data effectively. 

Big data is too expensive for small companies

False! Big data solutions, such as the cloud, are actually quite cost-effective, especially when you compare the cost of having and maintaining giant storage installations. Options on the cloud are also entirely customizable, meaning you can decide exactly how much space you need and even test out different options. No matter the size of your company, there are cost-effective solutions for the cloud. 

Big data is, well, big

Here’s a tricky one. We tend to think of big data as a large and overwhelmingly massive quantity of data, right? But actually, big data is made up of lots of little data points, such as an individual transaction or online search. These little data points come together to form big data, which then works to make sense of and find correlation between these points. 

Big data will replace humans

We just know you’ve heard this one! And while big data is capable of storing and processing much more information than humans are capable of, no machine will ever (or at least in the relatively near future!) be able to imitate human decision-making, intelligence, and emotions. The combination of big data working to order and sort the data and then humans using their knowledge and creativity is ideal. 

Big data will always make the best decisions 

Just like with any tool in tech, big data can make mistakes; it also lacks the human decision-making capabilities that take various factors, such as environmental and emotional ones, into account. Big data is not flawless, but together with human intelligence, we can harness the power of both parties. 

Big data is just for tech companies 

Wrong again! Although it’s typically referred to when talking about tech and data itself, all companies, regardless of sector or size, can benefit from big data to sort through their sales or financial data, to name just a few areas, and make improved, overall business decisions. 

Big data can predict the future 

We wish this were true, but it’s not! Just like in any area, the outcome of any proposed solution will depend on hundreds of factors and even if you use predictive models to make your best estimate of what can help, erratic human behavior or force majeure could mean that the prediction is totally off. Conclusions drawn with the help of big data should be carefully reviewed with discretion before setting anything into motion. 

Big data has taken over!

While lots of companies and media outlets are constantly referring to big data and its usage is on the rise, it’s not widely adopted--yet. It’s a relatively new technology and one that requires lots of knowledge; as companies learn more and more about big data and how to harness it for their specific use, we’ll see an increase in use. But for now, the majority of companies are in the first stages of implementing the tool. 

Did we help bust any myths or misconceptions surrounding data?! We hope so! When used correctly, big data can be a powerful tool that can help your company reach new heights. If you’re ready to join the party and become a big data expert, what are you waiting for?! Check out Ironhack’s bootcamps today.

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