How to Use Big Data Like Big Corporations Do - Tips and Examples

Big Data refers to all the information collected in the digital realm. As the name tells you, this collection of data is enormous and very diverse. Every day, we generate a vast amount of data, just by doing things like opening an email, logging in to one of our accounts, liking some posts, opening a link, or reading an article. All of this is collected by companies that use the information to tell them more about you, as a consumer. 

Big Data is established by 5 Vs: volume, velocity, variety, veracity, and value. This basically means that the volume is huge, it is accumulated at an extremely fast rate, in all kinds of varieties, it is highly reliable and trustworthy, and it has an immense value that gives precious insights for companies. 

So let’s see what you can use Big Data for like big companies do in the real world. We’ll look at examples of implementations and some examples of how you can take advantage of such big information masses. 

How to Do Big Data Analytics

First, we have to talk about the methodology of how you can use the data before we go into the details of what you can use it for. An article by Tableau explains the details of how Big Data analytics works: 

1. The first step is obviously collecting the data. This is a tricky concept in that it can look different for every business. It really depends on what you would like to extract from the information given to you by your users. It can be structured and stored in data warehouses, or it can be unstructured, which is more complex and varied. 
2. The second step is processing the data. This is also very diverse in methodology, depending on what you need the information for. You can even use AI for data processing and organizing. 
3. The third step is cleaning the data. You must eliminate any duplications or irrelevant pieces of information, and format your data correctly for analysis. 
4. And finally, there is data analysis. This is where you transform the data into valuable insights. Different types of analysis involve data mining, predictive analytics, and deep learning. 

And now that we know the hows, we can look at the purposes of what you can use Big Data for. Let’s look at some examples. 

Understanding Your Customers and Meeting Their Needs 

Big Data allows you to have as much information about your consumers as humanly possible. You can see such important facts as when they purchase, why they purchase, how they purchase, what they spend most of their time with in connection with your business, or when they stop buying or using your product. There is so much you can look out for just by analyzing this data that it becomes increasingly susceptible to getting to know your customers. 

For example, a study by Cambridge University and Microsoft Research reported that just by analyzing what people like on Facebook, they can predict such personal data as satisfaction with life, intelligence, emotional stability, age, gender, race, and so much more. Just from looking at Facebook likes of users. 

If you have the right collection of data at your hand, you can get to know more about consumers and their behavioral patterns than ever before, leading you to be able to conduct marketing and sales strategies that meet their needs perfectly. 

Identifying Trends with Big Data 

Once you have information about what your customers do, you can identify different patterns and trends that tend to re-occur during the customer journey. 

You can investigate such data as social media platform content, customer reviews, browser history, and login patterns, the possibilities are endless in behavioral data. It’s a great way for, for example, retailers to customize their offerings based on these trends. It can help with such factors as: 

• Managing the prices of your products or services
• Managing the supply
• Or looking at the competitors' offerings. 

Once you identify the trends, you will be equipped with the knowledge of when, what, and why your customers make purchases, which will then lead you to create strategies to accommodate these needs and behaviors. 

Big Data for Advertising and Marketing

This is probably the most interesting part of using Big Data in your business. Imagine being able to target your audience with the right product at the right time at all times. Offer them specifically what they need, even if they haven’t expressed exactly that they need it. 

For example, Facebook is one of the most professional organizations that use highly targeted advertising, making it a big competitor of even Google. They use Artificial Intelligence and deep neural networks to make sure every user gets a personalized experience when faced with advertisements. These are based on the users’s behaviors and every one of their activities, while also tracking cookies. 

Another example is Netflix, which traces such data from watchers as the date and time you watch the content, when you pause, rewind, or fast forward in the videos, where you watch, how you browse, and what you search for. All of these are used to make personalized recommendations on what you might want to watch and create an experience for you that fits your expectations the best. 

Cybersecurity Using Big Data

While having a massive amount of data places you as a potential victim of cyber attacks, it can also be a great advantage in avoiding such issues if you use the information at your hand in the right way. 

With analysis and even AI, you can create a system that counteracts cyberattacks and keeps your business safe from fraudulent activities. You have to look at historical data to learn from what might have caused the issues and implement such alerting analytics that will instantly tell you if something is wrong. 

When there are unusual patterns in the behavior of customers, or atypical patterns you see in the workings, it can signal you that you need to take countermeasures against fraudsters. 

An article by Sangfor lists such insights to look out for in cybersecurity as: 

• Network traffic monitoring
• Analyzing data to detect anomalies
• Malware pattern identification to detect threats more effectively
• Behavioral analysis
• AI analysis
• Web page filtering 
• Immediate incident response.

Conclusion

The vast, fast, and varied nature of Big Data offers insights into consumer behavior, market trends, and operational efficiency, and allows companies to make data-driven decisions that are precise, predictive, and proactive. 

This means they can effectively collect, process, and analyze Big Data, anticipate the needs and preferences of their customers, and protect themselves against cyber threats.