7 Common Myths about Big Data Debunked

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Whether you are in business, government, healthcare or any other industry, you must have heard of the name big data. Wondering if it means something for your business? Do you need it? Can you afford it and so on? If used correctly, big data has the ability to change your business. However, if you don’t have the right knowledge about it, it can do more harm than good. 

Big data and its hype got me thinking of the time when my friend Jade was super crazy about Optimum online plans. He forced me to switch too because it’s cheaper. It was the best decision I made. Many myths have been developed around the concept of Big Data. Let’s begin debunking some of the common ones:

1: Big Data is Everywhere 

Big data and its services have become the center of attention in a variety of industries. However, only 73 percent of the organizations are planning to invest in it. They have yet to figure out how to adopt big data.

Only 13 percent of the organizations have actually deployed their big data solutions. So, big data is not everywhere. Only its talks are everywhere. The biggest challenge organizations have to face is how to use big data with the right strategy.

2: It’s All about the Size 

The size of the big data is characterized by volume, veracity, velocity, and value. Yes, it is one of the major features of big data to handle the massive amount of data. However, its prime characteristic is volume. 

Big data also comes in diverse formats. The technology is beyond the size of data. Speed and diversity are among its key characteristics. If other features of big data are not considered, simple solutions will become complicated and in the long run, you will encounter cost and storage issues. 

3: Machine Learning and Big Data Are Related 

Machine learning deals with big data but ML uses data to model the underlying process for better utilization. Machine learning is based on the ML algorithms that analyze data sets and then apply whatever it has learned for making meaningful decisions. Big data and machine learning together can offer valuable insights.  

4: No Data Warehouse is Required to Place Big Data 

A data warehouse is an architecture and big data is technology. Therefore, data warehouses cannot replace big data and vice versa. 

Big data is responsible for storing and managing scale which is later on used on various big data solutions. A data warehouse organizes data and provides a single version of data. It consolidates data from different sources and places in one single location; making it easier to read. Using data lineage, you can identify the data’s origin. 

Big data analysis is independent of an existing data warehouse. It does so without interfering with the existing data warehouse. Both technologies have their own set of needs and utility. 

5: Big Data is Only for Those Who are in IT 

The first industry to use computers decades ago was the IT industry itself. When PCs got a little cheaper and accessible, they were found in every other organization. Now, they are being used on a daily basis. 

The same principle applies to big data. However, if data is kept locked in the IT department only, other departments will miss out on its benefits. Anyone can become more competent at their job if they have access to the right data. Your business is likely to succeed if it starts using data and analytics.

6: It Can Predict the Future

Big data does not tell anything with certainty. Anyone who is trying to predict the future is simply selling something.

Big data can offer predictions based on the previous data patterns but not with 100 percent accuracy.  Real-time data analysis tells what is going to happen right now. However, these predictions are based on probability. There is always room for error. The more data you have and the more relevant it is, the higher the chances of an accurate forecast. 

7: It Demands a Big Budget 

Multinational organizations, government agencies, and other large corporations are investing a significant amount of money in big data centers and machinery. They are also hiring data scientists who are certainly not cheap.

The usage of big data is slowly becoming universal. Therefore, chances are it will become cheap. A time will come when small businesses will find it affordable just like I found Optimum prices affordable.  An increasing number of tools and services are becoming available to help businesses make the most of data. If you haven’t thought out a data strategy yet, your competitors might already be already working on it. 

Final Words

If you don’t make yourself aware of the big data technology and unlearn the myths, you might end up taking wrong business decisions

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