3 and one more V’s of Big Data
We can’t name Big Data the newest technology because it exists for more than ten years already but still a lot of people can’t define what is it and how it works. So, let’s get acquainted with this great tool.
Firstly, we need to define this term. When you think about Big Data you might imagine some huge amounts of data somewhere on the Internet. Well, you are almost right. Big Data works with huge amounts of data but this is not the only one feature. Simply put, Big Data is a set of tools that can process really huge data sets, make predictions and define patterns for further training of neural networks, work with Artificial Intelligence and Machine Learning. Big Data can include a lot of services, you can read about them here: https://itsvit.com/services/big-data/.
There are three mysterious V’s of Big Data. These V’s define Big Data and allow us to distinguish it from other technologies.
What does every Big Data V mean?
The first feature of Big Data is of course Volume. Big Data appeared as a technology for huge amounts of data. It needs to collect and process this data. Such volumes actually need a lot of computing capacity. Big Data can be stored for some time and then processed or processed in real-time and this approach is more popular.
Such necessity leads to the next V – Velocity. You might need to process a lot of data per second to recognize fingerprints, for example. If the system processes data slowly, the result can become irrelevant by the end of processing. Thus, velocity is quite an important feature of Big Data.
The third V is Variety. Big Data input can include different information for creating patterns and predictions. The system receives some set of information, Big Data scientist combines it and makes patterns for further usage, analyze and processing. Thus, the system can be trained what input it has and what output it needs to give.
Big Data scientists and Big Data analytics have very important roles in this process. You can train the system appropriately or overtrain it and receive the incorrect result. Thus, collecting an experienced team also is very important but this is a theme for another article.
Let’s get back to V’s. Often you might face information about only three V but there is one more of them – Value. It is the fourth V and it’s very important for a business.
Big Data implementation is quite an expensive process, so you need to estimate costs and future efficiency in advance. Big Data can make great things but sometimes it will be unprofitable and it is important to analyze pluses and minuses before you start the implementation. All these are about the Value.
Benefits and examples of Big Data
If you understand the value of your Big Data implementation you’ll definitely have the cost-efficiency as a result. There are a lot of examples how Big Data saves money for companies. The most popular example is the restaurant chain. Some restaurant combines the food supplies with the Big Data and makes the next thing. A trained neural network uses data about the weather forecast, region, etc. and makes predictions about today’s number of guests. If the staff understands that they have a lot of spare food today, they can redirect some food to another restaurant or make a discount. This approach allows saving a lot of money every day.
In this example, you might see one more benefit of Big Data – the processing speed. The system makes predictions every morning or even at night. So, it analyzes a lot of different data very fast. As a result, Big Data will bring you great competitiveness on the market in your domain.
How to implement Big Data?
Let’s imagine that you decide to implement Big Data into your company. You have a lot of different data, you calculate the value and understand future profit. What’s next?
You need to hire a Big Data team. It includes different specialists like Big Data scientists, analytics and others. You might hire them one by one in-house or find a dedicated team. The second way is more efficient because such a team is ready to work with the project at once. They have a lot of ready solutions, know best practices and can implement them in your project. The in-house team is also a good decision but it is quite longer and more expensive. When you need to invest in Big Data implementation, saving some money on hiring the team is quite a rational idea.
How to find a dedicated team?
This said a dedicated team is the most efficient way of Big Data implementation. Dedicated teams usually work with the Managed Service Provides (MSP), so you need to find such a company. There are a lot of ratings and feedback on the Internet, so you’ll easily find a trustworthy contractor.
Also, you might have some interviews with key specialists of the team to be sure you understand each other and can work together. Wrapping up, if you want to implement Big Data, look for a reliable MSP.