Big Data is a very efficient technology set for data processing. Nowadays we produce really a lot of information every moment. For example, such a simple device as your smartwatch can collect data about your heart rate, a number of steps, walking speed, location, etc. All this information can be processed because of Big Data services. That’s why your smartwatch or fitness band can make recommendations for physical form based on your data and data of other users.
Using of Big Data
The example with smartwatches is one of the simplest despite the complexity of the technology itself. Big Data is widely used in very different areas. For example, the healthcare uses Big Data for the diagnosis. There are a lot of cancer tumors that the human eye can’t distinguish in pictures but taught neural networks can do it. This is the way how technology can save lives.
Drone cars also use Big Data for collecting and analyzing the road, creating routes, and making decisions when to stop, turn and do other actions.
Even restaurants can use Big Data for making supply predictions. The neural network can analyze how weather, day of the week, and other parameters influence the number of visitors. After that restaurants can make bigger or smaller supplies for each day.
Thus, almost any are can use Big Data for work optimization and increasing cost-efficiency.
How understand that you need Big Data implementation?
Big Data has three main characteristics: volume (you need to process a lot of information), variety (you need to process a different type of information, for example, images and text at the same time) and velocity (you need to process data fast). Thus, if your project has such characteristics, you might use Big Data.
You should pay attention to one more point – value. Big Data implementation is quite expensive. You will need to pay for the technologies and also to the specialists who will work with the project. Thus, you need to understand the future profit, current expenses, and make a conclusion about efficiency.
Two ways of Big Data implementation
You can implement Big Data in two common ways – to hire an in-house team or to hire an outsourcing team. If you choose the in-house team prepare to invest a lot of resources. You’ll need to invest in the HR and recruitment department for hiring the whole team. Hiring one by one is a long process, so you can’t start the project immediately. Also, you might need to spend time for adaptation and to equip new workplaces or even change the office fo a bigger one.
The outsourcing team is more beneficial. You will hire the whole team at once. Usually, this is an experienced cohesive team that doesn’t need time for adaptation. They can start to implement Big Data immediately. And you will not have the problem with farewell after the project ends. With an in-house team, this point is more complicated. You might need to pay salaries to a team on the bench or find a new project or fire the team.
Conclusion: how to implement Big Data with minimum risks and expenses?
Wrapping up, we can say that Big Data service provider is the most efficient way to implement Big Data. Managed Service Provider (MSP) is a company with strong and experienced specialists. You can hire a dedicated team from MSP and start projects fast and efficiently.
The dedicated team can make analysis before implementation and create the strategy and plan of the project. Thus, you’ll understand all the steps of implementation and will have the ability to add details. Big Data service provides will save your costs and make a successful project.