Every company around the globe these days has some data to store. Because we have so much more data than we used to, and much of that data is digital, companies look for solutions to storing, sorting and processing it all.
One solution many companies are turning to is using open-source software as part of their data storage solutions.
Linux, in particular, has developed a family of open-data licenses known as CDLA licenses.
Imagine a world where automakers can share safety information. Roads and cars could both be safer, and consumers would be able to make a more informed choice on which vehicle to purchase. Within that framework, cars could sense and transmit information as well, creating an artificial-intelligence scenario that would make cars safer and safer over the years.
Cons to Open-Sourcing Big Data
Even though companies will save money on the cost of the software, big data does require some specialized computer power . These tools can be expensive, and storing the info offsite on the cloud can run up costs of data storage. Because it is tempting to store every little bit of information, these costs can increase exponentially over time.
Your employees may require more training to know how to best use the frequently updated information and apply it to practices already in place.
Because the software is open-source, others will have free access to the same software, including hackers. They can use the information to figure out ways to hack into your data, particularly if you have security vulnerabilities on your network.
You might spend months learning the software and training your employees, only to discover the developers have moved on to another project. Open-source developers tend to donate much of their time to a project, which means they may not be as invested as a company that creates a paid version.
You also won’t have guaranteed support. While the open-source community is known for helping out people who have questions, they are not obligated to help you.
Pros to Open-Sourcing Big Data
One of the biggest benefits of using open-source software for big data is the software is free and easy for others to improve and adapt to their own needs.
Open-source allows companies to store vast amounts of data without the cost of private software for this purpose. For example, a furniture company might draw on information from sensors embedded in the furniture, and gather input from tests and reviews consumers post on various social media sites.
In the past, organizing all this data would have been a monumental task, but open-source software makes it easy to sort, search and categorize.
Big data can predict the probability of an outcome by looking at all the information available and coming to some conclusions.
Before, we mentioned hackers might be able to crack security vulnerabilities, but at the same time, open-source software is often pretty secure because the community works out these bugs and shares them with everyone. If the software has a vulnerability, you can be almost certain developers will release an update fix quickly.
Open-sourcing big data has both advantages and disadvantages. Companies should weigh the pros and cons carefully, figure out the costs of open-source versus private software and choose the best solution for their situation.