Five Challenges of Big Data

Using data to make business value is now a reality in many IT and NON-IT industries. With the introduction of the “Internet of things,” enhanced analytics and developed connectivity through new technology and application bring significant prospects for industries. For an example, at Siemens, Big Data is changing the way maintenance services are provided, from the reactive approach to predictive and precautionary maintenance.

However, we find some companies facing problems in leveraging the value of that data. First of all, companies have a problem in finding the right data and concluding how to make the best use of that data. Creating data-related business cases generally mean thinking something unique and finding for revenue models that are usually different from the traditional business.

Second, companies are finding it difficult to acquire the right talent capable of both working on new technologies and of understanding the data to provide meaningful business insights.

Third, access data and connectivity can be a problem. Most of the data points are not yet well connected today, and companies usually do not have the adequate platforms to collect and manage the data across the enterprise.

Fourth, in the data world technology landscape is developing extremely fast. Usage of data on a large scale means working with a robust and innovative technology partner that can assist in creating the right IT architecture.

Finally, the most important challenge for Big Data is maintaining data security at any cost.

If we can manage these Big Data challenges then Big Data would proof one of the most beneficial things that the IOT (Internet of Things) has provided us.