Big data is about more than big volumes of data. It also refers to the fact that the data is arriving at an extremely fast pace, and from multiple sources and formats. These massive datasets can be used to address business problems and gain insights that you might not have imagined possible. We can help your organization pinpoint the solution that best capitalizes on your big data streams to gain insights that help you make better decisions, boost sales, and increase customer satisfaction.

Cloud computing is a collection of information technologies that provides general access to shared pools of system resources that can be accessed with minimal efforts, often through the Internet. Cloud computing is based on sharing resources to achieve consistency and economy. Third-party clouds allow organizations to focus on their core business rather than waste resources on computer infrastructure and maintenance. Also, allow IT-professionals quickly adjust resources to meet rapidly changing demand.

E-commerce refers to commercial transactions conducted electronically. Recently, the number of such transactions has increased significantly. E-commerce includes both physical and digital goods and services, often divided into business for the consumer (B2C) and business to business (B2B).

Financial technologies (FinTech) - new technologies and innovations due to competition and replacement traditional methods of financial services. FinTech doesn’t only change the financial services sector, but financial operations and risk management.

The Internet of Things (IoT) is a network of physical devices embedded in an Internet connection and sensors that allow them to collect data and communicate over the Internet. They are equipped with certain technologies to interact with each other without human intervention in order to optimize the use of resources.

Machine learning is a subset of artificial intelligence that’s centered around a machine’s ability to learn from data. Through supervised or unsupervised learning algorithms and neural network models, machines can learn autonomously from sets of data in order to make predictions or explore patterns and draw conclusions from these patterns. In the era of big data, machine learning represents a massive opportunity for companies who can mine their own data to create new business insights, and smart products that do everything from detecting fraud and malfunction to diagnosing medical conditions.