The data grid can overcome many challenges inherent in big data by driving higher levels of autonomy and data engineering alliances among a wider range of stakeholders. However, big data is not a panacea, it brings a series of risks for enterprises to manage.

A smart supply chain involves streamlining operations using many emerging technologies including big data, IoT, blockchain, and RPA.

Seventy percent of respondents expect a return on their investment within one year, while for another 30 percent, a return on investment within six months is desired.

When executives hear the term "big data", they naturally think of an amazing amount of available data. This data comes from e-commerce and omni channel marketing, or from connected devices on the Internet of Things, or from applications that generate more detailed information about trading activities.

The application of big data is just like the use of credit cards. The better you use it, the greater the income. On the contrary, can enterprises bear the cost of mistakes in big data? This article describes 6 major mistakes and solutions.

Enterprises must design IoT devices to ensure that they work properly and comply with cost and aesthetic considerations.

The rise of cloud computing has found a brighter path for the development of small and medium-sized enterprises. Let's take a look at how to apply cloud computing for small and medium-sized enterprises to build their own websites.

More and more companies are turning to blockchain in order to improve their supply chain production processes.

Typical product recalls in the supply chain ecosystem cost $8 million per year, and improved tracking and tracing using blockchain can reduce that annual cost.

As more and more enterprises transfer their business to the cloud platform, it is crucial to understand the most common and dangerous cloud security risks and how to maintain protection.