Data silos and unlinked systems caused employees to waste a lot of time moving information around. In addition, the sheer volume of paper and electronic forms forced employees to manually process documents and verify their contents.
Big Data
What is the significance of digital transformation? This is the answer to the question that every enterprise is looking for, and the most common answer is the reinvention of business processes.
Companies tend to make their Big Data projects large in size and scope when implementing them, but the truth is that most Big Data projects usually end up in failure.
To do big data, first of all, you should understand what is the core of your own enterprise or industry. We often find that many enterprises are defeated not by their current competitors, but by many competitors who are not your competitors. For a simple example, everyone thinks that Amazon is an e-commerce company, but this is wrong. Its main revenue now comes from the cloud (cloud service). That is to say, enterprises need to find their own core data (value).
In order to unlock the potential of advanced visualizations that enable organizations to analyze multiple sources of information and uncover hidden patterns and trends, certain challenges of leveraging big data should be addressed.
On the Internet, everyone leaks certain fragments of information more or less, either actively or passively. When this information is mined by big data, there is a risk of privacy leakage and raises information security issues.
The enterprise data space is growing twice as fast as the consumer data space, in part because organizations are increasingly using the cloud for storage and consumption. Much of this raw data is often located in disparate silos at the point of collection, limiting its use in the enterprise.
Big data has always been a relatively mysterious industry, in recent years because of big data discriminatory pricing only by more than the average person to understand, so have you ever thought about big data whether it is developed or analyzed, where the data inside are coming from?
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.
High-end equipment manufacturing enterprise factory, there are many production-related equipment and various types of equipment, equipment management work more difficult.