Shulou(Shulou.com)06/03 Report--

Machine learning, data integration and NoSQL are only part of big data's development. This article will introduce seven important trends.

Big data is the source of most digital opportunities. A variety of trends can be observed.

Without big data, digital change would be unthinkable. Because only by acquiring knowledge from data can the enterprise become more agile. Agile capabilities here have two implications: constantly optimizing existing business processes based on data, and replacing outdated processes with better ones.

The growing network also reflects the importance of big data-consider the Internet of things. These new environments and data bring unimaginable possibilities to new business models and creative thinking, which can be verified by fast-growing startups.

1. Machine assistant

Machine learning (or deep learning) involves the automatic collection, storage and analysis of data. It is also equipped with artificial intelligence to understand the information in the data and to identify internal connections.

Machine learning is especially suitable for designing large amounts of data analysis. "if it's a small amount of data, maybe you can learn it yourself with a pen," NorbertWirth points out. (global head of data Science, GFK Market Research Institute)

When entering the field of security, machine learning becomes more popular. There are already a number of projects that are conducive to machine learning to increase security. Banks also see the potential of machine learning, such as making online shopping safer. The system will observe all transactions and try to identify potential criminal transactions from normal trading patterns and take action.

two。 The business model is changing.

IOT (- World networking), together with big data, gives enterprises a new opportunity to optimize traditional business processes, and it is possible to move business to a new business model, so that they can maintain a competitive position. Companies that have taken action have proved this. Vaillant, a thermal power company, for example, has installed small sensors on new products that allow users to control the temperature through a mobile phone or tablet. Digital change has begun to transform traditional thermal companies into technology companies and producers of thermal systems.

Other companies are undergoing the same transformation, satisfying emerging markets by adapting business models. DeutscheBahn, for example, is processing data in a way that has always been very special: VolkerKefer, who is now the late chairman of Deutsche Bahn and Railroad, reports that an application for displaying the status of lifts in real time has been developed on three marathons scheduled by CeBIT2016. This is not only the customer's advantage, but also the group's own advantage-for customers to know whether the lift can work, the group can also quickly send a maintenance team.

3. Make a prediction based on the data

Predictive analysis can predict credible future events from existing data. Predictive maintenance is a classic predictive analysis software, which is used in the planning of maintenance services. Predictive analysis solutions can make good decisions.

When the machine fails to work, it can lead to business losses, for example, one production line is forced to stop, and other machines do not work properly at the same time.

Ground transport is an obvious example. If there is a problem with a section of the railway track and cannot be dealt with in a timely manner, transportation must be suspended. That's why Deutsche Bahn began to install sensors on the tracks. These sensors record the electric energy needed by the motor when transporting the train. By comparing the target curve, we can get the status of the current orbit from the current energy consumption curve. It also allows the company to respond quickly to ensure normal railway transportation, save financial resources and improve user satisfaction.

4. Data integration creates knowledge

In order for data to play a full role, it is necessary to open data access. But enterprise organizations and technical data barriers often prevent such access. Enterprise search systems can help with this. These systems can provide intelligent exchange of data and information between departments and applications.

Access to information must comply with normal working regulations as well as data protection regulations. Integrated rights management ensures that users only access data within their permissions.

5. Graphical display

Dealing with past data is a very complicated thing. This is especially true if the data are still in a mess. It would be very useful if you could use a program to process the data and display it in a chart. How long the structure can be quickly identified, or the customer will quickly understand through a bird's-eye view of these detailed analyses.

These analysis tools should provide simple self-interpretation so that non-professionals can quickly understand and apply these data analysis results without the need for professional IT experts.

6. The whole world is a data set.

As mentioned earlier, big data of manufacturing, considering industry 4. 0.

Small factories are the key to this field. imagine that all the components in the factory are connected and exchange data. They provide a high level of automation so that resources can be more optimized and more cost-effective. It can also allow individual users to get the factory price.

And big data is not limited to manufacturing. It is also applicable to other fields. Health management is a good example. Just like in × × treatment, big data can also be used for research and diagnosis.

When you carry a wearable device-like a smartwatch and bracelet-big data also enters the personal world. These figures are something that health insurance companies have coveted for a long time. For example, Generali predicts that these medical data can rarely be exchanged and shared. Insurance companies want to use English to collect indicators to measure customers' exercise and consumption preferences, which are in line with German data protection laws.

7. NoSQL is a shortcut

Big data has different sources-machine / car / wearable sensors, social networks or email. Traditional relational databases can not satisfy this kind of data. NoSQL database provides more high-end unstructured data processing and storage capabilities.

This trend can be seen from the market analysis report of operational database released by Garter in 2015. Oracle,IBM, Microsoft and SAP are clearly leaders in this field, and people like Mongo-DB,DataStax,Re-DisLabs and MarkLogic have also entered this field.

Original link: http://www.cebit.de/en/news/article/news-details_28928.xhtml

Welcome to subscribe "Shulou Technology Information " to get latest news, interesting things and hot topics in the IT industry, and controls the hottest and latest Internet news, technology news and IT industry trends.