BACKGROUND

The "smart meteorology" meteorological industry has long been a data-intensive industry. Since its origin, it has relied on advanced detection technology, sensor technology and storage technology. It has a wide-ranging air, sky, and station monitoring network. Huge amount of meteorological observation data. Weather services are provided in the form of public services. For a long time, the form of weather services has been limited to the narrow scope of providing weather forecasts to the public. Nowadays, with the popularization of big data and the Internet, in addition to serving the public, industries in special fields such as agriculture, fishery, and aviation, such as ordinary enterprises in the financial industry, hope to integrate meteorological data for analysis to gain opportunities .

PAIN POINTS OF THE SUPPLIER OF SMART METEOROLOGY

How to break the traditional forecasting model is a difficult problem. Weather service providers are very mature in weather forecast services and some refined weather services. Now they need to export weather services to maximize the value of weather data. However, the traditional forecasting model has no potential to be tapped. How to quickly encapsulate the meteorological data into pairs of effective services for various industries is a difficult problem.

SOLUTION ADVANTAGES

Core advantages description

SOLUTION INTRODUCTION

FEATURES AND ADVANTAGES OF SOLUTION

CLIENT CASE

The Meteorological Bureau of Z Province has been exploring the expansion of meteorological data services from public weather forecasting to industry and commerce.

In this way, the meteorological data assets can be better activated, and a new path for meteorological services can be explored. Draw on the weather service model of foreign AcuWeather company,

The Meteorological Bureau of Z Province and Company X have used DataFocus to jointly build a business service platform for meteorological data.

After integrating high-quality meteorological data, enterprise users only need to perform correlated data analysis between their own business data and meteorological data, so as to better predict the development of business. The DaaS service platform is trying to be applied in many industries such as transportation and logistics, finance and insurance, energy and power, construction production, tourism, and even home appliances and fast-moving consumer goods, and is empowering various industries.