Big data analysis involves examining current situations through data-driven insights and using modeling and predictive techniques to forecast future trends and optimize improvements. In China, whether in state-owned or private enterprises, the results of data analysis are closely tied to business decision-making. Industries such as banking, insurance, telecommunications, and e-commerce have been among the earliest adopters of these technologies.
**Has the era of big data arrived?**
The trend is both impressive and overwhelming. Today, if you open any media outlet and don’t mention “big data,†it might even feel out of place. This phenomenon is everywhere, even reaching the highest levels of government. But why is everyone talking about big data?
As data volumes grow exponentially, the value hidden within them can no longer be captured by traditional charts or methods. This is why business intelligence hasn’t fully taken off and has been overshadowed by more advanced data analysis techniques. Data analysis is essential for uncovering these hidden values and turning raw information into actionable insights.
The level of data analysis capability directly affects the quality and success of value discovery. Without proper analysis, "big data" is just a collection of unorganized information, resulting in high costs and little return. Currently, the domestic big data boom is still in its early stages—focused on data collection, sorting, storage, and basic reporting. Only a few companies in certain industries have reached the stage of basic data analysis and application.
Looking at the domestic data analysis market, we see a large and growing demand. Many companies, both traditional and internet-based, are exploring this space and are willing to invest. However, the industry remains fragmented and lacks a systematic approach. The sectors with the strongest demand include financial institutions (banks, insurance companies, P2P platforms), internet companies like those in advertising and e-commerce, and others.
There is currently no dominant platform-level company model, which may indicate an early phase before the market becomes more structured. The B2B service environment in China is still developing. Some tech-savvy companies, especially when dealing with sensitive data, prefer to build their own systems rather than rely on external solutions, due to concerns over security and control.
In the future, companies like BAT, JD.com, 58.com, and Didi will likely lead the data field, thanks to their massive data resources. Despite the dominance of large players, the overall industry is vast, and there are plenty of opportunities for smaller companies to carve out their own niches.
**Data Acquisition**
In simple terms, it’s about collecting data. There are currently four main methods:
1. **Web Crawling**: We’ve developed our own crawler platform using Python and Go, extracting information from dozens of websites.
2. **Wi-Fi Access Solutions**: We offer a complete software and hardware solution that provides a high ROI. Property managers can earn money through network fees and promotional charges. This method relies on OpenWRT development and smart hardware integration.
3. **Image APIs**: We provide image search and face recognition services using machine learning and deep learning algorithms, primarily through C++, OpenCV, and MATLAB.
4. **Customer-Provided Data**: Some clients supply their own data for processing.
**Data Mining**
In layman's terms, it refers to using data analysis to gain deep and valuable insights. Based on the data collected through various methods, we can perform basic statistical analysis, understand user behavior, build user profiles, analyze brand relationships, and predict future trends.
Common tools used include Python, R, and SPSS. Algorithms range from basic statistics to more complex ones like Machine Learning, Deep Learning, and Collaborative Filtering.
**Data Presentation**
In simple terms, it’s about presenting analysis results in an attractive and easy-to-understand format, such as icons or graphics. Currently, we offer several forms:
- **Website (PC and Mobile Compatible)**: Provided to paid B-side customers, not publicly accessible. A typical interface is shown below.
- **Public SaaS Cloud Platform**: A cloud-based tool that allows users to create visually appealing reports easily shareable online, especially on mobile devices. It will be launched soon, with a preview shown below.
The technology used includes JavaScript, Node.js, and MongoDB, making it efficient and scalable for real-time data visualization.
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