Scattered and inconsistent data
Traditional enterprises produce data of various types, including structured, semi-structured, and unstructured data. Data sources include databases, logs, objects, and stock data on existing data warehouses. Data of different formats from various sources has different access and analysis methods. SQL statements are commonly used in most traditional enterprises that build their own business systems based on relational databases. This undoubtedly increases the storage and usage costs.
Forms of enterprise operations are increasingly diversified, such as real-time recommendation, precision marketing, advertising effect, real-time logistics, and risk control. Data timeliness plays an increasingly central role in enterprise operations. Real-time data processing capabilities become an important factor for enterprises to improve their competitiveness. Big data analysis is no longer limited to traditional T+1 scenarios. A growing number of enterprises have higher requirements for data real-time analysis and processing. The traditional batch processing mode has a latency of hours or even days, which cannot meet the business requirements of T+0 business. Users want to analyze large amounts of data within seconds or even milliseconds.
Extremely complex system
Typically, big data platforms are difficult to use. Users want to focus on their core business instead of the underlying technology. They want a ready-to-use solution instead of having to take on high learning costs for complicated technologies. They are eager to have a simple and easy-to-use platform. Additionally, solutions that combine big data platforms are insufficient to meet the requirements for fine-grained access control, high reliability, disaster recovery, and high availability, especially those of customers in industries such as finance.
High usage costs
The use of data in enterprises is cyclical and uncertain. Business changes rapidly, and its data scale also changes greatly. Some business has obvious peaks and troughs. During off-peak periods, resources are often idle. These business characteristics require high resource scalability of the underlying capabilities. The scalability refers to the scalability of both storage and computing capabilities. Users can flexibly select resources and change resource configurations at any time to maximize the return on invested resources based on business requirements.