“Big Data + Statistics” to Forecast Macro Economy
Economic development often displays a series of successive conceptual waves. It is particularly important to understand the current state of economy. Big data analytics provides reliable tools to support accurate and timely economic decision-making.
Rapids DB as an in-memory MPP data warehouse and Rapids StreamDB as a distributed in-memory streaming database, can quickly create data applications to achieve the connectivity of the existing corporate data, application systems, software equipment and resources. The pioneered in-memory MPP data warehouse engine helps to reduce processing flows, improve production quality, increase manufacturing efficiency and managing supply chain risk.
- Define strategic objectives
- Develop data analysis index system
- Develop data analysis application
- Put data projects into practice
- Provide a complete picture of the hospital-wide operational status for better-informed strategic planning.
- Tackle rapidly increasing hospital data at rest. Based on detailed and itemized data, calculation and presentation of any operation can both respond within seconds.
- Provide real-time alerting for instant care and quickly respond to new analytic needs.
- Enhance patient management and knowledge sharing.
- Provide intelligent search and management of a growing knowledge-base.
Rapids Data's big data platform has developed a business needs-based labeling classification system and a search engine. Through analysis of customer behavioral patterns in accessing the network, the platform can provide insights into network issues, allowing telco companies to optimize their services with equipment monitoring, capacity planning, and preventative maintenance. It also provides customer matching and marketing strategy optimization recommendations for merchants/advertisers to materialize their data value.
- Real-time data processing and distributed storage: Rapids Data's big data platform allows for linearly horizontal storage capacity expansion and contraction without compromising performance.
- High hardware availability: through software design, hardware failures can be detected and mitigated as part of a routine procedure.
- "Non-shared" architecture: the independence among the distributed machine nodes, data center and data mart prevents resource contention and ensures the efficient and stable operation of the platform.
- Exploratory self-servicing analysis: in response to ever-changing business needs, the Rapids Data platform provides self-service data preparation and analytics.
Financial Services Industry
Rapids Data's big data platform with its in-memory and massive parallel database technology, conducts real-time processing and analysis of the exponential growth of data in the financial industry. It can efficiently and timely process and analyze massive and multi-dimensional unstructured information to allow users to analyze market risks, evaluate intricate financial instruments, discover new investment opportunities and ultimately reduce cost and drive new revenue streams.
- Collect and manipulate data at the right speed, at the right time, to gain the right insights, reducing human involvement at the time of data collection, thus improving data accuracy.
- Monitor market developments in real time, utilizing internal change monitoring and key word search methodology to provide real-time updates.
- Support real-time payment, transaction, balance and other online financial service inquiries.
- Detect potential fraud in real time. Provide portfolio risk assessment to evaluate the return on investment.
- Utilize extracted data to improve business and management flexibility and provide sentiment analysis to understand customers opinions and behaviors to improve customer experience.