Runjiang automates 95% of data processing using Oracle Cloud

Founded in 2012, Hebei-based Runjiang Investment Group Limited has deep expertise in property management, commercial operations, and technology incubation, with a core focus on real estate development.

The company wanted a fast, accurate way to extract data for analysis from across internal and external sources. Its legacy systems relied on expensive manual processes that provided no visibility into product performance, competitors, or customers.

Runjiang needed to integrate distinct data sources, including existing customer data and finance data systems, to gain direct visibility into project analysis. It also required a clear, structured way to source, interpret, and consume ever-growing volumes and varieties of data.

After assessing several global cloud vendors, Runjiang turned to Oracle for a cost-effective solution.

The company selected Oracle Analytics Cloud and Oracle Autonomous Data Warehouse to enable a centralized data repository and easily add maps to dashboards to identify otherwise hard-to-see insights from the real estate market. Runjiang can layer disparate maps to visualize correlations between the company’s unconnected spatial data sets and help users navigate data with custom map analytics.

Using Oracle Cloud Infrastructure (OCI), Runjiang organized vast amounts of data into an understandable and actionable format. The company now automates 95% of manual data processing, while significantly reducing the total time and cost involved in learning manual tools.

Oracle Analytics Cloud allows the company to perform community analysis to better understand the relationship between building types, the number of buildings in a community, and average building price. It can also carry out customer analysis to gauge demand, product intention, and purchase.

Runjiang also takes advantage of Oracle Analytics to display market-related data via one intuitive, custom map, enabling its customers to make more-informed decisions. In addition, Runjiang centralized data from multiple disconnected databases into Oracle Autonomous Data Warehouse, eliminating the need for manual extraction. For company executives, the spatial features in Autonomous Data Warehouse make it easier to locate a house within a map, understand the hotspots around a project, and maintain customer information.

In addition, Autonomous Data Warehouse lets Runjiang unite siloed data, easily and securely discover and share governed data, and execute diverse analytics workloads while also meeting data security and system reliability requirements.