Unified Big Data Platform

Gamma Platform｜Gamma Data Platform

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Solution Overview

The Unified Big Data Platform leverages Ping An's thirty years of accumulated experience in "data standardization, data assetization, and data serviceization" to provide enterprises, banks, and other non-banking financial institutions with a one-stop, full-link, and intelligent big data platform. The platform addresses the issues of difficult data integration, thin data assets, and weak security, achieving full lifecycle management services for data.

Business Challenges

Chaotic product matrix management and untimely data services:

The management of the product matrix is chaotic, and data services are not provided in a timely manner. The limited service capabilities of enterprise data platforms, coupled with untimely responses and disorganized management, result in delayed data service effectiveness and a poor service experience. This, in turn, affects the data usage experience and business development outcomes at the busine
Siloed data platform construction leading to resource waste:

There is a lack of comprehensive planning for the data product system. Financial institutions and enterprises often independently purchase or build their own business systems, leading to the creation of numerous "data silos" within the organization. This lack of data sharing and exchange, along with redundant construction, leads to a significant waste of resources.
High cost of data governance due to vast business data:

As data platforms expand to a certain scale, they are confronted with the challenge of managing a large volume of data that has been accumulated through business operations. This data gradually forms the enterprise's data assets, but the costs associated with data collection, storage, and processing are excessively high for the enterprise.
Failure to form a data management loop, making it difficult to extract the value of data

Although most customers have established a certain data foundation, the absence of a closed-loop in the full lifecycle of data means that the proportion of data being effectively monetized is low. This inability to provide valuable data services has become a significant challenge in the customers' journey towards digital transformation.

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Product Solutions

Product Strengths

Eliminating Data Silos:

Meet the integration of multi-source heterogeneous data, providing rapid integration of more than 20 heterogeneous data sources and real-time data transmission capabilities. Our product consolidates the entire value chain data, breaks down the barriers between enterprise industry upstream and downstream, and between various systems, achieving unified data convergence and storage.
Accumulating Data Assets:

Create an end-to-end governance loop for enterprise data, making data usable and easy to use. Our product achieves intelligent standard deconstruction, automated quality audit, and error correction throughout the entire data lifecycle. Also,it provides capabilities for data mapping, data lineage, and impact analysis, achieving full traceability of the data chain.
Unified Data Services:

Create a one-stop portal for data query and usage, guided by application value. Forms a service catalog from data assets, allowing for quick location and acquisition of data.Intelligent data services, compatible with various data sharing modes, provide unified external services, ensure data security, and achieve efficient and timely data sharing.

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Customer Cases

A Large State-owned Enterprise in Xiamen

Background: The group hopes to build a big data platform foundation to achieve data convergence, governance, and shared data services at the group level. The project aims to enhance the business efficiency, cost control, and internal and external collaboration of the entire group with digital capabilities, and to build a strong strategic control capability for resources, performance, and risks.
Value: Starting from decision-making scenarios, we clarifies decision indicators, connects with more than 20 systems, establishes four major business themes, 17 industry classifications, and over 400 standard indicators. The project takes a holistic approach, unifying business data and master data-related standards. At the same time, it establishes a digital management cockpit for efficient and visual report management and self-service data analysis exploration. This enables rapid business insights and precise decision-making. It helps the headquarters to achieve a digital penetration strategy loop, implement classified control, drive innovation and development, and become a benchmark for digitalization in the industry.