Data Intelligence Management - RPA Robotic Process Automation - Data Operations Management - GETECH

Industry Pain Points

1. Data Transformation Difficulties

Enterprises collect multi-source data that is difficult to transform into data assets and is not effectively utilized

2. Uneven Data Quality

Inconsistent data standards, uneven data quality, data application value cannot be fully realized

3. Inefficient Manual Operations

Enterprises have many tedious repetitive tasks, manual operations are inefficient, time-consuming, and laborious

4. Low Operational Efficiency

Many park management matters, relatively insufficient service capability, management capability, emergency handling capability, park resource sharing capability, etc., leading to low operational efficiency

Solutions

1. Data Intelligence
Provides a data intelligence management system and implementation PaaS platform to help enterprises achieve data aggregation, data development, data analysis, data services, and data visualization, promoting data value realization

2. Data Governance Consulting
Provides data governance services for manufacturing enterprises, including master data, metadata organization, establishing data standards, etc., building enterprise data asset centers, and formulating data standard systems such as enterprise standards and standard approval

3. RPA Robotic Process Automation
Provides RPA solutions, achieving efficient automation of fixed-rule, repetitive tasks across users and systems, replacing low-value business processes performed by full-time employees with robotic virtual employees operating applications

4. Smart Park Integrated Management
Provides integrated park management solutions, integrating various park data resources, achieving visual and intelligent monitoring management of parks, and improving park digital management levels

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Customer Value

Data Assetization
Achieving manageable, findable, understandable, trustworthy, and accessible data assets, supporting data assetization and valuation, promoting data-driven decision-making
Data Value Enhancement
Achieving improved data quality and data reuse rate, meeting internal data application needs, ensuring the rationality and reliability of decisions
Efficiency Improvement
Releasing productivity from heavy repetitive work, reducing manual operations, improving work efficiency
High-Quality Development
Achieving visual management of smart parks, building green, safe, efficient, and intelligent industrial parks, helping park enterprises share resources and achieve high-quality development