50%

Faster date processing

100%​

Increase in data volume​

$1M

Annual cost saving

95%​

Source of truth for all data

About the Client

A technology solutions provider in the banking, commerce, and retail industries.

Solution

The solution involved migrating a legacy data platform to Azure Synapse Analytics. It resulted in efficiency, scalability, and cost efficiency of data processing with user adoption increase and data accuracy. The transfer restructured data architecture, allowing for greater innovation and growth.

Overview

Industry: Banking and Financial Service, Fintech, Commerce and Retail
Technology: Azure Data Lake, Synapse Analytics, Tableau
Service Domain: Modern Data Warehouse & BI, Cloud, Data Lake, Legacy Data Platform Migration

Background and Challenge Story

Figure 1. The high-level Architecture Design

Our customer decided to update their data architecture to overcome scalability issues and streamline operations. Their commitment to innovation and adoption of advanced analytics led them to collaborate with CMC Global team and begin the transformational migration to Azure Synapse Analytics.

The client's legacy data platform could not handle the growing volume of data, making it challenging to gain insights from the data in a timely manner. Furthermore, the platform was not scalable, making it difficult for the client to add new users or data. The platform also had data quality issues, which made it hard to trust the data.

CMC’s Approach and Solution

Our customer decided to implement Azure Synapse Analytics, a cloud-based data management service to deal with the explosive growth of data, scale easily, and provide high-quality data. The migration to Azure Synapse Analytics enabled our clients to upgrade their data infrastructure and gain the insights needed to make better decisions.

We offered our client a transformative data management solution through the transfer effort to Azure Synapse Analytics. Significant advancements in data processing, scalability, cost-effectiveness, and data quality resulted from our complete strategy, which solved problems and unlocked new opportunities.

Figure 2. Full Data Flow for the new Enterprise Data Platform on Cloud

What our team did
Evaluated our client's existing data infrastructure to define their specific needs and objectives.
Adjusted our solution to the customer's specific needs, considering their budget, timeline, and expected outcome.
Collaborated closely with the client to enable a smooth movement of their data to Azure Synapse Analytics.
Implemented sophisticated data cleansing and normalization processes to improve data quality.
Cautiously configured Azure Synapse Analytics to optimize performance and scalability.
Specified resources, established secure connectivity, and ensured systems compatibility.
Extensively validated data and used efficient transfer techniques to minimize downtime and disruption during migration.
Tested, optimized, and fine-tuned queries and workflows to maximize data processing speed and efficiency.
Provided comprehensive training to the client's teams to leverage advanced analytics capabilities.
Offered ongoing support and monitoring to ensure a smooth transition and continued success.

Results

The Azure Synapse Analytics migration project had a significant influence on our client's data management capabilities,  delivering tangible benefits in key areas:
Improved Data Processing Speed: Achieved a 50% reduction in data processing time, allowing for real-time analytics and faster decision-making.
Improved Scalability: Scalability increased threefold, supporting over 6000 users at once and handling exponential data expansion.
Cost Savings: A $1 million annual savings resulted from eliminating hardware infrastructure and reducing maintenance and licensing costs.
Improved Data Quality and Accuracy: Automated validation and cleansing processes improved data accuracy by 95%.
High User Adoption and Satisfaction: Achieved 90% user adoption in the first month, with users praising the user-friendly interfaces and extensive analytical features.

Thanks to the transfer to Azure Synapse Analytics, our customers improved data processing speed, scalability, cost savings, data quality, and user satisfaction. This transformed their data management capabilities and empowered them to drive industry innovation and long-term growth.

30%

Increase in User Satisfaction

40%

Reduction in Time and Effort Needed for System Updates

50%

Increase in System Performance

About the Client

A global financial company that provides a wide range of banking and financial services to people and businesses worldwide.

Solution

We implemented a scalable containerized microservices architecture on AWS EKS. To handle unstructured data, we linked AWS DocumentDB & ElasticSearch, and to streamline workflows, we used jBPM & Drools. We use React to redesign the UI/UX, & Kafka for seamless integration with upstream systems.

Overview

Industry: Banking and Financial Service Technology: AWS Serverless, S3, React, Microservices Architecture, EKS (K8S) Service Domain: Cloud, Legacy Modernization and Migration

Background and Challenge Story

Before working with us, our customers had several issues with their current system. The outdated infrastructure could not keep up with the growing data volume, which resulted in poor performance and limited scalability. Unstructured data could not be handled by the traditional relational database architecture effectively, which slowed data analysis and decision-making processes. The client also needed help adapting their system to changing business requirements. The existing architecture needed to be more flexible, making implementing changes and updates less complicated and time-consuming. As a result, businesses lost their competitive edge and hesitated to respond to market needs. In addition to these technical limitations, the client recognized the need to improve their user interface and user experience.

CMC’s Approach and Solution

Following clients' need to upgrade their data management, modernize their user interface, and relocate to the cloud, CMC Global created a strategy to help them achieve these objectives. Our team of experts redesigned their infrastructure, optimized their data processing, and delivered a better user experience. CMC Global worked closely with the client to design and implement a comprehensive solution that met their needs. The solution included a containerized microservices architecture, handling of unstructured data, optimized workflows and automated business rules, seamless integration with upstream systems, updated UI/UX design, and cloud-native deployment and infrastructure. By following best practices in cloud architecture, security, and performance optimization, we delivered a robust and scalable solution that modernized the client's infrastructure, optimized data processing, and enhanced the user experience. The combined approach enabled the client to overcome challenges, achieve remarkable outcomes, and position themselves for success in their industry.

Results

Serverless architecture has opened new possibilities for innovation. The team is now able to adapt quickly to changing business needs, make data-driven decisions, and stay competitive in their industry. An upgraded UI/UX design offering a more smooth and intuitive experience allows for a 30% improvement in user satisfaction, helping the client handle increasing data volumes and user traffic. The new UI/UX design is created using React, a modern JavaScript library that makes it simple to create interactive and responsive user interfaces, adapt to changing business requirements with ease, boost system performance by 50%, and guarantee a system uptime of 99.99%.

20%

Decrease in Development Effort

30%

Increase in Productivity

15%

Cost Savings through Cloud Deployment

About the Client

Our client is a leading logistics company based in Singapore, operating in the transportation and supply chain industry.

Solution

Developing a cloud-based microservices architecture on AWS to enable real-time tracking and collaboration in logistics. MSK, Java, NodeJS/Express, and DocumentDB were used to ensure robust data management and communication.

Overview

Industry: Logistics Technology: AWS EKS, Java, NodeJS/Express, AWS MSK, S3 Service Domain: Cloud App Development

Background and Challenge Story

In a fast-paced business, our logistics customer experienced serious problems with their transportation tracking and collaboration system. The previous systems were outdated, with no real-time capability or efficient communication channels. As a result, there were delays, misunderstandings, and decreased overall operational efficiency. To address these obstacles, our client required a modern solution enabling real-time tracking, improving team and organizational cooperation, and offering a user-friendly web portal for daily tasks. They also needed a scalable microservices architecture to meet their increasing demands and facilitate seamless cloud deployment, specifically on AWS.

CMC’s Approach

We implemented a solution strategy to address the logistical issues centered on delivering a powerful, real-time tracking and communication system. This approach enabled us to have a scalable transportation tracking and collaboration system, providing real-time monitoring, streamlined task management, and improved operational efficiency. Using our cloud application development and maintenance expertise, our team was responsible for designing, creating, and supporting the system. Focusing on delivering a scalable and reliable solution, we used Java, NodeJS/Express, AWS infrastructure, and DocumentDB for efficient data management. We also used AWS MSK to enable event listening from tracking devices, ensuring real-time updates and precise shipment information. Our client's logistics operations were to be transformed by offering a modern, real-time tracking and collaboration solution that would streamline procedures, improve communication, and enable effective task management. We sought to provide our customers with the tools they needed to overcome logistical obstacles and achieve operational excellence through our comprehensive solution.

Solution Story

We began by conducting a thorough analysis of the client's requirements, understanding their need for real-time tracking, collaboration, and document management. Using a microservices architecture, we created a scalable and modular solution that could adapt to their changing needs. We built a strong solution using a technology stack that comprised Java, NodeJS/Express, AWS infrastructure, DocumentDB, and AWS MSK. We integrated AWS MSK to listen to events from tracking devices, ensuring real-time updates and enhanced tracking capabilities. The system provided a user-friendly web portal that allowed end-users to easily access and perform daily tasks. Shipment routing and tracking, task dashboards, progress tracking, team management, and seamless communication were all incorporated. We used an agile strategy throughout development, allowing flexibility and iterative changes. Strict testing and quality assurance measures were implemented to ensure reliability, performance, and security. The solution underwent extensive testing to validate its functionality and guarantee a seamless user experience. The deployed solution met the client's needs by providing real-time tracking, effective task management, and increased communication. The scalability and adaptability of the system enabled future enhancements and the capacity to respond to changing company needs. Our client received exceptional customer satisfaction, and the project was completed on schedule and with minimal effort.

Results

The transportation tracking and collaboration solution has generated success for the whole system with streamlines operations, collaboration enhancement, customer service improvement while being scalable and adaptive. Effort optimization: Development effort is reduced by 20%. High customer satisfaction: Customer satisfaction scores are consistently above 90%. Enhanced efficiency: Operational efficiency is improved by 30%. Scalability: The system was built on AWS using a scalable microservices design, which can handle growing user load and data volume. Cost-effectiveness: Cloud implementation results in a 15% cost savings.

500​

VMs & Services Migrated to AWS Cloud

60%

Reduction in Cost of Ownership

20%

Reduction in Operational Costs

About the Client

A leading Japanese entertainment and e-commerce company.

Solution

The solution involved migrating the entire operating system, including servers, databases, front-end, and back-end components, to the AWS environment.

Overview

Industry: Entertainment, E-Commerce Technology: AWS EC2, Lambda, Aurora/PostgreSQL, DocumentDB, SES, SNS, Terraform, Ansible, AWS Serverless, AWS CI/CD, Java, PHP, and VueJS Service Domain: Migration and Modernization, Cloud

Background and Challenge Story

Our customer, a well-known entertainment and e-commerce company in Japan, faced the challenge of migrating their whole operating system to the AWS Cloud within a tight deadline of just six months. With approximately 500 virtual machines and services, the migration involved complex tasks that required extensive cloud expertise. The client also needed to develop new features to meet business demands, including online product release, SEO, and marketing.

CMC’s Approach and Solution

The solution approach for the migration project to AWS Cloud involved the following key steps: 1. Comprehensive Migration: The entire operating system, including servers, databases, front-end, and back-end components, was migrated to the AWS environment. This ensured that the previous system was seamlessly transitioned to the cloud. 2. Feature Development: New features were developed to meet business demands, such as online product releases, SEO, and marketing enhancements. This allowed our client to leverage the capabilities of AWS and enhance their online presence and customer experience. 3. Technology Stack: AWS EC2, Lambda, Aurora/PostgreSQL, DocumentDB, SES, SNS, Terraform, Ansible, AWS Serverless, Java, PHP, and VueJS were all used in the solution. This technology mix created a stable, scalable infrastructure to support client needs. We successfully migrated their whole operating system to the AWS Cloud by adopting this solution approach, developing new functionality to satisfy business objectives, and leveraging a comprehensive technology stack to enable a seamless and efficient transition.

Solution Story

In order to solve these issues, our team worked together with our client to provide a comprehensive solution. The solution entailed transferring the complete system to the AWS environment, including servers, databases, front-end, and back-end components. This guaranteed a smooth and seamless transfer while protecting the previous system's functionality and integrity. In addition to the migration, we worked closely with the client to develop new features that met their specific business demands. These included online product release capabilities, enhanced search engine optimization (SEO), and improved marketing capabilities. By leveraging the power of AWS services and technologies such as AWS EC2, Lambda, Aurora/PostgreSQL, DocumentDB, SES, SNS, Terraform, Ansible, AWS Serverless, Java, PHP, and VueJS, we delivered a robust and scalable infrastructure to support these new features. We kept a significant focus on efficiency and cost minimization throughout the project. As a result, the client's total cost of ownership was reduced by 60% compared to their previous on-premises system. Additionally, operational expenditures were lowered by 20%, resulting in significant cost savings for the firm. The smooth transfer to AWS Cloud and the development of new features established CMC Global as a reliable cloud consulting partner. The successful migration of 500 virtual machines and services and the cost and operational savings demonstrated the solution's effectiveness and solidified our partnership with our client.

Results

Our solution had a transformative impact on our client. The key outcomes include: Time and Cost Efficiency: We migrated 500 virtual machines and services to AWS within a tight 6-month timeframe. This reduced the cost of ownership by 60% and operational costs by 20%, allowing for more efficient resource allocation. Scalability and Flexibility: AWS Cloud provided a highly scalable infrastructure, enabling our client to handle rising user needs and expand their entertainment/e-commerce services effectively. Enhanced Business Capabilities: New features like online product releases, SEO enhancements, and increased marketing capabilities were developed, empowering our clients to deliver a superior customer experience and stay ahead in the industry. Trust and Partnership: The successful migration positioned CMC Global as a trusted consulting partner on cloud operations, opening doors for future collaborations and opportunities. Our solution enabled our client to achieve time and cost efficiency, enhance business capabilities, and establish a trusted partnership, driving their success in the entertainment and e-commerce industry.

40%

Cost Savings

20+

Fintech Apps Delivered

$1M

Transactions per Day

70%

Reduction in Fraudulent Activities

About the Client

A Singapore-based key player in the fintech industry.

Solution

CMC Global delivered a comprehensive solution on the scalable AWS infrastructure, with a focus on web-based and mobile distributions, blockchain-based loyalty programs, and AI/ML-powered fraud detection.

Overview

Industry: Fintech Technology: AWS EKS, S3, AWS ML, Java, VueJS, Native Android/iOS App Developments, Blockchain Service Domain: Cloud App Development, Blockchain Development, Advanced Analytics AI/ML

Background and Challenge Story

Our customer realized the need for strategic application development to improve their organization and capitalize on rising prospects in the fintech industry. However, they encountered multiple challenges in fulfilling their objectives. They sought to establish an offshore delivery center to pair with their onshore staff and maximize the advantages of cost-effective collaboration. They also aimed to incorporate cutting-edge technology such as AI/ML and blockchain into their applications to improve user experience and strengthen fraud detection and prevention capabilities. With an ambitious project scope that spanned multiple work streams, including core banking, smart lending platforms, supply chain finance, smart agent teams, eKYC, and smart interviews, our client faced the challenge of effectively managing and coordinating development efforts across diverse technologies and business domains. They needed a partner who could not only deliver high-quality solutions but also ensure smooth system operations and customer satisfaction. To overcome these challenges, our client engaged our expertise and embarked on a journey to establish a scalable offshore delivery center in Vietnam. The goal was to leverage the talent pool and cost advantages in Vietnam while maintaining close collaboration with the onshore team in Singapore. This strategy enabled optimal resource allocation, lower development costs, and faster project timelines.

CMC’s Approach and Solution

We established an offshore delivery center in Vietnam to satisfy the client's desire for a scalable and cost-effective development methodology. By leveraging the large talent pool and favorable cost structures in Vietnam, we created a dedicated team of skilled professionals who collaborated seamlessly with the onshore team in Singapore. To deal with various work streams, we adopted a technology-driven approach. Our development team utilized Java, VueJS, ReactJS, and mobile app development to build powerful and user-friendly fintech applications. We integrated advanced technologies, including AI/ML and blockchain, to enhance fraud detection capabilities, prevent financial crimes, and ensure secure transactions within the applications. Throughout the project, we maintained constant communication and collaboration with the client. We conducted thorough requirement analysis, provided regular progress updates, and incorporated feedback to ensure the solutions aligned with the client's vision. Our experienced development team and comprehensive technology stack enabled us to overcome challenges and deliver innovative and high-quality solutions. Establishing the offshore delivery center in Vietnam, combined with our technology-focused approach, allowed us to effectively address the client's challenges, accelerate development timelines, and optimize cost efficiency.

Solution Story

During the implementation and deployment of the solution, we encountered several challenges that required innovative approaches and problem-solving skills. One of the key challenges was managing the coordination between the onshore and offshore teams, ensuring effective communication and alignment of project goals. We established clear communication channels, implemented agile project management methodologies, and conducted regular video conferences and workshops to bridge the geographical gap and maintain a cohesive team. Another challenge was ensuring the seamless integration of different technologies, such as Java, VueJS, ReactJS, AI/ML, and blockchain. We faced compatibility issues and complexity in integrating these technologies within the Fintech applications. To overcome this, we conducted thorough testing and quality assurance processes, identified and resolved technical bottlenecks, and collaborated closely with the client's technical team to ensure smooth integration. Additionally, the project timeline posed a challenge as it required the efficient execution of multiple work streams within a specified timeframe. We implemented a phased approach, prioritizing critical components and delivering incremental releases to ensure steady progress and timely completion of each work stream. This allowed us to maintain project momentum and address any unforeseen challenges or changes in requirements. Despite these challenges, our dedicated team of skilled professionals, combined with effective project management and agile methodologies, enabled us to overcome obstacles and deliver high-quality Fintech applications successfully. The solutions we developed played a pivotal role in driving customer deployments to banks in Southeast Asia, enhancing operational efficiency, and meeting the demands of the Fintech industry. The project's success was evident in the smooth and obstacle-free operation of the developed systems, high customer satisfaction scores, and the recognition of our offshore delivery center as the largest in Asia. Through collaboration and innovation, we navigated challenges, delivered impactful solutions, and supported our client in their mission to revolutionize the Fintech landscape.

Results

The set up of an ODC has opened new opportunities for the company. It achieved a remarkable cost reduction of 40% by leveraging the offshore delivery center model in Vietnam, enabling our client to allocate resources efficiently and invest in further technological advancements. They developed and deployed 20+ fintech applications within aggressive timelines, showcasing the offshore team's expertise and ability to deliver high-quality solutions Now that the company has implemented AI/ML-powered fraud detection, it has seen a 70% reduction in fraudulent activities, safeguarding the financial ecosystem. The scalability and reliability of AWS infrastructure is leveraged to support the rapid growth of users, handling over 1 million transactions per day with no service disruptions. They also successfully launched a blockchain-based loyalty program, increasing customer engagement by 30% and driving customer retention and satisfaction.

About the Client

VPBank is a leading Vietnamese bank founded in 1993 with a strong focus on retail and SME banking that has successfully adapted to the digital age by investing in technology and innovation. The bank has a network of over 500 branches and ATMs nationwide.

Solution

CMC successfully helped our client evaluate and consult the data strategy and apply the solution architecture that is well-suited for the 10 next years. Perform the POC by building the end-to-end data pipeline that encompasses various business scenarios as illustrative examples.

Overview

Industry: Banking and Financial Services Technology: AWS Step Functions, AWS S3, AWS Glue, Amazon Athena, Amazon Redshift, Amazon CloudWatch, Amazon MSK, Amazon Kinesis, Amazon Managed Grafana Service Domain: BI and Analytics

Background and Challenge Story

At that time, our customer needed a system that could manage a large volume of data from hundreds of sources and automatically detect changes in data sources. First, the system needed to be scalable, versatile, and capable of integrating with a centralized monitoring system. Besides, as the requirements for streaming data flow are complex, the system should be able to handle numerous sources, topics, and consumers. In addition, a metadata management tool was also needed with a system that met security standards. The POC success requirements were challenging, and the system must meet high SLAs with limited resources.

CMC’s Approach

The customer has worked closely with CMC Global team to propose a complete and highly adaptable core data framework on the AWS Cloud. Following AWS's industry-leading security practices, the framework is secure, scalable and adaptable, allowing it to handle data of any volume and type. The framework also contains modules for data validation, cleasing, enrichment, monitoring, logging, fault tolerance, and error handling to guarantee the data processing pipelines' reliability and stability. Therefore, all data will be validated, cleansed, and enhanced to ensure accuracy, consistency, and reliability. OpenMetaData is used for data governance, with an easy-to-use interface and the flexibility to combine numerous data sources and flexible authorization choices.

Impact

The proposal has been approved and highly appreciated by the customer. Furthermore, the proof-of-concept (POC) evaluation to verify the solution's utility produced excellent results. The POC result not only fulfilled success criteria but also surpassed our customer expectations. The customer's acceptance and appreciation served as an indicator of the hard work, expertise, and attention put into creating the proposal, setting the foundations for a successful collaboration and a profitable future. This exceptional outcome solidified our customer's confidence in the proposed solution and further strengthened the business relationship.

15%

Decreased in Stock Level for the Same Revenue

30%

Cutting of Truck Count in the Same Transportation Workload

20%

Saving in Supply Chain Cost

About the Client

Our customer has a supermarket chain in Vietnam with over 1,000 stores nationwide. It sells various products, including food, apparel, electronics, and home furnishings.

Solution

We collected and processed data using Microsoft services to improve supply chain & sales operations. For the supply chain, the system generated PO suggestions with ML to optimize routes & delivery times. For sales & marketing, we analyzed customer behaviors to generate promotion recommendations.

Overview

Industry: Retail Technology: Azure Synapse Analytic, Power BI, Azure Analytic, Azure Data Lake Gen 2 Service Domain: Cloud, Data Factory, Data Lake, BI and Analytics

Background and Challenge Story

At that time, our client needed to improve their supply chain efficiency and sales activities and implement the best practice of data platforms to adapt to market needs. As our client’s ordering activities mostly relied on the experience of supermarket and warehouse managers, it led to high ordering and inventory costs. Besides, marketing promotions only focused on pushing slow-selling goods and campaigns from suppliers, which is unbeneficial to the business revenue. Their operational system was outdated, frequently overloaded, and poor performed, especially during the data extraction period for reporting purposes.

CMC’s Approach

We implemented the project by collecting and consolidating the processing of enormous data volume from the import, export, and selling transactions of 30+ supermarkets & 7 warehouses using Microsoft services. Subsequently, we utilized data to optimize the supply chain and sales operations. For the supply chain: Based on the current stock level, sell-in, and sell-out history, the system forecasted and automatically generated PO suggestions with detailed goods and quantities. These activities shortened the ordering process and optimized inventory costs, therefore reducing supply chain costs. We also applied the machine learning (ML) model to optimize the route and delivery in-time points to save transportation costs. For sales and marketing operations: Our data system analyzed customer behaviors and automatically generated promotion recommendations. These programs have proven effective in increasing customers' transactions at the supermarket and creating larger purchases. The methodologies applied include Cohort analysis, RFM analysis, and some recommended ML models..

Impact

The successful application of machine learning in many activities: PO suggestion, optimizing the route and on-time delivery point, individual promotion recommendation, highly available and stable operational system, centralizing monitoring and cost management has led to the following results: • 15% Decrease in stock level while maintaining the same revenue • 30% Cutting of truck count for the same transportation workload • 10% Increase in Bill count and 20% increase in cart value • 20% Increase in customer return rate • 20% Supply chain cost savings

80%

In Digitalize Process

30%

Cutting of the Manual Workload

15%

Saving on Operation Cost

20%

Increase in Revenue

About the Client

The corporation includes a holding company and 35 member companies operating in many industries: Exploration & Production, Refinery – Petrochemical, Power Generation, Petroleum Services, Gas Industry

Solution

CMC centralize data entry, establish data quality processes, and implement a data storage system with multiple layers. As well as develop flexible frameworks, leverage Microsoft technologies, Azure Data Lake and create data streaming pipelines.

Overview

Industry: Oil & Gas, Manufacturing Technology: Azure Synapse Analytic, Power BI, Azure Analytic Service Domain: Cloud, Data Factory, Data Lake, BI and Analytics

Background and Challenge Story

Our client turned to CMC Global when they realized several business problems, including: Inefficient management reporting: Compiling comprehensive management reports across the corporation was manual and error-prone, leading to delays and inaccuracies during the decision-making process. Lack of transparency in procurement: The procurement management process was not transparent and lacked monitoring and evaluation reports, which made it difficult to track spending and ensured that contracts were awarded fairly. Ineffective investment project management: The investment project management mechanism was inefficient due to a lack of clear investment decision-making criteria, which resulted in wasteful use of capital resources. Inefficient operation of manufacturing plants: The manufacturing plants needed to be improved due to disparate IT infrastructure, fragmented data, and manual processes. This led to high inventory costs, low-quality output products, and low machine performance. The company also identified 2 requirements to solve these problems: First is improving the management reporting process and centralize data storage by implementing a data platform and report system across the corporation to support automated management reporting and information utilization. Then, maximizing automation of processes at the production plants to enhance operational efficiency by implementing the sub-data platform at factories to facilitate data transformation, create the smart factory, and optimize production efficiency.

Project and Technical Challenges

Project Challenges The project scope covered multiple business functions in various domains with complicated features. During the implementation phase, engaging and collaborating with many stakeholders was required, which resulted in disagreements over deployment techniques, requirement unification, and even competing interests. The project's schedule was put at risk due to the heavy workload and short implementation time. Technical Challenges For the corporation It was challenging to integrate diverse data sources with multiple operating systems on-premise and in the cloud. At the same time, handling a large volume of data daily required complex data processing logic. Moreover, national data security policies restricted cloud storage possibilities and the reporting system must support flexible analysis and data self-service. For the factories Frequent changes in the input data structure posed challenges for data governance. To govern the data collected, a central data platform was needed to serve as a data hub and to meet the needs of analysis and monitoring. Data streaming was also essential for measuring machine parameters, product quality, environmental data, and fire safety. As to optimize manufacturing activities such as machine performance, malfunction prediction, repairs, equipment maintenance, product quality improvement, and inventory cost optimization, data applications were put into use.

CMC’s Approach

Project Solution To ensure comprehensive gathering and analysis of requirements and solutions, CMC Global assigned experienced resources to the project, primarily the roles of DA and BA with substantial expertise in business functions and several experts in adjacent disciplines. The team designed a transparent deployment approach, including specific roles, communication, conflict resolution processes, and effective interest management. The project also included training to increase end-user understanding of the digital transformation plan, data self-service capabilities, and technical deployment. Technical Solutions For the corporation The team starts with centralizing the data entry portal and build data quality processes for integrating external data sources and providing data services across the company. The process uses technology with similar characteristics and flexible migration to comply with data policies and enable a smooth migration. Finally, CMC team sets up a data storage system with multiple layers for varying levels of data self-service. For the factories The 1st step is developing flexible frameworks to automatically detect and handle changes in input data sources for efficient data governance. We create a data streaming pipeline to build machine learning models for optimizing plant operations based on specific needs. Then, the team uses cloud solutions to save expenses and leverage data from multiple factories to find practical solutions. At this stage, we leverage Microsoft technologies and Azure Data Lake to fully utilize cloud capabilities.

Impact

For the corporation: The centralized management reporting system is automatically updated, enabling BOD to make accurate decisions resulting in financial benefits, particularly investment strategy-related. Now that the self-service data culture is adopted, specialized departments make more decisions toward improving operational productivity and increasing revenue and profits across all corporate sectors. We also implement a transparent data system that reduces negativity while minimizing waste and loss. For the factories: The assistance of an integrated and centralized data system has digitalized the operation procedures, and plant operations can now be monitored in real-time. This decreases manual burdens, lowers costs, and improves operational efficiency. Automated production planning is based on historical and market data, ensuring high accuracy and efficiency, resulting in cost savings and enhanced earnings. The results of machine learning application look promising for the company's growth. Reduced downtime and increased machine performance are the results of early detection of machinery operation issues, maintenance, and repair recommendations using ML. The factories now optimize product quality through machine learning-based calculations of input material ratios. They also start managing security through automatic recognition systems and real-time monitoring of people entering and leaving the plant using ML.