Data Management Implementation Service

Service Overview

Data Management Implementation Service (DMIS) is designed based on Huawei's data management methodology and Huawei Cloud's data enablement solution to provide professional data services covering the entire data lifecycle, including planning, design, integration, governance, implementation, and O&M. The service drives business operations with data and helps companies improve operations efficiency during digital transformation.

Service Scope

Data management maturity diagnosis: Diagnose and evaluate the maturity of company data management, design a technical route, and plan for maturity improvement.
4A architecture planning and design for data enablement: Conduct as-is survey based on the enterprise's strategic goals, and plan and design business, information, technical, and application architectures, to support the implementation of data management.
Integration and implementation of the data enablement technology platform: Design the technical platform solution, enable and deploy the platform, and import IT and OT data into the data lake.
Design and implementation of the data enablement solution: Design and implement data models, standards, metrics, and quality.
Design and implementation of data application integration: Design and implement scenarios and solutions of data visualization applications.

Prerequisites

You need to apply for DMIS 30 days in advance so we can evaluate your goals and schedules.
Contract authorization is required to provide DMIS services.

Service Content

Data Management Maturity Diagnosis
Data management maturity diagnosis helps you to improve data management capabilities with the maturity model framework and Data Management Capability Maturity Assessment Model (DCMM). It is a process of building and developing data management capabilities based on Huawei's experience. Data management maturity model defines maturity levels by describing the capability characteristics of each phase. The maturity level can be assessed and an improvement solution can be designed when the maturity capabilities meet the certain requirements. Your company can develop and improve under the instruction of the assessment. The higher the maturity level is, the more consistent, predictable, and reliable the assessment is.

The management maturity is assessed in nine capability domains, including data policy and process, data organization, data standard, data architecture, data application, data quality, main data, metadata management, and data security. Under the nine capability domains, there are 28 sub-domains. Each assessment item has five levels. By calculating the average value, the overall data management maturity is evaluated and Enterprise Data Management Maturity Report is generated.

Companies can use the report to identify the current data management shortages, develop data management optimization measures from dimensions such as organization, system, platform, and data, improve data management, and support business strategic goals.
Business Architecture Design
The business architecture describes how organizations use key business elements to achieve strategic goals. It aims to provide companies with a specific business plan, ensures that the business architecture is in line with companies' duties and visions, and supports the achievement of strategic and operations goals.
1. Requirement survey
  Interview and communicate with stakeholders and owners of your company to understand business requirements, pain points, and objectives, and collect data and information about business scenarios, processes, and organizations.
1. Content design
  - Business value stream: Understand and optimize the whole process from requirement generation to value realization, eventually, effectively create value for customers and the company.
  - Business process: Sort out existing business processes and reconstruct or optimize them based on business objectives and scenario planning to realize the efficient operations of organizational architecture.
  - Business scenario: Develop a business overview based on business objectives and requirements, plan business scenarios for the next three to five years, and match the business scenarios with the project implementation plan.
  - Business metric: Based on business operations requirements, sort out key business metrics, unify the business language, standardize metric calculation rules, measure business operations results and performance, and measure business with key performance indicators (KPIs).
Information Architecture Design
The information architecture describes the information and their relationships required during business running and management decision making, that is, structured specifications of the whole set of components. System surveys are conducted based on business requirements, and IT system data exploration are performed to guarantee the management and consumption of future data assets through the data governance center.
1. Requirement survey
  - Information collection: Based on the project requirement scope of the current period, collect business documents, system architecture documents, and data dictionary, including business processes and analysis metric systems.
  - Survey and analysis: Clarify business requirements through interviews and analysis of related documents, understand the target business information architecture, and estimate the expected output.
2. Content design
  - Data asset catalog design: Analyze business data by referring to the existing information architecture and industry's best practices. Design the data asset catalog in a top-down and bottom-up manner (The following describes the directory scope. L1: subject area group, L2: subject area, and L3: data object).
  - Logical model design: Based on business scenarios, output logical entities and business attributes that support business objects (L4: logical data entity and L5: business attributes).
  - Data standard establishment: Design and establish data standards (business attributes) for the important attributes in catalog L5, and specify the names, definitions, business domains, and data owners.
Technical Architecture Design
The technical architecture describes the panorama of recent technical solutions from the technical perspective to support the implementation of the business architecture and information architecture.
1. Technical architecture planning: Plan the technical platform architecture that meets service requirements in the next three to five years in terms of functions, performance, security, reliability, and scalability.
2. Integration architecture design: Based on the technical architecture planning, design the technical platform integration architecture of current projects. Design the integration relationships of cloud services in all directions and the parameter configuration of each service on the technical platform.
3. Network architecture design: Plan the networking architecture of the technical platform, design the network solution for data storage, computing, and consumption in the data lake (VPN, private line, and Internet), design the VPC and subnet solutions of the technical platform based on the enterprise network IP address planning, and design security group rules based on the principle of least privilege (PoLP).
4. Deployment architecture design: Based on the integration architecture, design the detailed specifications and quantity of each cloud service on the technical platform that can support service requirements to guide the implementation of technical platform integration.
5. Security architecture design: Plan the overall security protection architecture from the perspective of the data lifecycle of collection, storage, computing, management, and use, and design a security solution that meets the requirements of the current project and covers all data processing phases.
6. Data integration solution design: Design the batch data solution and real-time data integration solution based on the timeliness requirements of service access and data features (database tables, APIs, messages, and timestamps).
Application Architecture Design
The application architecture describes the applications that support business architectures and process a wide range of data defined by the information and data architectures. Designed based on business requirements and scenarios, the overall application architecture includes components and modules from the frontend, backend, and databases, and the interaction and relationships between the components and modules.
1. Requirement collection and analysis: Hold meetings and discussions with customers to deeply understand application requirements, functions, and problems, and specify the core objectives of application architecture design.
2. Technology selection and evaluation: Evaluate different technology options, select a technology stack that meets project requirements, and consider factors such as performance, scalability, and security.
3. User interface (UI): Design the user interface, including the interface layout, interactions, and visual effects, to provide good user experience.
4. Frontend and backend architecture: Design the frontend and backend architectures, including the page structure, APIs, and data flow.
5. Database: Design the database structure, data model, and relationship to ensure effective data storage and management.
6. UI and function interaction: Design the interaction mode between the user interface and application functions to ensure that users can operate and use applications smoothly.
7. Application integration solution: Design the solution for integrating the application with other systems and services to ensure that the application can collaborate with external systems.
Technical Platform Integration Implementation
In the implementation phase, the technical platform is deployed and data is imported.
1. Technical platform integration: Based on the technical architecture design, configure the integration relationships of services between platforms, and enable and deploy the technical platform.
2. IT data ingestion: Based on the IT data integration solution, use data collection tools such as Huawei Cloud CDM and DRS to import workloads such as database tables, APIs, messages, and files into the data lake in batches or in real time, and complete data cleaning, conversion, and job configuration.
3. OT data ingestion: Based on the OT data integration solution, use the IIoT platform to collect edge data and ingest central data into the data lake.
Data Enablement Solution Design
1. Data model design: Output the physical model design solution of the data enablement platform, layered design solution of the data enablement platform SDI, DWI, DWR, and DM, and job scheduling solution of each layer, based on the data asset catalog and logical model output by the information architecture design.
2. Data standard establishment: Standardize each row of data and the specific values of each field based on existing national, industrial, and enterprise-level standards, to monitor data quality and improve data availability.
3. Data quality monitoring: Design data quality evaluation rules based on the six dimensions of data quality, helping users detect data quality problems in a timely manner.
4. Data metric development: Guide the development of technical metrics based on the service metric specifications output by the service architecture design, and generate the related calculation logics and data dependencies.
5. Data service design: Design RESTful data service APIs (including input parameters and authentication parameters) based on data access requirements.
Data Enablement Solution Implementation
1. Data model: Import the asset catalog of the information architecture to the data governance center for UI-based development of logical model and physical model, script and job development, job scheduling, and O&M monitoring.
2. Data standard: Configure the data generated in the design phase to the data governance center and associate the data with fields in specific physical models.
3. Data quality: Configure data quality check rules and produce data quality jobs and reports.
4. Data metric: Configure technical metric calculation rules in the data governance center, associate dimension tables at the report layer with fact tables, and generate mart-layer metrics on UI pages.
5. Data service: Based on the data service design, technical metrics are encapsulated into data APIs for consumption on the application side.
Data Application Integration Design and Implementation
Data application integration aims to build an application system for data visualization, analysis, and decision-making. It also collaborates with the production system to provide real-time services.
1. Application scenario: Design story lines and page prototypes to meet service requirements.
2. Technology stack: Based on the application architecture, select and design the technology stack that covers visual BI data applications, low-code development applications, and high-code microservice development applications.
3. Application development and integration: Release data applications through tool integration and code development based on the selected technology stack to meet requirements collected from the application scenarios.

Service Process

Phase	Milestone
Startup	Hold a project kick-off meeting and set up a project team. Communicate with related personnel, determine project objectives and acceptance criteria, and provide baseline documents. Develop the project's organizational structure and operating mechanism. Develop the SOW and project plan.
Planning	Obtain business requirements, identify missing and incomplete requirements, and define requirement types. Analyze requirements through the prototype, service survey, difference analysis, and function matching. Design the architecture of new systems with clear requirements. Use various types of design methods to determine the product application architecture, technical architecture, data architecture, integration architecture, and physical deployment architecture based on design principles and quality and security requirements, and properly allocate internal and external requirements to each subsystem or module. Use specified design methods and technologies to perform the high-level design (which must contain the data model design) based on requirements, output the project solution, perform peer review if necessary, and provide a baseline solution and its documents.
Implementation	Based on the project solution, the implementation engineer uses the selected design methods, technologies, and security specifications to perform the detailed design. The implementation engineer writes code and related documents according to the development and security specifications. Test development units and software package configurations through defined tasks, record and fix defects, and end the test when quality requirements are met. Set up a QC team to review the code, related documents, implementation guide, user manuals, and O&M manuals. Formulate and provide the project test plan based on the project plan, including the test scheme, schedule, and rounds. Design integration verification scenarios and use cases based on the requirement specifications, project solution, and product architecture design if necessary.
Verification	Organize users and related engineers to check and verify that the platform and data meet requirements. Record and verify defect rectification. Deliver an acceptance test report.
Trial run	Develop a trial run plan and confirm the plan with relevant parties. Organize a trial run. Prepare the trial run report.
Closure	Create a satisfaction questionnaire after the trial run. The project manager collects the survey targets and organizes the satisfaction survey. The project manager prepares the project summary report according to the template. The project manager convenes the project closure meeting, archives the project data and documents, and releases resources. If resources have been purchased, related personnel must leave. For the projects in specific regions, the regional IT representatives share project experience, collect project documents and summary reports, and share them within the region. Review the project completion status based on the project activities and delivery status. Publish project closure information.

Service Deliverables

Service	Deliverable
Requirement survey	Requirement Analysis Report
Asset catalog design	Data Asset Catalogs (L1–L5) (Excel) Data Standards (Excel) Business Metric Design (Excel) Data Mapping Table (Excel) Logical Model Design (including the ER diagram of the logical model)
Business metric design
Data lake design and implementation	Data Governance Implementation Solution HLD IT System Data Survey Form Huawei Cloud Service Configuration Description
Data integration survey
Data integration design
Data integration implementation
Data modeling design	Data Governance Implementation Solution HLD
Data standard establishment
Data quality monitoring
Data metric development
Data service design	Data Governance Implementation Solution HLD (including data governance design)
Data modeling implementation	Data Governance Implementation Guide Development Specifications ETL Script or Code User Guide O&M Guide
Data standard implementation
Data quality implementation
Data metric implementation
Data service implementation
Data application integration implementation	Data Governance Implementation Solution HLD (including application scenario design) Acceptance Test Cases Acceptance Report

Responsibility Matrix

Shared Responsibilities
1. Negotiate and confirm specific requirements and objectives.
2. Negotiate and confirm project management plans.
3. Negotiate, confirm, and review solutions.
4. Sign a contract.
Huawei Responsibilities
1. Specify a service owner for this project and notify the customer of any personnel changes three working days in advance until the project is accepted.
2. Provide the service within the agreed service scope (customer collaboration required).
3. Perform operations required for the service implementation with the customer's Huawei Cloud account only after being authorized by the customer.
Customer Responsibilities
The customer shall assign a project owner to assist Huawei Cloud in service implementation. The owner is responsible for coordination between the two parties, such as survey assistance, third-party resource coordination, authorization management, and service acceptance.
1. Provide information about the source service system, including but not limited to the requirement information in the survey table.
2. Negotiate with the third-party vendor to assist Huawei Cloud in solving problems if the source system uses third-party software and third-party support.
3. Authorize Huawei Cloud to perform operations related to data governance.

Matrix

This table provides an example responsibility matrix and can be modified as needed.

R: Responsibility

S: Support

No.	Process	Task	Huawei	Customer
1	Project kick-off	Organize a kick-off meeting and formulate the project plan.	R	S
2	Requirement analysis	Conduct a requirement survey and a data survey.	R	S
3	Solution design	Design the information architecture, data integration, data architecture, and data governance.	R	S
4	Resource deployment	Deploy Huawei Cloud resources.	R	S
5	Development	Implement data integration, data governance, and data application integration.	R	S
6	Acceptance Test	Design the acceptance test scheme and cases and verify the functions and performance of the data platform.	S	R

Acceptance Criteria

Acceptance Items
The customer checks the service authenticity based on the service deliverables provided by Huawei. After both parties confirm that the service content, the customer signs the service acceptance report.
Acceptance Process
- Huawei produces project deliverables and performs a self-check. After the deliverables pass the check, Huawei submits an acceptance application.
- The customer reviews and signs for all deliverables that meet the requirements. If the deliverables do not meet requirements, Huawei modifies the deliverables based on the review comments and resubmits the deliverables for acceptance.
- Huawei modifies the deliverables within five working days when review comments were received and then submits new deliverables to customers for acceptance.
- The customer reports the comments to Huawei within five working days when the new deliverables were received. The customer and Huawei Cloud each has up to three chances to submit reviews and modify the deliverables. If Huawei does not receive any written comments from the customer within five working days, the deliverables are deemed to have been accepted.
Project Completion
If the acceptance is confirmed and the customer has signed and sealed the acceptance report, the service is complete.