Data Strategy - Implementation

AWS will provide consulting and advisory services to Customer as described below, for up to the total number of days set forth in this SOW. AWS will advise and assist Customer in building a reusable framework for data ingestion, storage, transformation, cataloging, and consumption to enable the Customer to curate, ingest, and provide access to data assets through the implementation of an AWS-based Modern Data Architecture (the “Solution”) aligned with a Modern Data Strategy, in a non-production environment, with the following activities related to two (2) analytical use cases identified by Customer.

Scope of Work: The scope of the engagement includes building a solution including elements of each workstream noted below to support up to two (2) key analytical use cases and up to three (3) data sources [REVIEW THESE NUMBERS FOR YOUR SPECIFIC CUSTOMER], and implementation of the solution in a non-production environment.

Approach: The solution to be implemented is dependent upon the planning phase and will be delivered within a time-boxed approach to limit the scope of work to the allocated hours. The solution includes implementation of the following workstreams, as defined in the planning phase and further elaborated in Design and Implement phases:

• Mapping the solution to the associated business initiative and describing how the solution can be extended for future phases
• Developing key analytical use case(s)/business use case(s) as defined in the planning phase as part of the solution implementation using Business Intelligence (BI) tools, downstream data consumer applications, in non-production environment

AWS will advise and assist Customer in leveraging or enhancing their current data analytics architecture, including data lakes, data warehouses, and related ingestion and access mechanisms within Modern Data Architecture to support the targeted solution. AWS will advise and assist Customer, in a non-production environment with the following:

• Establishing Modern Data Architecture foundations by:
• Performing AWS Landing Zone assessment specific to Modern Data Architecture
• Defining AWS account and network strategy or aligning with existing Customer’s strategy specific to Data Architecture
• Defining DevOps and continuous integration and continuous delivery (CI/CD) tooling strategy or aligning with existing Customer’s strategy
• Designing Modern Data Architecture by:
• Defining analytics glossary along with data product definitions
• Defining required AWS purpose-built databases such as (e.g., Amazon OpenSearch Service for Enterprise Search and Log Analytics, Amazon Time Stream for Time Series, Amazon Neptune for Graph Analytics) based on the identified use case/s along with a strategy for administration of these data sources
• Finalizing high level solution design along with security and storage strategy
• Documenting future-state recommendation on Analytics, Machine Learning (ML) and Artificial Intelligence (AI) Use Cases Implementation by:
  • Identifying the specific analytical, ML and AI use cases that require the usage of AWS AI/ML Services
  • Providing a future-state recommendation based on the identified use cases and the capabilities of AWS AI/ML Services like Amazon SageMaker, Amazon Q and Amazon Bedrock

AWS will provide the following to Customer:

• Documented use cases and mapping to business initiative
• Documented solution architecture and design document
• Recommendations for follow-up work/backlog including Future Case

• Data domains

AWS will advise and assist Customer with developing data integration processes to ingest and transform data from identified sources into targeted data domains as needed to support the solution. AWS will advise and assist Customer in establishing the data domains for effective distribution of data governance and stewardship responsibilities and for extensibility of shared data domains to support future use cases with minimal rework.

1.1 Workstream Design and implement Modern Data Architecture: based on provided usage requirements, AWS will assist Customer with building the Modern Data Architecture for the identified use cases. AWS will advise and assist Customer, in a non-production environment with the following:

• Creating a detailed design for implementing Modern Data Architecture
• Implementing a data landing zone including data stored in Amazon S3 Storage Service
• Implementing Amazon Virtual Private Cloud (Amazon VPC) and required subnets per the solution design (This is not a full Amazon VPC strategy/Network Strategy for an enterprise, but focused on the current Modern Data Architecture)
• Building data storage including buckets, prefixes, encryption, file types, and partitioning
• Building Amazon S3 bucket policies, logging, and monitoring
• Implementing data lifecycle management
• Building cross region replication if required
• Implement any additional AWS purpose-built databases as identified in the solution design of the identified use cases

1.2 Workstream Design and implement Data Ingestion and Data Integration Layer: based on provided usage requirements, AWS will advise and assist Customer with building the Modern Data Architecture approach for identified use cases. AWS will advise and assist Customer, in a non-production environment with the following:

• Creating a detailed design for data Ingestion and data Integration layer
• Developing a data integration layer including data discovery, extract, transform, and load, cleansing, transforming, and centralized cataloging
• Creating logical data model for data product
• Creating physical data model for data product
• Building data ingestion pipeline for data product
• Building infrastructure as a code (IaC) script and creating CI/CD pipeline for data ingestion pipeline for data product
• Deploying data ingestion pipeline for data product
• Defining and providing access controls for data product hosted in AWS cloud data warehouse

AWS will provide the following to Customer:

• Detailed solution architecture for Data Ingestion and Data Integration layer
• Data Ingestion and Integration Solution aligned to targeted application/analytic use case(s) including infrastructure as code (IaC), CI/CD and data pipelines implemented in a non-production environment
• Solution runbook for helping deploy the solution to production

1.3 Workstream Design and build Data Pipelines for Analytics: based on provided analytical requirements, AWS will advise and assist Customer with building data pipelines for analytics for identified use case(s) and target persona(s). AWS will advise and assist Customer, in a non-production environment and representative data with the following:

• Creating a detailed design and architecture for data analytics pipeline
• Defining testing strategy for data analytics pipeline
• Building Infrastructure as Code (IaC) script and creating CI/CD pipeline for data analytics pipeline for data product
• Orchestrating and Deploying data analytics pipeline for data product

AWS will provide the following to Customer:

• Documented detailed solution architecture and design for implementation of data analytics pipeline layer
• Data Analytics Solution aligned to targeted application/analytic use case(s) including infrastructure as code (IaC), CI/CD and data pipelines implemented in a non-production environment
• Solution runbook for helping deploy the solution to a production environment

1.4 Workstream Design and implement Data Consumption Layer: based on provided consumption requirements, AWS will advise and assist Customer with building consumption layer for the identified use case(s). AWS will advise and assist Customer, in a non-production environment and representative data with the following:

• Gathering data consumption requirements or review existing consumption strategy
• Defining analytics consumption strategy
• Defining BI architecture
• Defining user authentication and authorization process including data access controls
• Defining CI/CD process for BI products (data sources, analysis, and dashboards)
• Building a data pipeline based on the consumption pattern
• Building Infrastructure as Code (IaC) script for consumption pipeline deployment
• Deploying Infrastructure as Code (IaC) pipeline for data product

• Documented detailed solution architecture and design for implementation of consumption layer
• Data Consumption Solution aligned to targeted application/analytic use case(s) including infrastructure as code (IaC), CI/CD and data consumption layer and pipelines implemented in a non-production environment
• Solution runbook for helping deploy the consumption layer solution to a production environment

Design Data Governance and Data Catalog: based on business requirements, AWS will advise and assist Customer in defining data governance standards relevant to the solution. AWS will advise and assist Customer, in a non-production environment with the following in non-production environment:

• Developing a data governance strategy for the solution using AWS services for data quality, access control, data sharing, data classification, and data Profiling
• Designing and developing a data classification framework

Establish Data Governance: based on data governance best practices, AWS will advise and assist Customer with building out governed analytics as it applies to the solution. AWS will advise and assist Customer, in a non-production environment with the following in non-production environment:

• Identifying consumption patterns and use cases for data product
• Implementing data sharing and access control framework using AWS Lake Formation and Amazon DataZone
• Developing a data management service to catalog(technical), discover, share, and govern data stored across AWS
• Optional integration to on-premises catalog and third-party sources
• Providing administrators and data stewards who oversee and their data assets the ability to manage and govern access to data using fine-grained controls
• Setting up controls designed to ensure access with the right level of privileges and context for their users for access to data so that they can discover and use data collaboratively to derive data-driven insights

Establish Central Data Catalog:

Based on user access requirements, AWS will advise and assist Customer with building out a central data catalog. AWS will advise and assist Customer, in a non-production environment with the following:

• Creating data definition language for the data catalog
• Building a searchable data catalog
• Implementing access requirements as part of the Modern Data Architecture implementation

AWS will provide the following to Customer:

• Documented detailed solution architecture and design for implementation of data management and data governance
• Implement data governance and enable data sharing and access control framework in a non-production environment
• Establish technical and central business catalog with data discovery, sharing and governance capabilities
• Solution runbook for helping deploy the data management and data governance solution to production environment

• Performing threat modeling of data threats for solution
• Defining security controls for infrastructure and data protection for solution
• Setting up appropriate data access control for the solution, including data perimeter to limit access to sensitive data
• Defining and Implementing mechanisms of data anonymization
• Defining and Implementing audit requirements for solution
• Identifying and Implementing security logging and monitoring requirements to contribute to their incident response strategy

AWS will provide the following to Customer:

• Documented detailed design along with security controls for infrastructure, data protection, data access control and meeting audit requirements
• Establish technical and central business catalog with data discovery, sharing and governance capabilities
• Solution runbook for helping deploy the data management and data governance solution to production environment

Guidance on People and Processes: AWS will advise and assist Customer with guidance and recommendations for operating the solution and governing the data associated with the solution.

Modern Data Architecture Runbooks: AWS will advise and assist Customer with creating guidance for operating the solution. AWS will advise and assist Customer, in a non-production environment with the following:

• Creating developer guide
• Creating tenant onboarding guide
• Guidance playbook on People and Process
• Modern Data Architecture Runbooks

AWS will provide the following deliverables for Customer during the engagement (“Deliverables”):

• Guidance playbook on People and Process (Operation module)
• Modern Data Architecture Runbooks

• Customer is solely responsible for all activities in its production environments where software, applications, code, or other products are placed into live operation for their intended use by internal or external end users, including:
• Deploying into, operating and maintaining production environments;
• Ensuring AWS consultants are not provided access to production environments; and
• Evaluating whether deliverables are ready for deployment, and assessing all modifications to Customer’s production environments.
• Customer will own and manage all aspects of Customer’s production environments including, but not limited to, AWS accounts, pipelines, deployment gates, logs and records, and access controls.
• Customer will provide access to a non-production environment to AWS ProServe Consultants and this account will be used for implementing the solution