Data Maturity Assessment with Sigma Software

Sigma Software, as an Advanced AWS Partner, provides comprehensive Data Governance and Data Maturity expertise to help companies enhance their data capabilities, better understand the organization's data assets, and gain comprehensive knowledge in the data domain tailored to the organization's needs. Aligning with AWS Well-Architecture Framework and AWS Data Strategy, Sigma Software provides a broad assessment of data aspects across an organization's technical and operational processes and practices to evaluate Data Maturity Level. Data Maturity Assessment helps clients to achieve data goals such as:

Conduct a Data Strategy Alignment Leveraging the AWS Data Strategy framework to evaluate a defined data strategy that supports your overall business goals and how well your data initiatives are prioritized, communicated, and funded, and whether they are driving measurable value across the business. Organize a systematic Metadata Management Involves organizing and maintaining data about data assets to help teams discover with the help of AWS Glue Catalog, understand, and trust data assets, enabling better governance, lineage tracking, and faster onboarding for new users. Implement Data Quality framework Focuses on how accurate, complete, consistent, and timely your data is and examines whether data quality is actively monitored, issues are resolved quickly, and standards and tools like Deque and data quality features in AWS Glue DataBrew and Glue Data Studio are in place to maintain trust in the data used for decision-making. Enhance Data Security This assesses the presence of data security practices, including defined roles (like data stewards and owners), data policies, and accountability structures using AWS IAM, AWS LakeFormation and Amazon DataZone. Evaluates how well your organization complies with internal standards and external regulations such as GDPR or HIPAA with AWS Artifact and AWS Security Hub. Define Data Ownership for data assets Defines roles and their responsibilities for specific data assets within the organization to ensure accountability for data quality, security, and compliance, and help clarify approval access, resolve issues with services like AWS LakeFormation and Amazon DataZone Organize recovery of data assets Evaluates how prepared your organization is to restore data in case of loss, corruption, or a system failure and includes tested backup strategies and services like AWS Backup, documented recovery plans, and clearly defined recovery time objectives (RTOs) to minimize downtime and business impact. Implement Data Integration strategy Evaluate how well your components within the system, platforms communicate with each other to share and consolidate data and enable a unified view of data across the organization, reduce duplication, and enhance analytics, reporting, and automation. Data Destruction Evaluate practices of secure and permanent disposal of data that is no longer needed, whether due to regulatory requirements, end-of-retention policies like AWS S3 Lifecycle Policies, or decommissioned systems, and ensure that sensitive or obsolete data is completely removed in a way that prevents recovery or misuse, using verified deletion or physical destruction methods Implement Data Troubleshooting toolset Focuses on effectiveness to detect, diagnose, and resolve data-related issues, such as inconsistencies, broken pipelines, or missing values. Mature troubleshooting practices rely on alerting tools, well-defined processes, and cross-functional collaboration to minimize data disruptions and maintain trust in the system. Cloud Optimization Examines how efficiently your organization uses cloud resources for storing, processing, and analyzing data and includes cost management, performance tuning, security controls, and scalability to ensure your cloud environment is delivering value without unnecessary overhead.