To help organizations manage corporate data throughout its life cycle, we implement a comprehensive data management program, which includes the following elements:
- Drawing up data governance standards and policies to ensure data availability, integration, quality, security, proper usage, etc.
- Evaluating the existing data governance standards and policies.
- Designing data architecture to govern how data is captured, integrated, stored, analyzed, and used.
- Auditing data architecture to align it with the enterprise strategy.
- Consolidating data from disparate data sources with extract, transform, load (ETL) or extract, load, transform (ELT) processes and data virtualization.
Data quality management
- Data cleansing activities, data enrichment and regular data quality assurance.
- Designing, implementing and supporting storage solutions for datasets of varying scale and format.
Reference and master data management
- Enabling data consistency and quality across transactional and business intelligence systems with data profiling, data deduplication and standardization, etc.
- Designing and populating metadata repositories with metadata to ensure localization of a data asset, data lineage, etc.
Data warehousing, analytics, and reporting
- Designing and implementing the BI and data analytics infrastructure to ensure maximized data value.
- Setting up data security practices and regular BI and DWH risk assessment to prevent unauthorized data access and inappropriate data usage.
Data migration and backup
- Moving your data from one system to another for ensured efficiency and security with preliminary data assessment, data migration automation, and data completeness evaluation.