Data Management

To help organizations manage corporate data throughout its life cycle, we implement a comprehensive data management program, which includes the following elements:

Data governance

• 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.

Data architecture

• Designing data architecture to govern how data is captured, integrated, stored, analyzed, and used.
• Auditing data architecture to align it with the enterprise strategy.

Data integration

• 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.

Data storage

• 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.

Metadata management

• 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.

Data security

• 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.