Ensuring quality information that feeds actionable decisiveness
With information architectures growing larger, more complex and diverse, the need to effectively monitor and control data quality becomes essential. At CDS, we offer a Data Quality Management (DQM) framework that:
Validates operational data
Reports errors and inconsistencies
Cleanses and standardizes data
Removes redundancy through data matching
Our modular approach provides guidelines and standards, giving you flexibility to adapt to any methodology. Improving and managing your data quality for best performance, DQM provides boundless operational and cost efficiencies.
We develop a uniform data dictionary across disparately sourced systems and formats, ensuring that your data is reliable, effective, usable, and easily retrievable. We also track technological advances and design offerings for the management of the complete Data Quality Life Cycle.
Trust in data metrics is very low due to data inconsistency. To increase trust in business analysis, DQM unifies diverse information assets to ensure:
Accurate financial and regulatory reporting
Reliable timely data that minimizes the impact of bad data in reporting
Enhanced and de-duplicated customer data for effective marketing
Greater control of supply chains with true inventory status
Businesses must find ways overcome obstacles to create accurate and reliable data sourced from a variety of inputs in order to function effectively. Issues they face today include:
Lack of unique data quality validations across the enterprise
Data duplication and silos
Lack of validation during data entry
Unavailability of source data owner and formal data quality strategy
No active participation from business users
Lack of cross-application expertise and data governance teams
Frequent mergers and acquisitions without strategic goals
Lack of source code expertise for legacy applications
Lack of advanced and automated source data profiling
Lack of source data documentation and resulting incorrect table relationships and dependencies
What CDS Provides
CDS develops solutions to manage data quality from all points in your business. We create and refine our DQM solutions to address your specific industry and organizational needs.
CDS’ DQM solution handles data on multiple platforms by profiling the source data to understand its content, structure, quality, and integrity. We address data management challenges with a range of services including:
Data Profiling: Inspections for errors, inconsistencies, redundancies and incompleteness.
Data Quality & Auditing: Correcting, standardizing and identifying data.
Data Integration: Matching, merging or connecting data from a variety of disparate sources.
Data Enrichment: Enhancing data using information from internal and external data sources.
Data Tracking: Checking and controlling data integrity over time.
Our DQM Consulting Framework assesses your:
Risks and their impact
We help you to locate and correct data quality issues in a sustainable manner, prioritize and build a focused strategy to work on strengthening problem areas.
Data quality scorecards and dashboard reports help enterprises measure data quality performance at different levels of the operational business hierarchy. This allows you to monitor both line-of-business and enterprise data governance.
Our DQM framework supports automatic measurement, logging, collection, communication and results reporting to data stewards. This closed-loop monitoring ensures enterprise data quality.
Our DQM solution offers you a competitive advantage through:
Improved Data Quality
We ensure quality data that helps in accurate financial and regulatory reporting, timely decision-making, efficient planning and budgeting and seamless integration during Mergers and Acquisitions.
A well-defined Data Governance framework enhances productivity and customer satisfaction.
Increased ROI from IT
We help you gain more value from existing CRM, BI, DW initiatives.
Single View of your Enterprise
We provide you with a single, accurate and complete view across multiple sources of business critical data improving cross-selling, up-sell insights, targeted campaigns, increased customer satisfaction and retention.
By matching, merging or linking data from a variety of disparate sources, we achieve data reliability through consistency.
Streamlined data and processes
We integrate data management efforts with business processes to increase productivity.
We reduce maintenance costs by decommissioning antiquated data facilities, such as an RDBMS.
Maximize ROI from enterprise applications
Reduce the cost of iterations and rework
Increased competitive advantage
Improve corporate performance and operational efficiency
Reduce uncertainty and risk in missing SLAs
Provide a measurable and accurate view of data for better customer service