" Transform your data into a trusted corporate asset "
DATA QUALITY
Good data quality means that an organization's data is accurate, complete, consistent, timely, unique, and valid. Sound business decisions rely upon clean and consistent data sources that provide information about an organization's products, suppliers, financial details, and most importantly, their customers. The better the data, the more clearly it presents an accurate, consolidated view of the Customer, across systems, departments and line of business and the more likely that an organization will be in a position to meet or exceed it's goals.
Data Quality describes various categories of desirable attributes (or dimensions) of data. These include accuracy, currency, completeness and usability.
Annik provides data profiling, cleansing, standardization, linking & matching, hierarchy management, and enhancement services.
Annik's Data Quality Capabilities
Annik works in harmony with trusted data sources [Dun & Bradstreet, Acxiom, InfoUSA, Experian, etc], data governance processes, our custom tools and skilled data analysts, and your business rules in order to resolve exceptions and improve the quality and effectiveness of data assets within your product, financial, supply chain, and customer information management systems.
Annik has developed data quality analytics solutions that enable you to profile and analyze your progress through customized Scorecards. These tools can be adapted and applied to independent data quality projects (or incorporated into enterprise Data Governance and MDM initiatives)
Services provided by Annik in this area are :
Profiling
Formatting & standardization
Cleaning
Matching and creating integrated entities
Enrichment
Real time data quality capabilities
Connectivity/ adaptors
Monitoring & scorecards
Metadata capabilities
On-site/ off-shore flexible-fit resource model
Annik deploys its own Match Engine based on following Search criteria :
Equal Match %, Fuzzy logic % match, multiple business logic
to Deliver de-duped Names in the Master "Dump"
Annik Solution Formation Approach
DATA GOVERNANCE
Is a centralized, enterprise-wide imperative that encompasses the people, processes and procedures required to create a single consistent, view of data owned by an Organization
Key Business Drivers
Increase visibility into the true state of business operations.
Decrease the risk of regulatory fines.
Improve security for sensitive financial and customer data.
Reduce IT costs by duplicated and under-aligned data management policies and practices.
Maximize the revenue generation potential that can be leveraged from higher-quality data within marketing and customer management operations.
Data Governance initiatives improve data quality by assigning a team to develop and manage processes that ensure data's accuracy, accessibility, consistency, and completeness, among other metrics. It is imperative that this team consists of executive leadership, project management, line-of-business managers, and data stewards.
The team usually employs some form of methodology for tracking and improving enterprise data, such as Six SigmaTM, and tools for data mapping, profiling, cleansing and monitoring data. Many companies have numerous business applications and databases that might lack context-based integration.
Therefore, knowledge-workers don't always have access to the information they need to best do their jobs. When they do have the data, the data quality may be faulty due to lack of inconsistent quality standards and processes. By creating and enforcing a comprehensive data governance practice, these problems can be mitigated.
Annik's Data Governance Capabilities
Annik provides clients with key management insight in terms of how data stewardship creates and manages the appropriate metrics and controls surrounding data management processes.
We can :
seamlessly support the processes within an ongoing governance program,
provide leadership and insight for organizations building a governance program,
and adapt our proprietary data governance tools for use within your data governance program
