Data Governance
Data Governance
A Data Governance initiative is about instilling the concept of managing data as a corporate asset. It is a set of processes to manage enterprise data as a corporate asset and to ensure that business activities use and access data in a simple, uniform, consistent manner.
Data Governance provides organizations with a framework for identifying, managing, and implementing appropriate controls around personal data processing activities. It is designed to help organizations maintain an accurate inventory of processing activities, establish, and apply documented controls around PII usage, and manage data retention requirements.
Advanced Data Governance Framework
FEATURES
Policy Engine
Define the policies and the actionable controls that should comply with regulatory rules and applied to source data to check the quality of the data through the governance process.
Business Glossary
Business Glossary is considered as the heart of Data Governance. Define metadata consisting of standard data definitions and documentation of them bridging the gap between IT and business.
Orchestration Engine
Create source data connection and map the source data by adding the predefined rules to the Data Asset which consists of a group of Critical Data Elements as per business requirement and configure the existing Governance process to check the Data quality of the source data.
Governance Stewardship
Transforming data from a multitude of systems into one single, accurate record through the match-merge concept that helps organizations to identify and resolve duplicate entity records and achieve ‘golden record’.
Governance Metrics
It gives the Data quality trust index score of the selected Data Asset. Users can view the different types of reports related to Data Assets and the Critical Data Elements attached to the Data Asset.
APPROACH
01
Prioritize areas for business improvement
By targeting an area of the organizational structure to act and ensure accountability business improvement can be achieved.
02
Maximize availability of information assets
Increase the availability of information assets with an industry-standard and open integration architecture/ Information asset needs to be accessed in real-time.
03
Create Rules, Roles, and Responsibilities
Organizations must define who does what with data, creating roles, responsibilities, and rules for the process people use in working with information.
04
Improve and ensure information asset integrity
Ensure that our set processes work for you by continuously improving and ensuring the integrity of information assets by Data profiling, parsing, data standardization, data enrichment, and data monitoring.
05
Establish an accountability infrastructure
Our Processes hold people accountable for information assets and provide them with the technology they need to ensure the integrity of the assets remains high.
06
Convert to a master data-based culture
It is the high-value information an organization uses repeatedly across many business processes; Master data exists everywhere in an organization.
07
Develop data analysis mechanism for process improvement
Allows for continual process improvement. Monitoring information assets over time gives a clear picture of how initiatives are performing and provides a way to graphically depict both successes and failures in the process.
BENEFITS
Improved
ROI
Having high data quality standards and using validated data, businesses can take fast and correct decisions, increasing their overall outcome.
Better Customer
Experience
Cohesive customer experience is gained by a better understanding of the customers and their needs by viewing them holistically.
Single Source
of Truth
You can automatically detect duplicate records and create a “golden record” for your key master data objects with lightning speed.
Cost
Reduction
Data Governance implementation protects your operations, processes, and information. This can accelerate cost reductions by 40%.
Fast-Track Your
Business Processes
With total business integration by placing data in one central location, processes can be accelerated by increasing the efficiency and reducing the wait times.
Informed
Decision-Making
Customers are provided with access to valid data, thereby leading them to analyze complex information easily, and be able to make tough business decisions with ease.
Better Data
Compliance
Governance compliance is achieved through the data governance process which is inbuilt by considering the business controls related to data privacy, data security, and data quality reporting as per data governance regulatory norms.
Faster Turn
Around
Our solution not only automates the process of obtaining error-free governed data but also saves an enormous amount of time.
CASE STUDY
Customer
- A leading Banking Customer.
Use Case
- Improve the data quality along with compliance with regulatory requirements.
Business Challenges
- To integrate data from different data sources into one common platform, silos data center.
- To implement data quality checks for the provision of precise data considering the key DQ dimensions like correctness, completeness, integrity, and consistency.
- To implement DG for trust index score, in- return, identify the good data, and rejected data.
- To implement compliance for the fulfillment of regulatory requirements
Project Requirements
- Create an MDM implementation to maintain Consumer (individual) and Customer (Business) records.
- Integration of different source data.
- Cleansing the data with given business validation data quality rules.
- Defining the data management strategy to master current and future consumers and customer data.
Solution Highlights
- Created data governance process as per regulatory policies that will operationalize data governance workflows.
- Created new critical data elements related to customer onboarding as per business requirements.
- Created and customized the data quality monitoring rules and Data Governance process as per the business standards.
- Provided process flow to easily fixing the data quality issues for new and existing bank customers which will increase customer retention thereby growth in bank revenue.
- Generated prescriptive/actionable insights better compliance with policy engine across the organization by enabling to implement of right data policies and controls.
Customer
- A leading Indonesian Banking Customer.
Use Case
- Identifying the Unique Customer Reference from multiple sources for Regulatory and MIS purposes.
Business Challenge
- Automate multiple source data processing using single platform.
- Ability to process the data conversion accurately during 2011 migration.
- Managing the future data processing in a robust and faster way.
AMURTA Value
- Supported in Identifying the Unique and robust Customer Reference from multiple sources.
- Reduced the time taken to view the complete customer view with a compilation of multiple source data.
Results
- Key metric information was provided in near real-time to business executives.
- Related operational Dashboard updated.
- Business is found reliable on future data to improve the customer experience.
- Improved business resource optimization.
SPEAK TO OUR EXPERTS TODAY
If you have queries we are ready to discuss how our Data Insights Platform can help you in improving your organization governance process.
