Data Quality
Data Quality
Data Quality refers to the methodical approach, policies, and processes by which an organization manages the accuracy, validity, timeliness, completeness, uniqueness, and consistency of its data in systems and data flows.
FEATURES
Data Profiling
DIP provides an ability to identify the imperfection as well as uncover relationships across different data sources. It profiles the data from multiple sources like data warehouses, cloud applications, spreadsheets, and so on. A comprehensive set of pre-built business rules as well as customized business rules can be used to accelerate the Data Assets to meet the business requirement standards.
Data Validation
DIP enables users to define and customize the business validation rules against which data sets can be evaluated. These standard data quality rules can be predefined and reused which can save a lot of time.
Data Monitoring
DIP helps to proactively test the data by ensuring that the data is of quality and appropriate for all purposes. It helps to measure and track your data trust index score using dashboards and reports where users can define the dimensional weightage according to the business requirement.
Data Cleansing
DIP helps in cleansing data within a selected data asset , either by removing or updating the information that is incomplete, inaccurate, improperly formatted, duplicated, or irrelevant through step by step process. Data cleansing usually involves cleaning up data assembled in one area.
On-Premise or Cloud Deployment
Manage the quality of multi-cloud and on- premises data for all use cases and for all workloads. DIP is flexible with any source of data; can work with any type of Database (MS SQL, MariaDB), Files etc.
APPROACH
01
Define
Business Terms & Sources should be created and defined based on business goals and requirements. These are the business/technical requirements that must comply with to be considered viable sources.
02
Discover
03
Design
Design what data should contain. “Quality rules” should be created and defined based on business goals and requirements with which data must comply to be considered viable.
04
Execute
Apply injection and execution. Embed the Data Quality services and business rules monitoring into your operational systems& Data Integrity processes.
05
Evaluate
06
Control
Data remediation is the performance of a “root cause” examination to determine why, where, and how the data defect originated. Update and improve systems and processes.
BENEFITS
Improved
ROI
Having high data quality standards and using validated data, businesses can take fast and correct decisions, increasing their overall outcome.
Reduced
Cost
Having high data quality standards enables organizations to operate more efficiently, leading to higher cost of project completions and fewer costs.
Less Time
Spent
Reconciling data Pre-defined automated rules help organizations work more effectively with less time and effort.
Regulatory
Consideration
With the ever-changing regulations, it is important for data to be of good quality.
Increased
Trust
Good data quality ensures trust in data analysis and decision making, which increases confidence in the organization’s analytical decisions.
Optimize
Decision-Making
Data Monitoring helps effective decision-making for your sales, customer services, manufacturing etc.
Data
Analysis
Data monitoring enables you to collect and assess feedback before it has a chance to harm your business.
Identify
Unauthorized Data
Monitoring all data transfer from the company helps to prevent any unauthorized data transfer by identifying it quickly.
Data
Reconciliation
Data Reconciliation Pre-defined automated rules help organizations work more efficiently and effectively Reconcile
data.
CASE STUDY
Customer
- Customer of a leading Indonesian Bank.
Use Case
- Identifying the Unique Customer Reference from multiple sources for Regulatory and MIS purposes.
Business Challenge
- Automate multiple source data processing using a single platform.
- Ability to process the data conversion accurately during the 2011 migration.
- Managing future data processing in a robust and faster way.
Project Requirements
- Create process to validate existing KTP or NPWP.
- Robust validation on information i.e., Province, City, DOB, Gender, etc.
- Assessing the quality of data captured in individual attributes i.e., Name, address, gender, DOB, POB, marital status, NPWP, Driver's license and Passport.
- Knowing the trust index score for the data conversion during the 2011 migration.
Solution Highlights
- Created an automated process to integrate the data collected from multiple sources.
- Managing the Data Quality requirements for the selected attributes in Data Asset through the standard validation rules.
- Build an audit and logging functionalities.
- Assessing the quality of data by generating the trust index score and the reports.
- Architecture to support feeding the single CIF back into the source system, so that further transactions can be initiated without any confusion.
- Secondary checks with other Government databases like PEFINDO.
- Periodic review of KYC for customers based on Risk categorization of the customer (High , Medium, Low) – 6 months, 12 months and 24 months once, through internet banking/mobile banking, mailers.
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 Dashboard and reports updated in Data Governance Metrics.
- Over 90% improvement in Data Quality.
- 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.
