Master Data Management
Master Data Management
In this digital era, data is one of the most significant assets for any business. The increasing volume of data in the past few years has made it difficult for companies to manage data efficiently. As companies aim to utilize their data optimally, master data management has become their prime focus.
Master Data Management (MDM) deals with the challenges and opportunities related to unstructured, user-generated, and Machine-generated data.
FEATURES
Data Model
Establish the data model by defining attributes, setting up enumeration, defining the model (foreign key-related information), and setting default values to the attributes wherever applicable.
Data Enrichment
Mass Processing
Mass updating the same value for multiple records either by giving the value or by writing SQL queries.
Matching and Merging
Measuring and Monitoring DQ
APPROACH
01
Profiling Master Data
DIP helps in profiling the data for each master data business entry and it is to be managed centrally in a master data repository. The preferred data quality rules must be analyzed by highlighting the key areas of data discrepancy to estimate the business impact.
02
Consolidating Data Migration
Consolidation is a key aspect of managing master data. Fusing master data from various siloed heterogeneous IT environments is the customer’s main objective. AMURTA Data Insights Platform provides Data quality services to standardize, cleanse, and match master data attributes during the MDM processes.
03
Cleanse and Govern
Post consolidation of the Master data can be cleansed and governed where cleansing involves standardizing, error correction, matching, de-duplication, and augmentation of the data where governing involves data definition, data quality rules, definition, privacy and regulatory policies, auditing, and access controls.
04
Collaborate
The ability to integrate and synchronize master data information with existing systems, enterprise applications, repositories, and masters.
05
Leverage
MDM creates a single version of the truth about every master data entity. This data has all operational and analytical systems across the enterprise. The key insights will have gleaned from the master data for effective decision making.
BENEFITS
Improved
ROI
Having high data quality standards and using validated data, businesses can take fast and correct decisions, increasing their overall performance.
Better Customer
Experience
Cohesive customer experience is gained by a better understanding of customers and their needs by viewing their Historical Data.
De-Duplicated
Master Data
Can automatically detect duplicate records quickly and create a “golden record” for your key master data objects.
Cost
Reduction
MDM implementation protects your operations, processes, and information. This can reduce the cost up to 40%
Fast-Track Your
Business Processes
By placing data in one central location and Integrating business data, you can speed up processes and increase efficiency and cut down on wait times.
Informed
Decision-Making
With one Central Data repository, it is easy to extract, analyze the data, and make well-informed decisions.
Better Data
Compliance
MDM application decreases the chances of security breaches and regulatory non-compliance.
Faster Turn
Around
MDM solutions not only automate the process of obtaining error-free data but also saves an enormous amount of time.
CASE STUDY
Customer
- A leading Retail Customer.
Use Case
- Improve the Data Quality and omnichannel experience for their consumers .
Business Challenge
- Automate multiple source data processing using a single platform.
- Need to maintain a single source of truth by matching and merging the duplicate records.
- Managing future data enrichment in a robust and faster way.
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 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 business validation rules.
- Assessing the quality of the data source by generating operational reports.
- Data model to support the feeding source system with require changes as per the business requirement so that further transactions can be initiated without any confusion.
- Easy edit for Master data through MDM data Browser.
- Different data models for various specifications as per business (e.g. Customer, Partner, Sales, etc.)
AMURTA Value
- Supported in managing the operational metrics as per business validation rules.
- Reduced the time taken to view all merged consumers' information as per their corresponding roles with the compilation of multiple source data.
Results
- Key metric information was provided in near real-time to business executives.
- Related operational Dashboard updated.
- Business found the number of consumers with specific consumer role to improve the performance in Sale.
- 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.
