Master Data Management

 
 
 
 
Supplier Data Management
Customer Data Management
Spend Analysis
Environmental Compliance
Data Digitization Services
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  Data Cleansing

Data cleansing is also referred to as data scrubbing. This is the basic and initial step of the Master Data Management (MDM) process flow. The rapid growth of e-commerce has increased the integration of multiple databases for which data cleansing is the must to ensure that the data in each database is standard, consistent and accurate to eliminate the errors.

It is the act of amending the data from the database by detecting and correcting corrupt or inaccurate data which is improperly formatted, incomplete, incorrect or duplicated. Usually data is held with duplicates and irrelevant data which should be eliminated by data cleansing.
 

"Bad Data lead to Bad Decisions"

 

Data Cleansing Process involves:

Data Analysis : It is the process of analyzing the data by experts to identify the content, structure and the quality of the data.
Data De-duplication : It is the process of removing redundant data. Here duplicate data is deleted, leaving only one unique copy of the data to be stored. This improves data protection, increases the speed of service and reduces the over all costs.
Data Standardization : It is a crucial process where the data is defined, formatted, represented and structured in all data layers. Development of schema or attributes is involved in this process. Data standardization helps in achieving better results in further steps down the road.
Data Normalization : It is the systematic process to ensure the data structure is suitable or serves the purpose. Here the undesirable characteristics of the data are eliminated or updated to improve the consistency and the quality. The goal of this process is to reduce redundancy, inaccuracy and  to organize the data.
Quality Check : QC is done to reconfirm the accuracy of data in all stages and at the end of the process by data experts

Maintaining clean integrated historical, data is the best way to cut down the cost and is the most cost-effective method of database management.

Benefits of Data Cleansing:

Reduced duplicates
Improved data quality and accuracy
Improved operational efficiency & reduced hurdles
Reduced risks, costs and turnaround
Enables trend analysis and benchmarking
Improved data security and accessibility

Standards for the data can be set according to the client’s requirements or according to NisargaSoft’s standards.

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