Does your organization have multiple databases with customer information? What happens if during invoicing, different systems have different addresses for the same customer? Without a proper Master Data Management process surrounded by quality Data Governance Standards your organization stands to loose significant time and effort in lost productivity.Implementing a methodology to manage Master Data is crucial as it enables consistent data management. Data governance provides the ability to manage data as well as integrate it with the rest of the business. Tegnosis brings best of breed practices that allows companies to build systems where reference data is understood and used the same way across the enterprise. We ensure that the way data is managed is consistent with the business objectives. Pragmatic data governance ensures error free analytics and reporting.
High Quality Data
Experience what it feels like to be sure that your reference data is always up-to-date.Right Decision Making
Be confident in your decisions because you are assured that the data used to come up with those decisions is accurate.
Single version of the Truth
Carefully defined data usage approach across the enterprise leads to data standards and a reliable source for a single version of the Truth.Future Proof BI Strategy
Accurate master data leads to BI projects that complete much faster than ever before.
Rock Solid Foundation
Your biggest asset – your data, is now guided by consistent principles and procedures.Synchronized constantly
Data is constantly updated and kept in sync across multiple databases and systems.
Efficient operations
With the right master data, your operations are smooth leading to satisfied employees andreduced costs.Sleep Well at Night
No conflicting data means better decision making and peace of mind.What We Offer
- A complete audit of the systems storing various reference data to formulate the best strategy for implementing MDM
- Utilizing Microsoft Master Data Services (MDS) tool to implement processes to manage Master data, create date models, etc.
- Implementing Microsoft Data Quality Services to fix up existing data quality issues and ensure that existing data is reliable.
- Data Cleansing including transforming data to meet standards, flagging outlying values, removing duplicates, updating outdated data elements, etc.
- Instituting a data governance framework to ensure timely and reliable information.
- Identifying and empowering data stewards who take control and ownership of their respective Master Data.
- Tactical project management techniques to produce measurable results.
