Jan 2009

Leading Retailer hire Provish
services for Modelling and re-architecting its Customer Data Mart
   
Data Quality
Poor data quality is detrimental to any growing organization’s top-line as well as bottom-lines. Critical decisions rely on the quality of the information supplied to make them and can cost a lot if the supporting information is incorrect. Similarly, compliance and regulatory requirements driving organization’s information needs will dictate zero-tolerance in quality of key areas. Plethora of information sources within an organization and lack of integration amongst them make better data quality even more difficult to attain than it seems.Our data quality solutions encompass all the phases of data quality, namely :
  • Data Profiling and Quality Assessment
  • Standardization of data quality rules
  • Matching and De-duping of information
  • Survivorship rules to enrich data quality
CDI/MDM
Many organizations face the mammoth challenge of reconciling master data like customers, products, employees, suppliers etc. As these key data elements originate, reside and utilized in multiple systems managed by disparate business/functional groups, these elements are often found duplicated, unclear and partially correct. Growing phenomena of mergers and acquisitions as well as globalization make this master data management even more difficult. However, organizations relying on accuracy of these elements for their vital business decisions can not afford to take passive approach for managing master data.

Provish team has expertise in leading and maturing technologies used for MDM (Master Data Management) as well as CDI (Customer Data Integration). Customer data being the most valued of all master data, customer data integration usually gets more attention and priority. Our team has been exposed to various areas of CDI/MDM and engagements implementing these solutions not only as a system of reference but as a central system of records in real-time. While leading technologies are still evolving for these solutions, it takes more than technologies to address CDI/MDM issues as they are evolving and depending on organization’s business processes and distributed functional ownership of the key data. Our solutions focus on analyzing this business processes and practices and we insist on partnering with various business owner groups in order to make these solutions effective.

Metadata Management
With numerous systems generating and consuming identical or overlapping information, it is imperative to understand what each piece of information means. Even the key information elements may seem similar when they are used across enterprise by different groups, but they may be interpreted totally different depending on the audience and the context where they are used. Functional interpretation of same data elements can be drastically different too. Management strategy to identify and standardize the “data about data” (referred to as metadata) is crucial to establish harmonious interpretation and avoid confusion at enterprise level.

Metadata management strategy can be expanded to operational/tactical metadata beyond functional metadata. In Data warehousing context, Metadata Management strategy is essential for ETL metadata and BI Metadata and the maximum value will be ripped by business users if they can trace back every data element from presentation layer back to source systems.

However, implementing such comprehensive sounds easier said than done. Founding metadata management strategy poses many other non-technical challenges about ownership, definition responsibility and custodianship of each metadata area.  Provish team can help your organization in navigating these challenges and assist in laying the foundation for enterprise-wide metadata management strategy.
Data Integration/ETL
Leveraging data scattered into disparate applications within organization is critical for successful business intelligence solution. Gathering various data points from different systems or processes and unify them to provide one version of the truth is the biggest challenge today’s organizations facing.

Our Extract Transform and Load (ETL) engagements provide strategic and operation direction to address these challenges. With growing information collection and reporting needs of organizations, data sources are becoming complex and massive with each passing day.

Analyzing complexities in various source systems or in integrating them is starting point for our ETL/Data integration solution assessments. Our solutions leverage cutting edge technologies to architect best of breed ETL/Data integration solutions. They are able to scale up to very high level of volumes without significant changes. We strive to make them efficient, scalable, easy-to-enhance for future needs and easy to support. 

Data Governance/Stewardship
Coming soon...
 

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