Kaizentric is a Data Analytics firm, based in Chennai, India. Statistical Analysis is performed on a well-built client specific data warehouse, supported by Data Mining.
4. Experience in Data Warehousing Technology focus Project Duration Data Warehouse Photons – Insurance Data Warehouse 7 months Data Warehouse Hornet – HR Repository 12 months Data Warehouse Group Benefits Insurance 9 months Data Integration Marketing and Sales Linkage 4 months Data Warehousing and Data Mining Mortgage Backed Securities 6 months Data Integration Services Data Integration Center of Excellence 2 years Data Warehousing and Data Mining Be InformEd – Education Industry 4 months
8. Photons – Architecture Data Standardization Source Staging Area Oracle DWH Interfaces & BI reports Data Sources Identification Data Mapping Data Validation Data Unification components Code Admin for Data Consolidation ACORD Data Standard Rectify data errors and enrich data Data Audit, Data Quality definition Implement business rules for data integrity, validation rules for cleansing, transformation rules for formatting and consolidation Physical Components Process Components DWH Staging Area Data Sources OpCo POS EDI Sibel Master Data
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10. Hornet – Architecture Data Standardization Source Staging Area Oracle DWH Jobs vs. Candidates Reports Data Sources Identification Data Mapping Data Validation Data Unification components Code Admin for Data Consolidation Data Sources Rectify data errors and enrich data Data Audit, Data Quality definition Implement business rules for data integrity, validation rules for cleansing, transformation rules for formatting and consolidation Physical Components Process Components DWH Staging Area Reports Pdf Flat files documents Hotlists Emails
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12. Insurance – High level Design Source A Source B Source C Maps Mart Kalido iStage Stage Maps Spreadsheets Maps Access Databases The Enterprise Logical Data Model will not be built in a single effort; instead projects requiring data will incrementally contribute to its build out The logical data model allows users to locate which systems contain particular data entities. It also has attribute mappings that allow a user to know which tables and attributes in the sources map to the enterprise logical data model; the mapping would reference all sources that have that type of data. In addition, the system of record would be identified for each type (and possibly segment) of data. The logical data model allows users to know if data elements are in the data warehouse and where in the environment they are located Other business owned data sources (such as spreadsheets and access databases) will also be mapped to the enterprise data model. This will give the organization a better understanding of data that is not part of the application portfolio or where duplicate data is being stored by the business. Enterprise Logical Data Model First Name Last Name Street Address City Phone Number Date of Birth Social Security Age Employer First Name Last Name Phone Number Street Address Date of Birth City Social Security Age Employer First Name Last Name Phone Number Street Address Date of Birth City Social Security Age Employer
20. Be InformEd– Architecture Data Standardization Source Staging Area Oracle DWH Interfaces & BI reports Data Sources Identification Data Mapping Data Validation Data Unification components Code Admin for Data Consolidation Educational Institute Rectify data errors and enrich data Data Audit, Data Quality definition Implement business rules for data integrity, validation rules for cleansing, transformation rules for formatting and consolidation Physical Components Process Components DWH Staging Area Kaizentric’s location Data Sources Student Staff Marks Attendance Others
22. For clarifications, please contact Azhagarasan Annadorai Kaizentric Technologies Pvt Ltd +91-90947-98789 azhagarasan@kaizentric.com www.kaizentric.com Thank you Head office: New #126, Old#329, Arcot Road, Kodambakkam, Chennai 600 024 India Phone: +91-44-64990787