Data Integration, Visualization and Analytics VOR 7235


Data Quality Assurance

Larger companies have been facing growing problems with incorrect and/or inconsistent data. Acceptable data quality is crucial to operational and transactional processes and to the reliability of business analytics / business intelligence reporting.

CM Inc. has extensive experience in helping our clients to get the reliability and application efficiency of data, particularly when kept in a data warehouse.

Two of our main Data Quality Tools sources are from Informatica and Oracle, who have been positioned as leaders in Gartner’s Magic Quadrant for many years.

Our DI/DQ tools include Extraction, Transformation and Loading (ETL), Data Profiling, Data Cleansing, Metadata and Master Data Management.

Our Data Quality Assurance (QA) involves the data profiling services, enablement for collaboration between non-IT and IT users, standardization, parsing, identity resolution, and address verification capabilities.

After the data QA process, CM Inc. will use advanced Data Quality Control approaches to control the usage of data to keep it stay clean, providing clients with reliable data for their business analysis and decision-making.

With the help of CM Inc.’s Data Quality services, organizations can identify new opportunities, improve operational efficiency, and more efficiently comply with industry or governmental regulations.

DIVA Data Quality Basic Features

  • a) Data Quality Auditing (DQA)
  • b) Data Quality Assessment Routines and Reporting
  • c) Data Quality Operations as Services via Multiple Protocols
  • d) Data Quality Analytics
  • e) Defining and Collecting Measures of Data Quality Assurance
  • f) Data Extraction, Transformation and Loading (ETL), profiling and reporting of data completeness

Product(s) proposed under this Capability, must also be able to support encryption of data.

Gartner Group Magic Quadran