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CRM Data Integration Challenge: Data Quality Web Services, Part 2
Part 1 of this two-part series appeared in the November 29 issue of DM Direct Special Report. Click here to read it.
ASP Features - Business Model
The following facts provide a hint about the growth and business value of the application service provider (ASP) market and also data quality strategy acceptance by enterprises.
Conclusions that can be made from the above facts are:
Outsourcing: In face of data quality professional skill shortage, organizations would be increasingly looking forward for outsourcing, leading to a growth in data quality services market
Application service provider: As shown above, the ASP market is ever growing, as there are more cost pressures ever with in enterprises. The data quality ASP will significantly bring down the cost of data quality investment.
Web services factor: Web services technology come to meet the demand for online integration, especially in case of bridging of the externally hosted data quality solution with CRM infrastructure with in an enterprise
Following points elaborate the cost components associated with the business initiation and sustenance of an ASP providing data quality services:
Challenges contemplated needing careful examination are:
Advantages of the ASP-hosted data quality services compared to an in house implementation are:
There are a few critical risks identified with the proposed ASP business model as listed below.
The two principle features related to ASP's technical function are that it:
1. Hosts, operates and maintains the application software and hardware. It must also include the staffing arrangements for support. This will introduce a possible operation cost sharing across multiple clients.
2. Can provide services to all customers, irrespective of their geographical location.
Potential customer expectations and challenges from a customer relationship management (CRM) data integration point of view, which has to be considered during this technology modeling, would include:
Figure 2 illustrates a high-level ASP setup to provide data quality services:
Figure 2: High-Level ASP Setup
Elaborating on the preceding diagram data quality services essentially should include whatever customers may look for and beyond in their CRM data integration endeavor. A sample enterprise modeled in Figure 2 would be extended to several enterprises, with dedicated processing setups within the ASP to cater to. In effect, the customer name and address data from the client's enterprise CRM applications will be posted through Web services requests to the ASP with special identifiers for the action to be performed on the same. ASP data quality functions will immediately process the same and provide a common de-duplicated reference to the client, which the client application will use for cross-linking.
Data Quality Server - Parsing: A best-of-breed data-cleansing tool can be procured from a number of options available in market, which essentially should be good in parsing, verifying and standardizing the name/address or any other unformatted information.
Data Quality Server - Postal Directories: This setup will be backed up with postal directory databases from various countries and vendor directory integration with selected online vendor directory providers and so forth.
Data Quality Server - Matching Engine: A matching engine generally comes with a data cleansing tool. However, as the main focus remains on linking and deduplication of data, a specialized matching engine can identified and integrated into this function
Data Quality Server - Business Rules Engine: Generic as well as custom business rules will be required for data standardization as well as enrichment for each of the geographies supported. Though this is supported to some extent in available data cleansing tools but a custom-grown database of business rules would be a value add for the clients.
Data Quality Server - Transliteration: Transliteration and/or translation becomes a critical function for processing data in languages worldwide, if the client's data comes in different languages. This is an area slowly gaining attention and would drive technology trends to come up with universal transliteration possibilities soon. Modern day technology has yet to offer considerable capabilities of automated transliteration, which would definitely be a value add for clients requiring that feature.
Data Profiling Tool: A standalone data profiling tool or the one that arrives with the data cleansing tool can be chosen for profiling data, a very important exercise.
Data Consolidation: A database of significant capacity will support each enterprise client for identifying their application data, saving the pre- and postcleaning states of the customer name and address profile records and storing a common identifier for common customer address data for reference. Clients requiring a constant monitor of their data would opt for building the consolidation database with in their enterprise and use only the data quality services of the ASP.
Metrics/Performance Monitoring Server: A server or a utility which would produce reports on data anomalies, data flow and frequency distribution would be a handy tool, which clients can use for review and analysis.
Data Quality Consultation Services: These are normally comprised of online or offline professional interaction for day-to-day data quality issues of different client enterprises that consolidate the solutions and breakthroughs for cross application.
The future of Web services-based data quality ASP will be driven by these two growth factors:
Apart from basic services that ASP needs to begin, a few more can be added later as part of moving up the value chain. The future growth-plan for ASP may consist of the following ventures:
For more information on related topics visit the following related portals...
Business Intelligence (BI), CRM, Data Integration and Outsourcing.
Shadab Hussain is a data warehousing consultant at Wipro Technologies. He holds an MBA from IIITM-Gwalior and a graduate degree in electrical engineering. He has worked in data quality initiatives and data warehouse implementation. His interest areas are data quality, data warehouse design and architecture and data modeling.
Shashidhar Kalwa is a Web technology consultant with Wipro Technologies. He holds bachelor degree in Information sciences and engineering. His interest areas are data quality and web technologies.
Venkatesh Ramakrishnan is a data warehousing consultant at Wipro Technologies. He holds a master degree in science. He has worked in data quality initiatives and data warehouse implementation. His interest areas are data warehouse implementation, databases and data quality.
Mahesh Velapakam is a business intelligence solutions consultant at Wipro Technologies, currently located at Bangalore, India, supporting clients on data warehousing and data quality projects. He a chartered mechanical engineer and has served in different functional and IT areas of high-tech and light engineering manufacturing organizations. His interest areas are databases and business analytics solution design and implementation.