3. One of the most important tasks in developing an integration strategy is anti

Question

3. One of the most important tasks in developing an integration strategy is anticipating the types of problems you might encounter in accessing, testing, and modifying the data. These problems will differ depending upon the nature of the project and the nature of the data sources and the data target. List the problems that you would anticpiate in the following application scenarios: a. Migrating a 30-year-old application based on COBOL VSAM files to a COTS package based on Oracle’s relational database management system b. Building an information-sharing application that uses XML to consolidation information from the following agencies: transportation, health and human services, and the department of motor vehicles c. Consoldating two billing applications ater a merer or acquisition

Explanation / Answer

1. Please find below the problems faced while migrating Migrating a 30-year-old application based on COBOL VSAM files to a COTS package based on Oracle’s relational database management system :

a. First of all experienced workforce is very hard to find in market for COBOL VSAM files handler.

b. Secondly the functionality used in VSAM files should not be changed in COTS package can be bigger challenge while migrating.

c. Thirdly since data is too old so to find the obselete code can be big problem as that need to scanned line by line and manual scanning is very time consuming resulting into costly project.

d. Lastly manual testing might be needed instead of automation testing requiring large number of testers for huge data so ACCURACY is much concern.

e. Data Safety could be known issue while migration so protection of same needed.

f. Recognizing of semantic inconsistencies.

2. Problems while building information system for Health domain :

The challenges that prevent efficient health information integration using XML (HL7 - XML prototype for health domain)for heterogeneous data sources are the lack of a common standard to support mapping across distributed data sources and the numerous and diverse healthcare domains. Health Level Seven (HL7) is a standards development organization which creates standards, but is itself not the standard. They create the Reference Information Model. RIM is developed by HL7's technical committees. It is a standardized abstract representation of HL7 data across all the domains of health care. In this article, we aim to present a design and a prototype implementation of HL7 v3-RIM mapping for information integration of distributed clinical data sources. The implementation enables the user to retrieve and search information that has been integrated using HL7 v3-RIM technology from disparate health care systems.

Problems while building information system for transportation :

Challenge #1: Addressing Diverse Needs and Finding Common Ground There are a diverse set of data types, sources and data users within the transportation community,which means there is much work to be done and a wide variety of perspectives to consider in defining metadata standards for transportation and furthering their use. The term “metadata” means different things to different people.

The challenge is to map out the transportation metadata territory so that it is clear where the common ground is, and where individual efforts can and should proceed more independently.This is essential for defining a coherent and productive approach to metadata work in transportation and to allow for productive communication across people with different perspectives.

Challenge #2: Getting Agreement on Standards Getting agreement on standards is hard work that must consider variations in methodologies used by different data producers, differences in how commonly used terms (e.g. “trip”) are defined, and Final Metadata Working Group variations in what different data consumers need to know in order to make appropriate use of data. It also needs to recognize practical issues such as the effort to collect metadata, and availability of certain metadata items (particularly for older data sets). Successful development of metadata standards requires several ingredients: people to champion and organize the effort, incentives for participation across the full range of relevant stakeholders, and the knowledge and expertise to navigate the web of existing metadata standards and other relevant data standards (e.g. standard code lists for document formats). There are multiple existing overlapping metadata standards that are under the stewardship of groups including the US Library of Congress, the National Transportation Library, the Federal Geographic Data Committ ee (FGDC), the Inter-University Consortium for Political and Social Research (ICPSR) and various committees within standards organizations such as ASTM, ISO and IEEE. Many of these standards are purposely defined at a general level in order to be flexible and adaptable. Efforts to get agreement on metadata for a specific type of transportation information need to determine which (if any) of these high-level standards to adopt, and then they must develop extensions or applications of these standards to fit the needs of the relevant stakeholder group. Once this is done, the issue of ongoing stewardship and updates for the new or modified standard must be addressed.

Challenge #3: Overcoming Implementation Barriers The final challenge is that even where standards exist, there are a host of barriers to be overcome before data producers will routinely build in metadata that adheres to these standards. Processes for collecting, updating, archiving and quality-checking metadata need to be put into place, which can involve considerable effort. For this to happen, managers need to have sufficient incentives to justify the effort required. Both “carrots” (persuasive value propositions) and “sticks” (metadata requirements imposed by data publishers/distributors) can provide these incentives. On the flip side, metadata standards need to be kept reasonable so that they will not be too arduous to implement. There is also an important education component to implementation – current metadata concepts are not well understood by data users and managers.Good examples are needed to provide easily adapted models. A strategy for piloting high value applications of metadata and then publicizing the results and benefits may be required in order to build support and acceptance.

Problems faced while consolidating two billing applications after their merger :

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