Address the following: Discuss the pros and cons of various data exchange design options. What best practices do you feel are the most important with regard to data exchange design options? Explain in detail. What significant challenges have you encountered? How did you overcome these challenges? Solution Pros and cons of different data design options: XML: Pros: Readable and editable by developer. Error checking by means of Schema and DTDs. Can represent complex hierarchies of data CONS: Bulky text with low payload/formatting ratio. Both creation and client side parsing are CPU intensive. Some common word processing characters are illegal Json: PROS: Readable and editable by developers. Plenty of JavaScript developers. Highly developed browser toolkits such as Dojo and jQuery CONS: Bulky text with low payload/formatting ratio, but not as bad as XML. Client CPU time required to parse. Not as flexible as XML for some data structures and binary data Plain text: PROS: Readable and editable by developers. Fairly compact representation for simple types. CONS: Possible confusion introduced by punctuation in values. Limited to very simple structures 2. The most important best practices to data exchange design options are: - The basic challenges that are encountered during data design exchange are: IP confidentiality, Diverse application land scape, Business process differences, Role in partnership. To overcome these challenges what we have to do is: Although many OEM\'s are entering into partnership to take advantages of technologies or innovations devoleped by other partners. OEM;s dont want to loose the compititive advantages of new innovations with data sharing outside the organization or department, demand for confidentiality of respective intellectual property is at highest level. - Manufacturing organizations have evolved diverse and complex product devolepment methodologies which are unique to each organization different set of authoring tools among partners add to the complexity data exchange this stress needs for standerdization data exchange processes key for effective collaberation. .

1. Address the following:
Discuss the pros and cons of various data exchange design options.
What best practices do you feel are the most important with regard to data exchange design
options? Explain in detail.
What significant challenges have you encountered?
How did you overcome these challenges?
Solution
Pros and cons of different data design options:
XML: Pros:
Readable and editable by developer. Error checking by means of Schema and DTDs. Can
represent complex hierarchies of data
CONS:
Bulky text with low payload/formatting ratio. Both creation and client side parsing are CPU
intensive. Some common word processing characters are illegal
Json:
PROS: Readable and editable by developers. Plenty of JavaScript developers. Highly developed
browser toolkits such as Dojo and jQuery
CONS: Bulky text with low payload/formatting ratio, but not as bad as XML. Client CPU time
required to parse. Not as flexible as XML for some data structures and binary data
Plain text:
PROS: Readable and editable by developers. Fairly compact representation for simple types.

2. CONS: Possible confusion introduced by punctuation in values. Limited to very simple
structures
2. The most important best practices to data exchange design options are:
- The basic challenges that are encountered during data design exchange are:
IP confidentiality, Diverse application land scape, Business process differences, Role in
partnership.
To overcome these challenges what we have to do is:
Although many OEM's are entering into partnership to take advantages of technologies or
innovations devoleped by other partners. OEM;s dont want to loose the compititive advantages
of new innovations with data sharing outside the organization or department, demand for
confidentiality of respective intellectual property is at highest level.
- Manufacturing organizations have evolved diverse and complex product devolepment
methodologies which are unique to each organization different set of authoring tools among
partners add to the complexity data exchange this stress needs for standerdization data exchange
processes key for effective collaberation.