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2.0 Grid Grid
Computing is a way of organizing computing resources in such a way that they are flexible, easy to access and useful in many other ways as well for users. The objective of Grid computing is to make resources available so they can be more efficiently utilized. The original purpose behind Grid computing was to link together supercomputers spread across wide distances, but the aims have since moved beyond this scope. There are many organizations, which are efficiently maintaining data grid for the help of users. The main core of these organizations is to provide the ease to the users while they are using any sort of data for any purpose. There are some predefined standard for grid. The data grid is a good example of an interoperable system. Many Grid implementations are oriented toward supplying specific types of resources. Grids can be categorized according to these resources. The most common types of Grids are Computational Grids, Data Grids, and Application Grids. There are many data grid which are currently serving a lot number of users across the world e.g. NASA Information Power Grid, AstroGrid, European Data Grid etc.Grid can be divided into two main categories the way it store data: Structured Grid Structured grids we always know which neighbors will be around any grid point. Unstructured Grid For unstructured grids the neighboring points are not immediately available.

2.1 Data Grid
The data grid emphasizes its role as a specialization and extension of the Grid that has emerged as an integrating infrastructure for distributed computation. Data grid is a subset of grid, whose basic goal is to give an integrated infrastructure for distributed computing. Access to distributed data is typically as important as access to distributed computational resources. Term Data Grid is used for different purposes: Data Grid terms for a virtual data grid The automation of the execution of processes is managed in virtual data grids Data Grid terms for a distributed resilient scalable architecture Federated server architecture refers to the ability of distributed servers to talk among themselves without having to communicate through the initiating client Data Grid terms for an information repository abstraction

It is a software system that is used to control combinations of semantic tags and the associated value of data attributes. Data Grid terms for a storage repository abstraction It is a storage system that holds digital entities Data Grid terms for a logical name space

It is a naming convention for grouping digital entities [Moore,R.W.,merzky,A., 2002]. XML is really worked hard to catch the most of capabilities that are require for distributing computing but it still have a lot of room left for improvement in these fields. XML cope well with data integration, data interoperability and grid problems. Grid is very important for heterogeneous computing.

3.0 Data Integration
The most important and recurring problem that XML able to solve is middle tire data integration. This problem is difficult for several reasons. Data coming from different sources can have different formats, and if the application code is exposed directly to these different formats. It is bad enough that a single application has to have code to handle the multiple formats [Reaz Hoque2000]. It plays a very important role in the management of heterogeneous databases. There are many different ways to integrate the individual databases. One is known as system overhaul technique in which a new system is created that consolidate the existing systems into one system. This option can be costly in some cases. The federation technique allows users to choose from the variety of individual database schemas. The composite technique, the mediated technique, the cover up technique, and the data warehousing technique the goal of all these and many more that may come with the passage of time is and will be, the technique should be affordable, quick and easy to handled and that does not require a large amount of investment of capital and other related resources when integrating databases. XML adopt the composite technique, the method of working of this technique is it creates a virtual data warehouse, which provides the feel of single repository, and it also allows data to remain in its natural distributing settings. XML enables intelligent client side processing; it also has the ability to change presentation of data dynamically without unwieldy and time consuming interaction with server. On middle tire XML ideally suited to address the many of persistent data integration problems that infect the enterprise application. And XML is also very good with data storage and retrieval medium.

4.0 Data Interoperability
There are many definitions available for interoperability. Many group of people look at it in different way. Ability of a system to use the parts or equipment of another system [Loesgen Dictionary 2000] or It is ability to transfer data products between different types of storage systems or share the data across different users or networks. But its function does not change with the change of word in its definition. One of the most important and fundamental feature required for distributed computing in heterogeneous environment. It gives a meaningful way for the presentation of data, and also gives permission to distribute it. XML allow data to be shared across the web not only within local network but also across the networks of the networks in a quite easy way just by giving meaningful structure to the data. It is platform independent and application independent and is well capable of mediating interactions between various Grid components. Types of interoperability Supporting multiple devices Enterprise: Inter application Inter process Inter departmental Inter enterprise

Here are some major achievements of XML in term of interoperability. XML Interoperability to talk to multiple devices. Its uses SOAP to implement a pub/sub message monitor. The BizTalk initiative and how they combine to facilitate XML interchange.

Conclusion
Although XML was initially envisioned as simply a replacement for HTML, but its impact is turning out to be far grater than that. By giving a healthy affect on the client-tire, the middle-tire, and the backend-tire. It handles every tire very well that is a big plus point of XML. Different other programming languages are using XML now days due to its open end structure. Compared to the object-oriented one, the relational model is not the most appropriate for storing XML data. The only reason is when it just stores XML data then it convert into plain text, so many thing wrong can happened with it, like relations. Technology shows that there are many interesting problems concerned with the use of XML and databases together. The described use of XML and its associated technologies in databases and its importance in data warehousing, we just can not ignore XML's importance, the only thing which is needed that the future work of XML may make it, a complete data model and the work with other technologies. We can take it as semi structure data, which use Object Exchange Model for data modeling. This model actually used for semi-structure data models and use different approaches to make its use in DBMS. Using XML source for feeding data warehouse systems will become a standard in the next few years. Much of work has been done and still in progress by different people and organizations to make a maximum use of XML with other technologies. XML is brought many changes as compare to HTML; it is really flexible and extensible markup language. In the end I would like to say that XML is flourishing day by day and its use is incredibly increased during last years, because of its flexibility and extensibility. XML real deal well with the issue of data integration, interoperability and grid computing though it is not perfect in these field but progress is still continuous. For more topic on related field click ecommerce software solution
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