Java IoT Authors: Liz McMillan, Pat Romanski, William Schmarzo, Yeshim Deniz, Elizabeth White


Effective Server Side Data Mashups In Enterprise Clouds - Windows Azure Appfabric Proposition

Data Mashups & Slowly Changing Dimensions

Mashups are  new concept in web 2.0 where by  the web User interface combine data from multiple sources to build new views that show information in new ways. Mashups can take different forms. As a cloud provider or an enterprise who deploys applications on Cloud, you may  have to provide mashups to end users by combining business data from different sources into a unified interface.  These include data from external, internal, public sources.

Mashups & SQL Joins :

Traditionally in relational database JOINs (INNER JOIN, OUTER JOIN, SELF JOIN) are utilized to join data from multiple subjects and provide multiple views to the end user. However there are many ways Mashups provide more flexibility than traditional JOINS.

·         Data need not be aggregated to one place. Traditional SQL JOIN require that data is ETL (Extracted, Transformed, Loaded) from multiple sources to target. But the new way of content generation mandate that the needs for data integration are unknown till the run time and these situational applications have to modify them selves  dynamically.

·         Traditional SQL JOIN works well between the same database but requires lot of cost and licensing for multi database support. If we need to Join Oracle to DB2 or vice versa then we may have to purchase the expensive gateway products from respective vendors.

·         Traditional SQL JOIN assumes that the provider enterprise owns all the data, however the Mashups inherently provide for data integration between providers both internal and external.

·         Traditional SQL JOIN works well for relational data where as Mashups are for both relational as well for unstructured content.

The below diagram gives a view of the Mashups in a typical enterprise where the data integration needs are from very many disparate sources.

It is evident that Data Mashup plays a vital role in providing a richer set of intelligence to your business process and improves the QoS of your cloud services.

Key Success Factors For a Successful Data Mashup :

·        Keep Control Of Your Dimensional Attributes that require for Mashing Up with external engines : As evident  unlike a traditional RDBMS / Data Mart applications where the enterprise has got all the control of data, in Cloud data mashup only half of  the data is under the organization’s control and rest are from external sources. For example depending on the Customer’s  Geography your application need to provide the near by service centers, then keeping the zip code as part of your  enterprise data and linking it with external feeds based on the Zipcode as a key is important.


·         Aware of the Slowly Changing Dimensions and ensure the validity of data to near 100% :    While much of the success of your business depends on mashing up the data from multiple internal and external sources in a cloud enabled enterprise,  but due to dynamic nature of the  dimensional data you may end up with old data too frequent unless there are measures to keep track of it  using multiple means. For example assuming that much of the  mashup strategy depends on the customer’s drive location for example the customer’s  work location zip code, so that lot of marketing materials can be targeted towards that location and assume that customer has changed his work location and this information is not kept current, this may result in unnecessary or redundant information to the customer  and may result in loss of business. This concept  traditionally known as ‘Slowly Changing Dimension’  (Dimension  is some thing that describes the attributes of key business parameters – Customer, Product, Region, Date/Time are typically some of the Dimensions). There are multiple types of changes and each of these SCD (slow changing dimensions) can be tackled appropriately as per the Mashup strategy.


o   Type 1  SCD :   In this type the  new data replaces the old data. For example  some Address information can be considered as Type 1  where by once the customer moves his location we can change his Zip code too so that newer data mashups will represent the customer’s current location.

o   Type 2/3 SCD :  Both are slight variations, but basically here even if the dimension information changes both the old and new information kept to make your mashups even more useful. For example  you keep track of your customer’s interest and show relevant information  on your mashup strategy.

§  Assuming that the current interest  of the customer is about  Music  then you show relevant musical CDs or other Concert related information for the customer

§  Assuming that your customer profile is updated with an added interest of  Major League Base Ball, it does not mean that your mash strategy should  replace the music related feeds rather it can augment with MLB related feeds like Scores, game information etc…

·         Aware of Performance Related Issues with respect to Linking data  :    The information  like explained above  (zip code…) are the key to the linking strategy to the rest of the external feeds. And the key has to be most appropriate for the situation to bring the most relevant information  that is meaningful to the customer in a shortest possible time. For example if there a Mashup with a Weather feed it is more appropriate to  link with zipcode than with state code.


Windows Azure Appfabric

Windows Azure AppFabric provides a comprehensive cloud middleware platform for developing, deploying and managing applications on the Windows Azure Platform. It delivers additional developer productivity adding in higher-level Platform-as-a-Service (PaaS) capabilities on top of the familiar Windows Azure application model.

It also enables bridging your existing applications to the cloud through secure connectivity across network and geographic boundaries, and by providing a consistent development model for both Windows Azure and Windows Server.

You can refer to Microsoft  Vendor site documentation about detailed explanation on Azure stack of products especially for data mashup scenarios. 


Using a proper selection of tools  and appropriate strategy will provide the basis for your organization’s ability to build effective situational applications.  Once the data strategy for the Mashups are clearly defined the user interface can be built on top of it using the appropriate WIDGETS available as part of various platforms.


More Stories By Srinivasan Sundara Rajan

Highly passionate about utilizing Digital Technologies to enable next generation enterprise. Believes in enterprise transformation through the Natives (Cloud Native & Mobile Native).

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