Having touched on the virtues of data mashups in several other articles, it seemed only logical to take a closer look at this key BI technology. Particularly since there has been an increase in the adoption of data mashups as businesses demand more flexible and affordable BI solutions. The term data mashup has been used in the BI industry to describe applications that combine, integrate or aggregate heterogeneous data sources providing new and improved results.
What is Data Mashup?
Clarkson and Holmes in The Architecture Journal define data mashup as the technique for building applications that combine data from multiple sources to create an integrated experience.
What that really translates to is the ability for business users to access and merge data on the fly themselves, as and when they need it. They don’t need to rely on IT. And IT don’t need to build complex and expensive data warehouses, data marts, or ETL processes.
What is particularly interesting about data mashup is the fact that it enables the integration of not only internal data sources but also external data sources. To this end, many data mashup applications tend to be web-based giving businesses an unmatched advantage in accessing and integrating a wide spectrum of data from the web with internal data sources. With the aid of data mashups businesses can analyse not only internal variables but also external ones.
There is ongoing innovation in the BI industry, as businesses demand more intelligent, scalable BI solutions capable of achieving flexibility and optimised performance. In response, data mashup applications have started to emerge which address many of these demands ahead of other models of data integration. There has also been a push to make BI solutions more user-friendly and more of a focus on self-service BI. Earlier BI models were rife with complexity creating a significant demand on IT to manage dashboards, reports, cubes and other analytical tools and to generate results. This issue has also been addressed with BI solutions, such as InetSoft Style Intelligence, that use data mashups giving users a wide scope for experimenting and integrating data sources to test and achieve desired results reducing the demand for IT support.
Advantages of Data Mashups
- Data mashups have a higher rate of delivering a successful BI implementation due to higher end-user satisfaction and user adoption.
- Data mashups deliver business results quicker.
- Data mashups enable faster, better decisions by putting business users in control of designing a solution that is fit for purpose.
- Data mashups have a lower cost of ownership since it vastly reduces the need for expensive hardware and expensive IT resource.
- Data mashups facilitate self-service BI by empowering users to experiment with information and find new ways to achieve the best results.
- Data mashups enable users to leverage just-in-time, quick and easy solutions making mashups an agile BI solution.
There are a myriad of benefits that can be derived from using data mashups and our list could go on. But hopefully that gives you the gist for now…
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