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May 31, 2009
Time to get BASHED UP! - BI greets Mashups
Not many applications become killer-apps in their life-time and neither have Data Mashups become one. But of what I have seen of Data Mashups is enough to get a feel of what killer applications are all about. I, for one, strongly believe that data mashups can have profound impact on the way BI is delivered to business users. Let's explore a bit of bashups (BI Mashups) in this blog.
A "mashup" combines applications or data from different sources (sources not originally intended to be used together) into a single site or page. Content used in mashups are typically obtained from a third party source through a public interface API, web services, RSS or screen scraping. A mashup has 3 components:
a) A Web page that creates the mashup by aggregating data from multiple sources
b) Additional content provider
c) Client / Web Browser
Mashups are not compound pages obtained by simply embedding the content from another page nor is it equivalent to a portal. Mashups must obtain real-time data from 3rd party content providers on the fly.
In the context of BI, Enterprise Data Mashups can be a game-changer in the way information has been disseminated to business users. Traditionally, BI has been delivered by aggregating data into data warehouses and marts that are modeled in specific ways to aid end-user reporting and self-service capabilities. That is, traditional BI is one of tightly coupled information chain. Though this model has served the needs of first-generation BI, this model is not going to be sufficient for future needs. With ever increasing data volumes, real-time requirements imposed by Operational BI, increased sophistication for end-user analytics and the clamor for leveraging unstructured data, it is not going to be practically possible to physically aggregate ALL the enterprise data that is required for business decision making. The future of BI is going to be one of loosely coupled information integration.
Business users have (now and in the future) the necessity to combine data from multiple sources before taking a decision. Though ad-hoc query features provided by BI tools are considered a wonderful improvement to canned reporting, the users have been restricted to view data that is available in data warehouses & marts. Data Mashups provide a way to combine this formal data (present in data repositories) with data that is available outside of this domain (informal data). Informal data can be external data provided by RSS feeds or can be any type of unstructured data like documents and mails. The only thing of importance is the fact that the combination of both formal and informal data adds significant value to the business user. In this dimension, Mashups truly empowers the business user by providing "complete" end-user self-service capability.
Here is some friendly advice to BI practitioners to get started on Mashups:
1) Mashups are closely related to webservices and so it is important for BI practitioners to get a good handle on XML, webservices, SOAP, REST etc.
2) Programmableweb.com is an excellent website that showcases exciting mashups and also provides a catalogue of mashup API's
3) Mashup editors such as Microsoft Popfly, Yahoo!Pipes, Google Mashup editor etc. can help BI practitioners get started in creating their own mashups
4) Mashup servers like Presto (JackBe.com), WSO2 etc. once installed in your environment can help combine information from multiple sources.
5) Create prototypes of BI dashboard type mashups. Mashup that I created recently on Presto mashup server had the following pieces of information on a dashboard kind of web-page:
a) Data from a table in a DW exposed as a web-service
b) Source system information exposed as a web-service
c) Information from a RSS Feed
d) Used the Google Map Mashup API
That should give some idea of the possibilities and power of "Loosely Coupled Information Integration" through Mashups.
Thanks for reading. Please do share your thoughts.
Posted by Karthikeyan Sankaran at 1:30 AM | Comments (2)
May 6, 2009
Ascent of BI - The Five Elements
My inspiration for this post is a book that I recently read titled "Five Equations that Changed the World" by Michael Guillen. This is a fascinating account of the history and people behind what are arguably the most important set of scientific equations that humankind has ever laid its eyes on. The top 5 equations according to the book are:
1) Issac Newton and the Universal Law of Gravity
2) Daniel Bernoulli and the Law of Hydrodynamic pressure
3) Michael Faraday and the Law of Electromagnetic Induction
4) Rudolf Clausius and the Second Law of Thermodynamics
5) Albert Einstein and the Theory of Special Relativity
These 5 fundamental equations have made possible several achievements like electricity, airplanes etc. and more significantly in understanding the nature of life and death.
The world of Business Intelligence has seen rapid strides in the last 10-15 years. In my view, the top 5 reasons for the "Ascent of BI" are:
1) Proliferation of powerful transaction systems (ERP, CRM, SCM etc.)
2) Internet Explosion that created the dissonance between availability & requirement of information and finally solved the problem too.
3) Globalization generated the need to have sophisticated analytical systems for businesses that span multiple geographies
4) Regulatory compliance requirements like SoX, Basel 2, GAAP etc.
5) New Business Models in industries (for example in Financial Services, Telecom etc.) that demands management by metrics
Over and above this, the BI product vendors have shown tremendous visionary zeal in coming up with vast range of BI platforms and tools across the entire BI landscape - be it data integration, databases and reporting tools, that has helped enterprises visualize the power of analytics.
Putting on my predictive hat let me list down the 5 things I think will take BI to the next orbit. They are:
1) Cloud Analytics (Analytics as a service)
2) Analytics that combine structured and unstructured data
3) Deeper Analytical Layer with Predictive capabilities and simulations
4) Real-time analytics (likes of Complex Event Processing (CEP), etc.)
5) Loosely coupled information integration (likes of data mashups etc.)
I will delve into each of these areas in my future posts. Please do share your thoughts. Thanks for reading.
Posted by Karthikeyan Sankaran at 8:45 AM | Comments (0)
