Cookies help us display personalized product recommendations and ensure you have great shopping experience.

We use cookies, including third-party cookies from Google to serve personalized ads through AdSense, to operate this site and understand how it is used. By continuing to browse, you accept this use. See our Privacy Policy and Terms of Use for details, including how to opt out of personalized advertising.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    chatgpt image jul 21, 2026, 04 34 30 pm
    4 Core Benefits of Predictive Maintenance after Vibration Analysis
    10 Min Read
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results -- AI-generated illustration
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results
    11 Min Read
    chatgpt image jul 13, 2026, 04 23 45 pm
    How Data Analytics Helps Companies Improve User Engagement
    19 Min Read
    chatgpt image jul 13, 2026, 03 59 46 pm
    How Data Analytics Improves Multi-Location Search Strategies
    10 Min Read
    cybersecurity efforts
    How Behavioral Analytics and AI Are Redefining Cybersecurity for Boca Raton Businesses
    14 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Blurring the Line Between SOA and BI
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Business Intelligence > Blurring the Line Between SOA and BI
Business Intelligence

Blurring the Line Between SOA and BI

EvanLevy
EvanLevy
5 Min Read
SHARE
Toolbox_01

photo by Siomuzzz

I recently read with interest an article in the Microsoft Architect Journal on so-called Service-Oriented Business Intelligence or, as the article’s authors call it, “SoBI.” The article was well-intentioned but confusing. What it confirmed to me is that plenty of experienced IT professionals are struggling to reconcile Service Oriented Architecture (SOA) concepts with business intelligence.

SOA is certainly a valuable tool in the architecture and development toolbox; however, I think it’s only fair to keep SOA in perspective.  It’s an evolutionary  technology  in IT that has numerous benefits to developer productivity and application connectivity.  I’m not sure that injecting SOA into a data warehouse environment or framework will do anything more than freshen a few low-level building blocks that have been neglected in some data warehouse environments.  I’m certainly not challenging the value of SOA; I’m just trying to put in perspective to those folks that are focused on data warehouse and business intelligence activities.

The idea around SOA is to create services (or functions, procedures, etc.) that can be used by other systems.  The idea is simple: build once, …

More Read

Image
Assisted Insight: The Future of Data Discovery
Is Performance Management Pushed or Postponed in an Ailing Economy?
Automated Valuation Models
Integrating customer preferences
Analytics Moves To The Core: Reporting from the Gartner Summit

Toolbox_01

photo by Siomuzzz

I recently read with interest an article in the Microsoft Architect Journal on so-called Service-Oriented Business Intelligence or, as the article’s authors call it, “SoBI.” The article was well-intentioned but confusing. What it confirmed to me is that plenty of experienced IT professionals are struggling to reconcile Service Oriented Architecture (SOA) concepts with business intelligence.

SOA is certainly a valuable tool in the architecture and development toolbox; however, I think it’s only fair to keep SOA in perspective.  It’s an evolutionary  technology  in IT that has numerous benefits to developer productivity and application connectivity.  I’m not sure that injecting SOA into a data warehouse environment or framework will do anything more than freshen a few low-level building blocks that have been neglected in some data warehouse environments.  I’m certainly not challenging the value of SOA; I’m just trying to put in perspective to those folks that are focused on data warehouse and business intelligence activities.

The idea around SOA is to create services (or functions, procedures, etc.) that can be used by other systems.  The idea is simple: build once, use many times.  This ensures that important (and possibly complicated) application processes can be used by numerous disparate applications. It’s like an application processing supply chain:  let the most efficient resource build a service and provide to everyone else for use.   SOA provides a framework for allowing multiple applications access to common, well-defined services.  These services can contain code and/or data.  

The question for most data warehouse environment’s isn’t whether SOA can improve (or benefit) the data warehouse; it’s understanding how SOA can benefit a data warehouse. 

We’ve got lots of clients leveraging SOA to support their data warehouse.  They’ve learned they can leverage SOA techniques and coding to deliver standardized data cleansing and data validation to a range of business applications.  They have also upgraded the operational system data extraction code to leverage SOA which allowed other application systems (or data marts) to reuse their code.

However, their use of the SOA hasn’t been focused on enhancing the data warehouse environment as much as has been focused on packaging their development efforts for others to use.  Most data warehouse developers invest heavily in navigating IT’s labyrinth of operational systems and application data in order to identify, cleanse, and load data into their warehouses.  What they’ve learned is that for every new ETL script, there are probably 20 other systems that have to custom developed their own data retrieval code and never documented it.  The value that many data warehouse developers find with SOA isn’t that they are improving their data warehouse;  they’re just addressing the limitations of the application systems.

Link to original post

TAGGED:bisoa
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Best Age Estimation Software in 2026: Which Facial Age Providers Actually Hold Up -- AI-generated illustration
Best Age Estimation Software in 2026: Which Facial Age Providers Actually Hold Up
Artificial Intelligence Exclusive Machine Learning
Top 8 Multi-Cloud Architecture Tools for Automated Infrastructure Design in 2026 -- AI-generated illustration
Top 8 Multi-Cloud Architecture Tools for Automated Infrastructure Design in 2026
Cloud Computing Exclusive IT
6 Top Agentic SDLC Platforms for Enterprise Engineering Organizations -- AI-generated illustration
6 Top Agentic SDLC Platforms for Enterprise Engineering Organizations
Artificial Intelligence Exclusive
6 Best Runtime Intelligence Tools for Debugging AI-Generated Code in 2026 -- AI-generated illustration
6 Best Runtime Intelligence Tools for Debugging AI-Generated Code in 2026
Artificial Intelligence Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

The Register’s take on Microsoft and Oracle / Sun

5 Min Read

Next query: NoSQL and Business Intelligence

7 Min Read

The Road to Operational Analytics

6 Min Read

Facts not fears, confidence not certainty, critical thinking not wishful thinking

5 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

giveaway chatbots
How To Get An Award Winning Giveaway Bot
Big Data Chatbots Exclusive
AI and chatbots
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-26 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?