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

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    media monitoring
    Signals In The Noise: Using Media Monitoring To Manage Negative Publicity
    5 Min Read
    data analytics
    How Data Analytics Can Help You Construct A Financial Weather Map
    4 Min Read
    financial analytics
    Financial Analytics Shows The Hidden Cost Of Not Switching Systems
    4 Min Read
    warehouse accidents
    Data Analytics and the Future of Warehouse Safety
    10 Min Read
    stock investing and data analytics
    How Data Analytics Supports Smarter Stock Trading Strategies
    4 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Integrating Big Data and More with Your Data Warehouse
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Data Management > Best Practices > Integrating Big Data and More with Your Data Warehouse
Best PracticesBusiness Intelligence

Integrating Big Data and More with Your Data Warehouse

Barry Devlin
Barry Devlin
4 Min Read
SHARE



AIW.pngIn 1988 I 
published the first data warehouse architecture.  Its aim was to provide consistent, integrated data to business users in support of cross-enterprise decision making.  Quality and consistency were the key drivers; at that time the major issues were that operational / transactional systems were highly inconsistent and direct access to them was discouraged for reasons of performance and security.  Business users were happy to get whatever consistent view they could, and, in general, wanted to see a stable representation of the business on a monthly, weekly or occasionally daily basis.  This architecture has remained a foundation of business intelligence ever since.

21 years later, in 2009, I introduced Business Integrated Insight (BI2).  With emerging needs like near real-time decision making in operational BI and increasing use of non-traditional data coming from Web 2.0 and other sources, this new architecture had to address a far wider scope than the original data warehouse.  While consistency and integrity remain important considerations, today’s business needs are far more about instant access to the ever-changing ebb and flow of trends in sales, manufacturing and more.  It was becoming clear that a new, over-arching architecture was required to cover all the information, processes and people of the business.

Now, three years later, it’s clear that traditional BI is racing to keep up with developments in big data, data virtualization and the cloud, mobile computing as well as social networking and collaboration.  All these topics were incorporated in BI2 from the outset.  Now, as the technology moves to the mainstream, we can and must to dive deeper in these specific areas.  Big data leads clearly to the impossibility of routing all information through an enterprise data warehouse (EDW).  But, how will that impact our need for consistency and integrity?  I envisage we will move from the old adage of “a single version of the truth” to multiple versions depending on users’ needs, with one particular version that I call core “business information” being the source of truth for external reporting and financial governance needs.  

More Read

TechAmerica and Big Data in the Public Sector
Six Data Management Predictions for 2011
Privacy Proponents Prompt President-Elect To Police
IBM Holds Human Capital Management (HCM) University in Private…
How AI Is Solving Banking Challenges During The Coronavirus Pandemic

Data virtualization has also become big news in recent years.  In many ways, it’s a technology whose time has come.  With the explosion of data volumes and varieties, users need ways to combine data on the fly with confidence and performance.  Data virtualization addresses these needs and is increasingly overlapping with function we traditionally associate with ETL.  The result, data integration, as it’s sometimes called, enables us to envisage a future where data is made available to users as they need it, whether real-time or integrated and historicized.  

And, against the background of all this upheaval in data and infrastructure, we also see a new breed of technology-savvy business users moving into positions of power.  These so-called millennials are demanding seamless, mobile access to the information they need, as well as the ability to play with it as required.  The rule of IT over the data and application resources of the organization is coming to an end.  But, that’s not to say that IT has no future role.  In fact, I see more of a fully symbiotic partnership between business and IT emerging, a partnership I call the “biz-tech ecosystem”.

My 2012 BI2 Seminar in Rome on 11-12 June explores these new directions and provides guidance on their introduction in your existing data warehouse environment.  It also introduces the Advanced Information Warehouse, shown above, as the next step on your journey from a traditional data warehouse to comprehensive business integrated insight.

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

ai in video game development
Machine Learning Is Changing iGaming Software Development
Exclusive Machine Learning News
media monitoring
Signals In The Noise: Using Media Monitoring To Manage Negative Publicity
Analytics Exclusive Infographic
data=driven approach
Turning Dead Zones Into Data-Driven Opportunities In Retail Spaces
Big Data Exclusive Infographic
smarter manufacturing
Connecting the Factory Floor: Efficient Integration for Smarter Manufacturing
Infographic News

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

RuleSpeak – some useful guidelines for writing rules

1 Min Read
data architecture
Best PracticesBig DataCloud ComputingCommentaryExclusiveHadoopOpen Source

Preserving Big Data to Live Forever

5 Min Read
Image
Data ManagementHadoopKnowledge ManagementOpen SourceUnstructured Data

The Data Lake Debate: Pro Cross-Examines Con

7 Min Read

Big Data Without Integration Is Broken

7 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 chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?