Steve Cormier

TamGroup Director, Solution Delivery
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Recent Posts

The Heart of Data Virtualization (Part 3)

Posted by Steve Cormier

10/13/15 11:14 PM

Part 3: Data Virtualization to the Rescue

In Part 2 of this article, we explored how creating a data warehouse meant buying hardware, and software, and managing it, and doing backups, and version upgrades, and having more DBA’s, and how something new was needed.

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Topics: Analytics, Business Intelligence

The Heart of Data Virtualization (Part 2)

Posted by Steve Cormier

6/16/15 1:00 PM

Part 2: The re-emergence of process oriented design

In Part 1, we looked at how OOD/Normalized modeling came into being and how important it was to data efficiency and integrity. 

In this installment, we see how the process-oriented design approach has re-emerged in the Big Data culture, and how data virtualization helps restore OOD/Normalization order. 

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Topics: Analytics, Business Intelligence

The Heart of Data Virtualization (Part 1)

Posted by Steve Cormier

2/28/15 10:51 AM

Part 1: Data Virtualization and Business Data Modeling 

Data virtualization is a technology that’s receiving a great deal of attention, as it offers solutions that are more efficient and economical than predecessor technologies such as data warehousing/ETL.

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APIs Are Like a Box of Chocolates: Part 2

Posted by Steve Cormier

2/26/14 8:30 AM

In my last post I talked about APIs, whether they are really a new technology, and how to avoid being swept up in the hype surrounding them. In this post, I'll go over the important principles of software engineering and deployment that you should review if you plan on buying and implementing an API. 

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Topics: Optimization, Information Management, Information Integration, Digital Business Evolution

APIs are Like a Box of Chocolates: Part 1

Posted by Steve Cormier

2/20/14 8:00 AM

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Topics: Optimization, Information Management, Information Integration, Digital Business Evolution

Evolving IT Systems - Key Concepts

Posted by Steve Cormier

1/14/14 11:00 AM

Many organizations who want to migrate to a new, comprehensive operational system try a ‘big bang’ approach. This approach to business transformation usually proves unsuccessful. Most ‘big bang’ projects fail for multiple reasons such as:

  • The gap between the evolved complexity of existing systems and the new system (out of the box) is too large.
  • However innately sophisticated it is (e.g. SAP), the new system almost always lacks the matured, business-specific capabilities of existing systems (if put into production, the new system would develop these capabilities over time). 
  • Timing of migration is a very difficult and complex topic of its own. How to create a workable migration plan is usually not well understood, particularly with respect to comprehensive reporting for areas such as sales, marketing and finance.
  • The stress of learning a new large scale system while maintaining the current one overwhelms personnel resources. This can cause errors in current production, the correcting of which pulls resources off the new system development causing further migration delays. 

The solution?

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Topics: Digital Business Evolution

Business Rules Rule

Posted by Steve Cormier

11/18/13 9:30 AM

A number of years ago, I was in charge of designing and implementing a data warehouse. At the same time, the company involved was replacing a number of operating systems with a single new one. Two deadlines had already been missed for go-live on the new system, and a lot of meetings were being held as to why. I happened to end up in one of these, which was about system security. The discussion was about user access to information in the system through the new website portal. The company had several subsidiaries, and at one point I asked the question, “Can an employee work for more than one company subsidiary?”

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Topics: Information Management

Microsoft Excel – The Beauty, the Danger, and Moving Beyond to Analytics

Posted by Steve Cormier

11/13/13 11:00 AM

People talk about a lot of cool data science and tools these days; big data, analytics, sentiment in social networking; but the fact is, a very substantial amount of the computing in the US takes place in a small intimate place called Microsoft Excel.

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Topics: Analytics

Integration: What’s in a Name?

Posted by Steve Cormier

4/28/12 6:14 PM

You're building a data warehouse, and you want to indicate what U.S. Census regions your customers are in for analytics purposes.

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Topics: Analytics, Data Warehouse, Information Management, Information Integration

IT Transformation Success Means Resisting Existing Systems

Posted by Steve Cormier

4/24/12 7:25 PM

You're an architect and you've just entered a new environment: a company in the throes of business and IT transformation initiatives.  Your task is to design a new system to replace what's already there, achieving enterprise transformation that yields competitive advantage. 

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Topics: Optimization, Information Management, Information Integration

Analytics: getting better all the time

Posted by Steve Cormier

8/3/11 4:27 PM

The pace of competition in business is increasing, fed in part by advances in information dissemination and computing power.  It doesn't matter what type of business, constant improvement is the focus.

The obvious sector is retail, where margins are often thin, competition can be fierce, and immediate product feedback allows businesses to adjust their advertising, promotions, or product placement in time frames inconceivable even a decade ago.    

A customer on the Internet can experience a new set of offers based on aggregate information from thousands of their fellow shoppers, drawn from their reaction to an offer experienced within the previous hours or even minutes.

Retail isn't the only sector subject to demands for constant improvement.  Healthcare, with pressure from government, constant innovations in treatment, and an emerging sense of consumerism on the part of patients, is seeking to identify improved practices and achieve better patient communication.

Utilities, faced with constrained resources and ever increasing need, are looking to smart feedback systems to help them tune their supply and demand balances, based on how people react to various factors in their consumption of services.

The solution to all of these demands for constant improvement is found in analytics.

What is analytics, really?  

Analytics is about getting feedback from existing systems to determine how to alter them for the better.

To do this, data (often large amounts) is drawn from existing systems, and compared against desired outcomes.  Where the result doesn't match the expectation, further analysis can be done to see where things are going wrong.  The system is altered, and the cycle starts again.  Doing this over and over again can lead to deeper customer satisfaction and better rewards to the provider.

Predictive analytics takes this one step further.  By applying algorithms based on extending existing data patterns, expected results of possible changes to the system can be modeled.

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Topics: Optimization, Analytics