A metadata model is “a gathering of Meta information that includes both physical information and business information for one or more datasources and is the foundation for both future modelling and report development within an organization”. Meta-model flexibility can be defined as the ability of a (Meta) model to: Easily expand and grow (to support […]
Posts Tagged ‘iod’
Rapidly Adaptive Visualizations
I was “lucky” enough to be selected to “go on the road” this year as part of my organizations presence at the IBM business analytics summits, taking pace all over the country. If you haven’t attended one yet, you should as the content presented is both […]
Where and How to Learn Splunk
“Never become so much of an expert that you stop gaining expertise.” – Denis Waitley In all professions, and especially information services (IT), success and marketability depends upon an individual’s propensity for continued learning. With Splunk, there exist a number of options for increasing your knowledge and expertise. The following are just a few. We’ll […]
Cognos TM1 Performance Review – on a budget!
Often I am asked to conduct a “performance review” of implemented Cognos TM1 applications “rather quickly” when realistically; a detailed architectural review must be extensive and takes some time. Generally, if there is a limited amount of time, you can use the following suggestions as perhaps some appropriate areas to focus on (until such time […]
A Splunk Decision Support System
The importance of making credible decisions can be the difference between profit or loss, or even survival or extinction. Decision Support Systems (or DSSs) serve the key decision makers of an organization– helping them to effectively assess predictors (which can be rapidly changing and not easily specified in advance) and make the best decisions, reducing […]
Cognos TM1 TurboIntegrator – Run-time or Read-time?
In this blog I wanted to take some time to describe certain “behaviors” of Cognos TM1 TurboIntegrator processes. Access to Processes As of version 10.2 (or as of this writing), TM1 Server lists all processes (in alphabetical order) under the consolidation “Processes”. The visibility of processes can be controlled by implementing TM1 security. TM1 groups […]
Predicting Project Success with IBM SPSS
A technology company has literally participated in thousands of projects over the years. At some point the group decided it wants to determine what factors or characteristics may influence the (hopefully successful) competition of current and future implementation projects. Thankfully, they have maintained records in on every project that they were involved in and that […]
Selecting your Modeling Approach with IBM SPSS Modeler
Coming from a TM1 background (more business than statistics), it is easy to get stated with modeling once you determine your modeling objective, and Modeler can help with that. IBM SPSS Modeler offers an intuitive interface that will appeal to a wide range of users from the non-technical business user to the statistician, data miner […]
Examining (Data) Relationships
The discovering of relationships within data (between fields) is an important part of any data mining project (in the Crisp-DM methodology, this is described as part of the “Data Understanding” stage). This “relationship discovery” is part of developing a predictive model but is also helpful in answering specific business questions -perhaps even what originally motivated […]
All about CLEM
SPSS CLEM is the control Language for Expression Manipulation, which is used to build expressions within SPSS Modeler streams. CLEM is actually used in a number of SPSS “nodes” (among these are the Select and Derive nodes) and you can check the product documentation to see the extended list. CLEM expressions are constructed from: Values, […]
Sampling Your Data
Another interesting feature of SPSS Modeler is its built-in ability to sample data. It is pretty typical to have (in one or more files) hundreds of thousands of records to process, and using complete sets of data during testing can take a huge amount of your time and is inefficient in terms of computer processing […]
TM1 vs. SPSS Modeler Comparison Continues – Setting to Flags
Consider the scenario where you have to convert information held in a “categorical field” into a “collection of flag fields” – found in a transactional source. For example, suppose you have a file of transactions that includes (among other fields) a customer identifier (“who”) and a product identifier (“what”). This file of transactional data indicates […]