Posts Tagged ‘predictive analytics’

As promised, today I am sharing the fundamentals of using the LOOP and VECTOR in a SPSS Syntax script. LOOP LOOP is a common programming concept – it simply allows you to apply or execute the same script commands for an identified number of times without having to recode them.   VECTOR A VECTOR is […]

I recently finished another productive mentoring session exploring Data Transformations using SPSS Syntax. We had so much fun using some basic SPSS, I just had to share, so: Getting back to my Predictive startup example, we now have a new version of the quarterly hours file. This one includes a few new columns (“variables” to […]

Continuing my discussion on the use of SPSS Syntax scripting to perform file operations, today I’ve investigated how to use SPSS to perform some very general physical file restructuring. Why is this important? It’s important because it again shows how SPSS can be used to arrange the data pool into the most effective format based […]

My start-up predictive analytics organization “Predictive Performers” wants to do some internal planning. We receive extract files from an an accounting service each month that provide the total hours billed per each of our consultants, along with each consultants hourly rate. The files are saved to a folder on our network: The files also breakout […]

I just returned from the IBM Vision Conference in Orlando, Florida. I attended a session in every available timeslot from Monday morning to Wednesday afternoon and it was worth every single minute of my time! Although there were too many sessions and presenters to mention, here are my “top picks”: Designing Solutions with IBM Cognos […]

The SPSS Syntax Editor (by default, the name of the new syntax window is SPSS Statistics Syntax Editor). Is divided into 4 areas (or “panes”):   Editor Pane The editor pane is the main part of the syntax editor and it is here where you perform your scripting. Gutter Pane The gutter pane is adjacent […]

As IBM’s Premier Partner delivering Smarter Commerce solutions Perficient knows how to create a seamless and unified omni-channel commerce experience that leverages commerce, social and mobile technologies to provide the operational excellence needed to deliver a consistent brand experience that deepens your client relationships. Perficient is one of a very small delivery partner that are […]

Perficient’s award-wining IBM Business Analytics practice is a Gold sponsor of Vision 2013. During the conference our subject matter and industry experts will be on-hand to discuss how Perficient helps our clients leverage accurate, timely and integrated information to transform information into actionable intelligence that provides insight, drives planning and improves performance. Our experience with […]

With Perficient’s help Mission Health is leveraging IBM’s master data management (MDM) to build a scalable, accurate foundation around its most critical data to support critical business processes across the enterprise – information about patients, providers, facilities, organizations, employees and more. Watch this webcast and learn how Mission Health is using Big Data and Analytics […]

No matter what the tool or technology used, data analysis always involves 4 simple steps: Pull together data, Pick the appropriate analysis process or procedure to be performed on that data, Point out (designate) the variables in the data that you are interested in and finally, after performing the selected process, you can Peruse the […]

Healthcare organizations need to better understand the factors leading patients to make hospital visits in the first place and then effectively treat those issues in the first visit. Predictive analytics allows healthcare organizations to do just this by managing chronic conditions, engaging patients in their own care, and identifying factors that make readmission likely. Perficient […]

I have been pleasantly surprised about the new startups which have emerged on predictive analytics  This year, i would be covering a wide range of predictive analytical tools and its usage techniques. We no longer need PHDs to understand statistics and to start using predictive models. We have to know how to use the tools and […]