Posts

How Data Scientists Demystify Complex Questions

To help you understand Ironside’s philosophy on advanced analytics, data science, and predictive/prescriptive technologies, we thought it would be helpful to share insights directly from our data scientists.

Win FullerThis week I talked with Win Fuller, who has over three decades of experience with advanced analytics and business intelligence at a wide array of companies including Staples, VistaPrint, Upromise, Stax, and Bain & Company. Win holds a PhD in Econometrics from Tufts University, and specializes in predictive models addressing questions around churn, customer retention, and demand generation among many other analysis topics. He is also an expert in all aspects of data extraction, integration, and manipulation. His goal in any engagement is to use his experience to clearly understand and realize his clients’ business and analysis goals. Read more

How Data Scientists Reveal the Right Actions

To help you understand Ironside’s philosophy on advanced analytics, data science, and predictive/prescriptive technologies, we thought it would be helpful to share insights directly from our data scientists.

Chi ShuThis week I spent some time with Chi Shu, a 5-year veteran in the data science and advanced analytics space with experience across both the public and private sectors. Prior to joining Ironside, Chi worked as a marketing analyst evaluating performance through segmentation and direct marketing models and as a government analyst using business analytics platforms to make critical metrics available to key stakeholders. Chi is one of our brightest programming minds with extensive knowledge of systems such as MATLAB, Python, R, SAS, and SPSS. Her top priority in any engagement is to consistently deliver personalized, relevant results that unlock an organization’s true potential. Read more

Ironside’s client, a leading New England technical institute, wanted to get predictive with their admissions strategy, leveraging advanced analytics to generate projections that would have measurable impacts on the number of successful students continuing on past their freshman year. They also wanted these projections to integrate seamlessly with the admissions process, providing counselors with actionable guidance and standards for admittance. Read more

 How Data Scientists Find Order in Chaos

To help you understand Ironside’s philosophy on advanced analytics, data science, and predictive/prescriptive technologies, we thought it would be helpful to share insights directly from our data scientists.

Pam Askar BWThis week I spoke with Pam Askar, who has over 10 years of quantitative research and predictive modeling experience and holds a PhD in Developmental Psychology from UConn. She worked in academia and the private sector as a psychology professor and a data modeler for a pharmaceutical market research firm before joining Ironside. This makes Pam uniquely qualified to both implement analysis strategies for clients and teach solutions in ways that ensure success. Regardless of the project, Pam’s deepest source of enjoyment is always the same: finding powerful solutions to complex problems that provide actionable business results. Read more

On June 3rd, Ironside hosted a webinar on Donor Optimization Techniques with IBM Business Analytics.  Industry experts from IBM, along with special guest Monique Dozier, the Assistant Vice President of Advancement Information Systems & Donor Strategy at Michigan State University, demonstrated techniques for successfully increasing and accurately targeting fundraising efforts. Read more

IBM SPSS Modeler 17 and Statistics 23 were officially released at the beginning of March 2015. There are several important changes in licensing structure and system infrastructure, as well as many innovative new functionality enhancements. This article will briefly introduce the enhancements added to Modeler 17 from a practical perspective. Something worth noting as you begin exploring this most recent round of upgrades is that Analytics Server will be heavily leveraged in a lot of these new features. Read more

Ironside, has become the first IBM Business Partner to achieve IBM Gold Software Accreditation in the three major pillars of IBM business analytics software: Business Intelligence (Cognos), Financial Performance Management (TM1), and Predictive Analytics (SPSS). Read more

Earlier this year, we published a newsletter article scratching the surface of the Text Analytics Premium add-on for IBM SPSS Modeler. It introduced the fundamentals of text analytics and the idea of extracting information from unstructured text data. In this follow-up article, we will dive more deeply into some of the more advanced topics to fully leverage the add-on’s functionalities. Read more

What Python Is and Why to Use It

Python is a powerful open source general-purpose programming language. Through an easy-to-use structure, it allows users to perform a huge variety of controlling tasks on a computer.

In the case of using the Python plug-in for SPSS, it enables one to control the program flow based on conditions, to execute different syntax dynamically and interactively according to intermediate results, to apply command extensions and unlimited Python modules for more complicated algorithms, etc. Read more

On June 17th, Ironside hosted a Customer Analytics for the Informed Executive webinar exploring how advanced analytics can help businesses attract and retain customers. This webinar reviews a variety of data science methods that can utilize extensive existing data to provide guidance on many functional areas within a company. Read more