For the past few years we’ve worked closely with Higher Education Institutions on applying data analytics to optimize student admissions, financial aid, student retention and academic outcomes. We recognized from the onset that this student “lifecycle” has a straight progression to an alumni lifecycle which has a critical goal of fostering school loyalty and giving.
At least that’s what I thought when I first starting hearing about graph database technology. I’m a business person, not a database expert. Our business is simply stated, delivering high value insights for the enterprise through analytics. So, when our CTO, Kurt Rosenfeld, explained to me what “what is possible” with graph databases I knew
In this part 2 of 6 view blog series: In a recent survey conducted by CTI, marketers listed data integration as the number one obstacle to their ability to arrive at a single, trusted and complete 360-degree analytical view of their customers. In his latest video blog, CTI CustomerUniverse Product Director, Mark Janowicz talks about
I’ve been in the Data Analytics space for a long time and over the years I’ve worked on numerous HR “reporting, dash-boarding, and data warehouse projects.” Actually, I am in the process of wrapping up a 6 month project that integrates analytics into a Workday environment. Just to level set, Workday, is highly regarded as
Data Governance and Student Success — I just attended the Higher Ed Data Warehouse (HEDW) conference, which this year was hosted at the University of Arizona in Tucson. This is our second year attending (as a sponsor). U of A is a sizeable institution with an excellent facility to accommodate the 300+ attendees. And Tucson
Student Life-cycle at HEDW Conference — On April 23rd – 26th, CTI is once again sponsoring the Higher Education Data Warehouse conference. Last year at the conference we introduced the concept of the “Student Lifecycle” to drive recruitment, retention and success. The impact of analytics is driving improvements in University performance across a broad
In today’s competitive and Omni-channel markets, the key to success of each business is understanding its customers. Through a systematic approach of harnessing data, leveraging analytics and knowledge, one can drive effective marketing decisions in a technology-enabled and model-supported interactive decision process. Customer Segmentation We live in a diverse society where customers differ in their
Data analytics is a process, where information is gathered, modeled and interpreted, with the end goal of providing insights and implications for the business decision-making. Data project pipeline To be successful in it, we must approach a data project in a methodical way. There is a sequence of steps—a data project pipeline with four general