Data Analytics

Each of our data analytics courses are organized in a fashion that mirrors real-life work experiences, participants can learn the individual concepts, skills and tools and then combine them in a meaningful way. This additional assimilation of what they have learned along with the practice and skill building activities allows them to begin to do data analytic work immediately following the program.  

This program uses our exclusive “immersion” method of teaching. Participants are thrust into a simulated “real-life situation” where they practice and solve real data analytic problems. The case problem will require students (with coaching as needed) to work independently and will require teams to “prompt” themselves to take the correct actions at the right time.

An analytics maturity model is a sequence of steps or stages that represent the evolution of the company in its ability to manage its internal and external data and use this data to inform business decisions. By mapping this program to the maturity model, participants across the organization will have the same framework of data analytics making them more cohesive and able to help move SSA forward in their data analytic efforts.

Participants will apply the AIDD methodology in each course using essential skills and tools more consistently, efficiently, and effectively. This will result in the participants being able to produce results decision makers can act on with confidence.

In 3 years, the tools will be different, but data analytic concepts and the participants skill in applying them will be the same. The application of the tools is embedded into the courses so that principles can be realized, and simulations of real work can be accomplished. Students who have had specific tool training can follow along. Students who have not had specific tool training can view this as a demonstration and obtain specific tool training later.

Research shows people make sense of visual information more quickly (than tabular or narration). This makes sense for the data analyst and the decision maker. Data visualization is a key part of exploring, transforming, analyzing data, and displaying information when presenting solutions.

The field of analytics is concerned with applying statistical methods to practical business problems. Participants will develop skill in applying statistical methods and tool skills against the case problem.  They will learn to efficiently create information from their data.

Participants will create and evaluate their solution. This affords them a retrospective period to self-assess how they did and what they can do better moving forward.