Search Knowledge Base
Analytics Advisory
Data analysis is an important part of the managerial and strategic planning process. Our data analysis module includes a two-step approach: (1) data analysis to examine in great detail the components of a data set by separating them out to study the parts individually and in particular their relationship to and interaction between each other; and (2) using data analytics as a much broader and overarching discipline that encompasses the complete management of data. It provides us with tools and techniques needed for collecting, organizing, analyzing, governing and storing data, of which data analysis is a necessary subset.
We restrict our approach to conventional data analysis to a degree due in part to novel characteristics, principles, objectives, and concepts integral to our research projects, program structures, themes, home office activities, and field operations. Standardized interviewing skills and other tools in vogue are not entirely reliable, given the type of analysis needed for the type specialized work we perform. This suggests a need for innovative criteria from which to devise an alternative approach to data analysis to help us better understand information derived from our work. It has revolutionized how we think about collecting, assessing, analyzing, evaluating, and managing data.
Data analysis looks at the past while data analytics attempts to predict the future. We consider data analysis as an in-depth study and/or review of past and current facts relating to how our organization functions internally and its external performance of projects, programs, and field-level operations. Data analytics analyze data to discover that which can occur in the future; a process necessary for conducting logical, systematic and deductive reasoning for descriptive, statistical, and mathematical data analysis. These methods relate to clusters and segments to score and predict what scenarios are most likely to happen in the future, approaches that are interactive and often interchangeable in our work.
While data analysis suffices for decision-making in certain scenarios, the wider and more comprehensive discipline of data analytics empowers the next phase in planning and decision-making. It can predict an event occurrence and prescriptive measures if needed. This insight for forecasting an event occurrence and solutions required supports our efforts to plan strategically and create sustainable pathways that foster systematic and progressive achievements over extended time-horizons.
Module Details
MOD-1. Qualitative and Quantitive Data. Collects data through methods of observations, one-to-one interviews, consultation, facilitating focus groups, and similar methods.
MOD-2. Data to Articulate Performance. Assesses modes of communication: interpretive, interpersonal, and presentational to articulate performance and goal achievement.
MOD-3. Data Assessment and Evaluation. Aims for factual analysis of content. Provides guidance on insights and distinguishing features of information received.