Digital Mind Development is a specialist provider of data analysis solutions. The process of evaluating data using analytical and logical reasoning to examine each component of the data provided. This form of analysis is just one of the many steps that must be completed when conducting a research experiment. Data from various sources is gathered, reviewed, and then analyzed to form some sort of finding or conclusion. There are a variety of specific data analysis method, some of which include data mining, text analytics, business intelligence, and data visualizations. Knowing how to properly handle the data analysis will allow you to get the most from your data and make the right decisions.
To use an analogy: After sorting the pieces of a jigsaw puzzle into groups, it is important to inspect individual pieces to determine how they fit together and form smaller parts of the picture (e.g., the tree part or the house part). This is a labor intensive process that usually involves a lot of trial and error and frustration. A similar process takes place in the qualitative data analysis. When analyzing data, one compares and contrasts each of the things that have been noticed in order to discover similarities and differences, build typologies, or find sequences and patterns. In the process one might also stumble across both “wholes” and, quite literally, holes in the data.
While the jigsaw puzzle approach to analyzing data is frequently productive and fruitful, it also entails some risks and problems that also translate to qualitative data analysis. Experienced qualitative social scientists have always been aware of the potential problems, and organize their work to minimize the adverse effects. For example, when coding data, the simple act of breaking down data into its constituent parts can distort and mislead the analyst and distort the final data analysis. A serious problem is sometimes created by the very fact of organizing the material through coding or breaking it up into segments in that this destroys the totality of philosophy as expressed by the interviewee-which is closely related to the major goal of the study that informs the data analysis. A proper data analysis acknowledges this problem and, in fact, takes precautions already when first analyzing data.
Our team has deep expertise in the entire data analysis lifecycle and strong working knowledge of all of the basic and advanced components and processes that go into any effective solution