ATLAS.ti belongs to the genre of CAQDAS programs. CAQDAS stands for Computer-Aided Qualitative Data Analysis Software. It is a somewhat lengthy acronym as compared to ‘QDA software’, which can also be found in the literature. The latter stands for Qualitative Data Analysis Software and the apparent similarity may be responsible for some misunderstandings and misperceptions related to CAQDAS. To avoid problems in the process of data interpretation it is necessary to outline the differences between QDA and CAQDAS:
ATLAS.ti – like any other CAQDAS program – does not actually analyze data; it is simply a tool for supporting the process of qualitative data analysis or the process of analyzing qualitative data. Not all qualitative data is analyzed in an interpretative tradition and not always in the context of academic research. Instead, users apply a deductive coding frame and they aim to extract code frequencies or cross-tabulations of codes in the end. This is an equally valid application. Counting is easy business for software, however, ATLAS.ti also offers many layers for writing and thinking and for developing your interpretation. Thus, it is easier to examine even large data sets or different types of data. ATLAS.ti does not only offer ‘a coded segment’, it splits a coded segment into two objects: a quotation and a code. And there is not even the need to set a code.
For an initial very detailed analysis you can go through your data and create quotations, write comments for these quotations and use the quotation name as a label for the selected data segment. When you want to move to the next level of abstraction in your analysis, you can begin to apply codes. Thus, ATLAS.ti will not (and cannot) make suggestions in terms of how to interpret data, but it offers research tools that help you to develop an interpretation yourself without losing track.
Computers are excellent at finding things like certain words in the data, in your comments or memos; or coded data segments in a large variety of combinations. It is up to the researcher to define via commenting, labeling, memoing and coding, which data segment has what kind of meaning. Therefore, the outcome of data interpretation questions may difference between several researchers. To avoid misunderstanding and question based on different interpretations it is useful to fix a central angle. This ensures that analysis and interpretation help you to verify or counterfeit a hypothesis. A carefully data-informed decision-making helps to increase your success and should not just rely on quantitative data.
In discussions, you often find three camps of researchers: those who see software as central to their way of analyzing data and those who feel that it is peripheral and fear that using it leads to a ‘wrong’ way of analyzing data. Therefore, it is important how collected analyzed and presented data are put together. Some advocate software mainly as an organizing tool that helps you manage the data.
A powerful tool like ATLAS.ti can answer the questions you arise during your text analysis, but please note, it is not a comprehensive solution. The interpretation of different types of data is a challenging work to do because it is more than just drawing some pie charts, bar graphs, bar charts, line graphs or line charts. Please take some time to decide which chart shows which information. This often needs some more time than statistical analysis. Your charts may lead to other questions based on your results of research and outline several data interpretation questions.
Software frees you from all those tasks that a machine can do much more effectively, like modifying code words and coded segments, retrieving data based on various criteria, searching for words, integrating material in one place, attaching notes and finding them again, counting the numbers of coded incidences, offering overviews at various stages of a project, and so on.
By using ATLAS.ti, it becomes much easier to analyze data systematically and to ask questions that you otherwise would not be able to ask because the manual tasks involved would be too time-consuming. ATLAS.ti accelerates the process of integrating and structuring large amounts of data or those with different media types. In addition, a carefully conducted, computer-assisted qualitative data analysis also increases the validity of research results, especially at the conceptual stage of an analysis. When using manual methods, it is easy to ‘forget’ the raw data behind the concepts as it is quite laborious to get back into the data. In a software-supported analysis, the raw data are only a few mouse clicks away and it is much easier to remind yourself about the data and to verify or falsify your developing theoretical thoughts. In other words, it gets easier to identify data interpretation problems earlier.
Your ideas about the data are likely to be different three or six months into the analysis as compared to the very early stages, and modification of codes and concepts is an innate part of qualitative analysis of data. Computers also document this process. The steps of analysis can be traced and the entire process is open to view.
ATLAS.ti may be less appropriate if you have lots of data material like 5000 lengthy documents or 50.000 or more pages of material. You are probably better off looking for data mining software. If your methodological approach requires very fine-grained work on just a few lines of text and you only intend to look at a small body of data but in a very detailed way, CAQDAS is likely to be inappropriate as well. We recommend that you download the demo version and work through the Quick Tour to find out whether ATLAS.ti serves your methodological needs or other requirements you may have.
If you are still not certain, contact our help desk and describe your project and requirements. We will put you in touch with a person that will provide competent advice. We certainly want to sell our product, but we also want happy customers. Therefore, we would like to invite you to test drive our software before you purchase it.