ATLAS.ti has always been at the forefront of software for qualitative and mixed research, but version 22 has exceeded all expectations and previous editions. The processes of creating a project, adding data sources and coding them is very simple, and functionalities for automatic searching and coding have been added and improved. The new functions to incorporate data from social networks is also very useful, considering that many researchers work with this type of source. Finally, the icing on the cake is the multiple ways to visualize the data, a feature appreciated when you want to identify and discover patterns in the data that are not identifiable at first glance.

I was introduced to ATLAS. ti a few years ago, and the first thing that struck me was its ease of use and impactful facilitation of the coding process that is at the heart of any good qualitative study. A well-coded data is a gold mine that throws some ground-breaking and powerful interpretation and construction of meaning and perspectives to the research phenomena. Coding is an iterative process, often they get written, rewritten and refined as more and more transcripts get read for coding. As you start coding in ATLAS.ti, the codes get saved, the list of already existing codes show up every time you code a new piece of data segment. This saves a lot of time as you would have otherwise spent going back and forth previous transcripts, looking up the codes you had already given while coding manually. ATLAS. ti also allows merging or splitting of codes at any point while coding the documents and automatically updates the previously coded documents with the updated codes. This ease of coding allows any number of iterations and reflective re-coding of data possible resulting in an unbiased, thoroughly thought set of codes that would lead to a meaningful interpretation of qualitative data.

ATLAS.ti offers a very wide range of qualitative analysis options, one of the options that most helps me in my work is certainly the co-occurrence table, which flattens the data crossings; with it I can create exceptional graphics through tables in excel. Another exceptional option is the network option, which allows you to design the analysis visually. In my dissertation I used these schemes a lot to explain my findings, the teachers who analyzed the work really enjoyed seeing this process. I'm in the testing phase of AI in the software, and I've seen some very good results, even in the beta version. This software is the future for every researcher who wants to deepen his analysis.