Introductory Webinar on QDA Miner & WordStat

Why attend?

Dr. Uwe Ewald, Analyst & Lawyer

Improve your text analytics skills!

This Introductory Webinar on QDA Miner & WordStat for Provalis Research text analytics software offers an introduction into the complex functionality of Provalis software.

QDA Miner is a powerful analytical tool to research digitized (mainly) textual information. At the end of this eight hour webinar attendees should be able to start their own analysis on (mass) digitized data.

Quote from Provalis Website:

“QDA Miner is an easy-to-use qualitative data analysis software package for coding textual data and graphical, annotating, retrieving and reviewing coded data and documents. The program can manage complex projects involving large numbers of documents combined with numerical and categorical information. QDA Miner also provides a wide range of exploratory tools to identify patterns in codings and relationships between assigned codes and other numerical or categorical properties. Documents are stored in Rich-Text Format and support font and paragraph formatting, graphics and tables. Documents may be edited at any time without affecting the existing coding. QDA Miner can import and export documents, data and results in numerous file formats (MS Word, WordPefect, RTF, PDF, HTML, XML, MS Access, Excel, SPSS, Paradox, dBase, QSR N6, Nvivo, Atlas.ti, HyperResearch, Ethnograph, Transana, Transcriber, etc.). It also provides unique integration with advanced quantitative content analysis, text mining (WordStat) and statistical analysis (Simstat) tools, providing easy combination and integration of qualitative and quantitative methods.”

 

Big Data, Electronic Evidence and Criminal Defence

RAV-Seminar “Digitale Beweismittel: Von Handydaten bis Umgebungsintelligenz – Strafverteidigung im Zeichen von Big Data”, Berlin

Big Data electronic evidence predominates more and more the evidentiary procedure in serious and organised crime cases in European criminal courts. Hence, law enforcement and courtroom participants are often still in ‘analogous’ mode and just begin to understanding the nature of digital evidence, the technologies to process digital data and eventually its revolutionising impact on their role in criminal procedures. It appears that criminal defence lawyers are facing a particular challenge in handling Big Data electronic evidence (eEvidence) since they are often not sufficiently prepared and equipped to process digital evidentiary data in contrast to prosecutors with the technological power of law enforcement agencies at their disposal.

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