The use of QDA software in social science research is so common that many people tend to see QDA software as a tool primarily for social science research. However, applications like MAXQDA are invaluable productivity tools for research analysts in industry or government as well.
Remarkably scalable, MAXQDA employs a database architecture that can handle research projects ranging in size from several dozen pages to tens of thousands of pages. Many projects today involve identifying connections found among information stored in PDF, Powerpoint presentations, Word documents, photos, videos, and audio recordings. MAXQDA allows users to code relevant sections of each document, identify interrelationships among documents, build relationships among diverse sets of documents and identify thematic trends.
MAXQDA features a simple 4 pane interface that makes it easy to use. The Document System- is where you place documents (text, images, video, or sound files) you want to analyse. The Document Browser is where you view the content of the document. The Coding System shows the various codes that you create and assign to documents. The Retrieved Segments Pane shows search results.
Based on our record, Amazon EMR seems to be more popular. It has been mentiond 10 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: about 1 year ago
I'm going to guess you want something like EMR. Which can take large data sets segment it across multiple executors and coalesce the data back into a final dataset. Source: almost 2 years ago
This is exactly the kind of workload EMR was made for, you can even run it serverless nowadays. Athena might be a viable option as well. Source: about 2 years ago
Apache Spark is one of the most actively developed open-source projects in big data. The following code examples require that you have Spark set up and can execute Python code using the PySpark library. The examples also require that you have your data in Amazon S3 (Simple Storage Service). All this is set up on AWS EMR (Elastic MapReduce). - Source: dev.to / over 2 years ago
Check out https://aws.amazon.com/emr/. Source: about 2 years ago
NVivo - Buy NVivo now for flexible solutions to meet your specific research and data analysis needs.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
ATLAS.ti - ATLAS.ti is a powerful workbench for the qualitative analysis of large bodies of textual, graphical, audio and video data. It offers a variety of sophisticated tools for accomplishing the tasks associated with any systematic approach to "soft" data.
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
QualCoder - A very complete Free and Open Source Software (FOSS) Computer-Assisted Qualitative Data Analysis Software (CAQDAS) written in Python. It works with text, images, and multimedia such as audios and videos.
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?