Apache Arrow Reviews

MAXQDA Reviews

1. ColdInWinter

   | Analyst at Trimal Consulting | over 2 years ago
   A data analysis tool for business, government, and academic research projects

   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.

   🏁 Competitors: ATLAS.ti, NVivo, QDA Miner, HyperResearch, Quirkos

Apache Arrow mentions (34)

• Arrow Flight SQL in Apache Doris for 10X faster data transfer

  Apache Doris 2.1 has a data transmission channel built on Arrow Flight SQL. (Apache Arrow is a software development platform designed for high data movement efficiency across systems and languages, and the Arrow format aims for high-performance, lossless data exchange.) It allows high-speed, large-scale data reading from Doris via SQL in various mainstream programming languages. For target clients that also... - Source: dev.to / 26 days ago

• How moving from Pandas to Polars made me write better code without writing better code

  In comes Polars: a brand new dataframe library, or how the author Ritchie Vink describes it... a query engine with a dataframe frontend. Polars is built on top of the Arrow memory format and is written in Rust, which is a modern performant and memory-safe systems programming language similar to C/C++. - Source: dev.to / 3 months ago

• Time Series Analysis with Polars

  One is related to the heritage of being built around the NumPy library, which is great for processing numerical data, but becomes an issue as soon as the data is anything else. Pandas 2.0 has started to bring in Arrow, but it's not yet the standard (you have to opt-in and according to the developers it's going to stay that way for the foreseeable future). Also, pandas's Arrow-based features are not yet entirely on... - Source: dev.to / 6 months ago

• TXR Lisp

  IMO a good first step would be to use the txr FFI to write a library for Apache arrow: https://arrow.apache.org/. - Source: Hacker News / 6 months ago

• A Polars exploration into Kedro

  Polars is an open-source library for Python, Rust, and NodeJS that provides in-memory dataframes, out-of-core processing capabilities, and more. It is based on the Rust implementation of the Apache Arrow columnar data format (you can read more about Arrow on my earlier blog post “Demystifying Apache Arrow”), and it is optimised to be blazing fast. - Source: dev.to / about 1 year ago

MAXQDA mentions (0)