--- description: Scopri le funzionalità di Orange, i dettagli del prodotto, chi utilizza il software e quali sono i prodotti suggeriti. Attraverso le recensioni di utenti verificati potrai capire com’è la user experience, l’assistenza post-vendita e molto altro. image: https://gdm-localsites-assets-gfprod.imgix.net/images/capterra/og_logo-e5a8c001ed0bd1bb922639230fcea71a.png?auto=format%2Cenhance%2Ccompress title: Orange - Prezzi, recensioni, informazioni - Capterra Italia 2026 --- Breadcrumb: [Home](/) > [Software per data visualization](/directory/30696/data-visualization/software) > [Orange](/software/164505/orange) # Orange Canonical: https://www.capterra.it/software/164505/orange Pagina: 1/2\ Avanti: [Pagina successiva](https://www.capterra.it/software/164505/orange?page=2) > Soluzione di visualizzazione dei dati open source e machine learning che fornisce programmazione visiva per creare flussi di lavoro di analisi. > > Conclusione: valutazione di **4.2/5** stelle assegnate da 19 utenti. Miglior punteggio per il parametro **Lo consiglieresti?**. ----- ## Panoramica ### Chi utilizza Orange? Progettato per le piccole e grandi imprese, è uno strumento di visualizzazione dei dati on-premise, che aiuta a gestire data mining, pre-elaborazione, modellazione predittiva, valutazione delle funzionalità e altro ancora. ## Statistiche e valutazioni | Parametro | Valutazione | Dettaglio | | **Nel complesso** | **4.2/5** | 19 Recensioni | | Facilità d'uso | 4.2/5 | Sulla base delle recensioni complessive | | Assistenza clienti | 3.8/5 | Sulla base delle recensioni complessive | | Rapporto qualità-prezzo | 4.3/5 | Sulla base delle recensioni complessive | | Funzionalità | 4.3/5 | Sulla base delle recensioni complessive | | Percentuale di raccomandazione | 80% | (8/10 Lo consiglieresti?) | ## Informazioni sul fornitore - **Azienda**: University of Ljubljana ## Contesto commerciale - **Modello tariffario**: (Versione gratuita disponibile) (Versione di prova gratuita (free trial)) - **Pubblico target**: Lavoratore autonomo, 2-10, 11-50, 51-200, 201-500, 501-1.000, 1.001-5.000, 5.001-10.000, 10.000+ - **Implementazione e piattaforme**: Mac (desktop), Windows (desktop) - **Lingue supportate**: inglese - **Paesi disponibili**: Slovenia ## Funzionalità - Analisi predittiva - Analisi statistica - Analisi visiva - Creazione di report/analisi - Determinazione visiva - Estrapolazione del testo - Gestione dei dati collegati - Pannello di controllo personalizzabile - Ricerca/Filtro - Visualizzazione di dati ## Opzioni di supporto - Chat ## Categoria - [Software per data visualization](https://www.capterra.it/directory/30696/data-visualization/software) ## Categorie correlate - [Software per data visualization](https://www.capterra.it/directory/30696/data-visualization/software) - [Software per data mining](https://www.capterra.it/directory/31083/data-mining/software) ## Alternative 1. [Microsoft Power BI](https://www.capterra.it/software/176586/power-bi) — 4.6/5 (1871 reviews) 2. [Tableau](https://www.capterra.it/software/77260/tableau) — 4.6/5 (2348 reviews) 3. [Google Analytics 360](https://www.capterra.it/software/177042/google-analytics) — 4.7/5 (8089 reviews) 4. [Canva](https://www.capterra.it/software/168956/canva) — 4.7/5 (13253 reviews) 5. [Google Charts](https://www.capterra.it/software/176573/google-charts) — 4.6/5 (740 reviews) ## Recensioni ### "Machine Learning, Perdiction based data viulization" — 4.0/5 > **Tariq Mahmood** | *8 luglio 2020* | Elettronica di consumo | Tasso di raccomandazione: 9.0/10 > > **Vantaggi**: Best ever tool to visualize large data with basic configuration even by UI steps, like data flows and variable flows. Much effective in statistic process control, prediction and forecasting. It’s my essential tool while planning and deep through into large data, Machine learning and prediction models are awesome usage while testing hypothesis models. User interface, graphs, are really helpful to determine full meaning of data, so in data mining and data science it is a worthy tool with cool UI with easy usage. Machine learning, data prediction further can be used with programming in AI and other automated detection tools. Performance is awesome working on data, very easy to install. > > **Inconvenienti**: Live visualization can’t be obtained from a database or data source, somehow it should be linked like simulated tool, like graph is running as data changing. Saas, domain or remotely usage is not available. Graphs can’t be further used in another presentation with data source, a screenshot is only can be copied. > > Used in human resource planning, need of training in human resource development. Analyzed visuals of unemployment vs employed life's essential to get motivational reforms. Used in finance settlement predictions. ----- ### "An Amazing Tool for Data Visualization, Machine Learning and Data Mining" — 5.0/5 > **Olga** | *31 agosto 2020* | Gestione formativa | Tasso di raccomandazione: 10.0/10 > > **Vantaggi**: I was using this program when I was doing my first Master's in Fundamental and Applied Linguistics, and the software turned out to be indispensable for my qualitative and quantitative research. I used the tool for lots of different operations, such as Linear Regressions, K-Means Clustering, working with Heat Map, Venn Diagram, t-SNE, Text Preprocessing, Topic Modelling, Concordance and Sentiment Analysis as well as working on Correlations and Data Tables. The most pleasant thing was that this software is compatible with Linux (mine was Ubuntu), but for some weird reason it worked better on Windows despite it should have liked more the native Python environment. However, it is really an outstanding tool, I really appreciate this great thing. I think it would be good if the developers worked on creating a more powerful version with paid subscriptions. Just an idea for the guys to consider in the future. > > **Inconvenienti**: I had experienced some problems with doing Sentiment Analysis using by Orange (there were some widget or plugin trouble, for some weird reason the Sentiment Analysis thing was working perfectly only with some specific sets of data and languages). > > That's splendid. I want to sincerely thank you. A great tool for researchers, scientists, Master's and PhD students, data scientists, and everyone who is keen on Data Mining, Machine Learning and Data Visualization. ----- ### "easy product selection, order, and checkout, to convenient online payment, shipping, and delivery—e" — 4.0/5 > **Salman** | *22 giugno 2021* | Prodotti tessili | Tasso di raccomandazione: 4.0/10 > > **Vantaggi**: Everything you need to start online today grow your business > > **Inconvenienti**: No one can buy during site crush Can't try before buy Highly competitive > > It's a good platform ----- ### "Orange is for non programmers who want to learn Machine Learning\!" — 4.0/5 > **Lisa** | *16 ottobre 2018* | Istruzione superiore | Tasso di raccomandazione: 8.0/10 > > **Vantaggi**: The graphical user interface of orange is great for someone who is not a programmer but wants to execute analytic workflows on machine learning on their dataset. The interface is nicely designed and the analytics workflow is easy to create with the use of drag and drop of its widgets. The widgets available are extensive and would enable users to clean, visualize, build models for supervised and unsupervised learning and validate their model. Orange has put together resources for its users to pick up machine learning on their own. There are also several tutorial videos as well on the website. > > **Inconvenienti**: We aren't able to set.seed in the software which causes results and analysis to not be reproducible. Orange does not provide enough parameters to tweak for advanced users. For instance, the randomForest widget does not allow the user to see which variables have the highest information gain. > > Overall my experience with Orange has been fruitful for me as I picked up machine learning concepts without allowing my basic coding knowledge to hinder me. The interface is prettier than weka(another GUI tool for machine learning) There are several preloaded datasets that has already been clean and users can take advantage of those and follow through the documentation that is provided. My favorite one is the titanic dataset that predicts if the person survives or not depending their gender, class and the number of siblings/spouses they have. ----- ### "Effective usage of data Visualization and Statistical ML models." — 4.0/5 > **Utente Verificato** | *7 agosto 2021* | Produzione di apparecchi elettrici/elettronici | Tasso di raccomandazione: 8.0/10 > > **Vantaggi**: Used in big data analysis, found extremely easier while getting data insights and prediction with a few basic configurations, graphs, charts of external data like excel, CSV, and MySQL table are supported to perform. Machine learning and statistical-based machine learning models are useful while working with AI/automation-based analysis, data flow with variables can be defined as draggable options, no huge coding is required, while for advanced scenarios coding options is also available. > > **Inconvenienti**: Graphics are poor formats, poor functions in charts, like histogram can not be modified after putting the data and variables, while even in excel its is configurable, support with ERPs is not available, some APIs type configuration should be available to work on ERPs data/ > > Overall found it useful while working on raw data, used in designing Electrical consumption of appliances, and assessment. ----- Pagina: 1/2\ Avanti: [Pagina successiva](https://www.capterra.it/software/164505/orange?page=2) ## Link - [Visualizza su Capterra](https://www.capterra.it/software/164505/orange) ## Questa pagina è disponibile nelle seguenti lingue | Lingua | URL | | de | | | de-AT | | | de-CH | | | en | | | en-AE | | | en-AU | | | en-CA | | | en-GB | | | en-IE | | | en-IL | | | en-IN | | | en-NZ | | | en-SG | | | en-ZA | | | es | | | es-AR | | | es-CL | | | es-CO | | | es-CR | | | es-DO | | | es-EC | | | es-MX | | | es-PA | | | es-PE | | | fr | | | fr-BE | | | fr-CA | | | fr-LU | | | it | | | pt | | | pt-PT | | ----- ## Dati strutturati