List of All Analytics Tools:-
KNIME Analytics Platform is the leading open solution for data-driven innovation, helping you discover the potential hidden in your data, mine for fresh insights, or predict new futures.
With more than 1000 modules, hundreds of ready-to-run examples, a comprehensive range of integrated tools, and the widest choice of advanced algorithms available, KNIME Analytics Platform is the perfect toolbox for any data scientist.
Much like KNIME, RapidMiner operates through visual programming and is capable of manipulating, analyzing and modeling data. RapidMiner makes data science teams more productive through an open source platform for data prep, machine learning, and model deployment. Its unified data science platform accelerates the building of complete analytical workflows – from data prep to machine learning to model validation to deployment – in a single environment, dramatically improving efficiency and shortening the time to value for data science projects.
This tool also include Fraud detection via analyzing financial data and other kind of data in any format.
What if I tell you that Project R, a GNU project, is written in R itself? It’s primarily written in C and Fortran. And a lot of its modules are written in R itself. It’s a free software programming language and software environment for statistical computing and graphics. The R language is widely used among data miners for developing statistical software and data analysis. Ease of use and extensibility has raised R’s popularity substantially in recent years.
Besides data mining it provides statistical and graphical techniques, including linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, and others.
Orange is open source data visualization and data analysis for novice and expert, and provides interactive workflows with a large toolbox to create interactive workflows to analyse and visualize data. Orange is packed with different visualizations, from scatter plots, bar charts, trees, to dendrograms, networks and heat maps.
OpenRefine (formerly Google Refine) is a powerful tool for working with messy data: cleaning it, transforming it from one format into another, and extending it with web services and external data. OpenRefine can help you explore large data sets with ease.
Pentaho addresses the barriers that block your organization’s ability to get value from all your data. The platform simplifies preparing and blending any data and includes a spectrum of tools to easily analyze, visualize, explore, report and predict. Open, embeddable and extensible, Pentaho is architected to ensure that each member of your team — from developers to business users — can easily translate data into value.
Talend is the leading open source integration software provider to data-driven enterprises. Our customers connect anywhere, at any speed. From ground to cloud and batch to streaming, data or application integration, Talend connects at big data scale, 5x faster and at 1/5th the cost.
Weka, an open source software, is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a data set or called from your own JAVA code. It is also well suited for developing new machine learning schemes, since it was fully implemented in the JAVA programming language, plus supporting several standard data mining tasks.
For someone who hasn’t coded for a while, Weka with its GUI provides easiest transition into the world of Data Science. Being written in Java, those with Java experience can call the library into their code as well.
NodeXL is a data visualization and analysis software of relationships and networks. NodeXL provides exact calculations. It is a free (not the pro one) and open-source network analysis and visualization software. It is one of the best statistical tools for data analysis which includes advanced network metrics, access to social media network data importers, and automation.
Gephi is also an open-source network analysis and visualization software package written in Java on the NetBeans platform. Think of the giant friendship maps you see that represent linkedin or Facebook connections. Gelphi takes that a step further by providing exact calculations.
11.Apache Spark
The University of California, Berkeley’s AMP Lab, developed Apache in 2009. Apache Spark is a fast large-scale data processing engine and executes applications in Hadoop clusters 100 times faster in memory and 10 times faster on disk. Spark is built on data science and its concept makes data science effortless. Spark is also popular for data pipelines and machine learning models development.
Spark also includes a library – MLlib, that provides a progressive set of machine algorithms for repetitive data science techniques like Classification, Regression, Collaborative Filtering, Clustering, etc.
Datawrapper is an online data-visualization tool for making interactive charts. Once you upload the data from CSV/PDF/Excel file or paste it directly into the field, Datawrapper will generate a bar, line, map or any other related visualization. Datawrapper graphs can be embedded into any website or CMS with ready-to-use embed codes. So many reporters and news organizations use Datawrapper to embed live charts into their articles. It is very easy to use and produces effective graphics.
Solver specializes in providing world-class financial reporting, budgeting and analysis with push-button access to all data sources that drive company-wide profitability. Solver provides BI360, which is available for cloud and on-premise deployment, focusing on four key analytics areas.
Qlik lets you create visualizations, dashboards, and apps that answer your company’s most important questions. Now you can see the whole story that lives within your data.
Tableau democratizes visualization in an elegantly simple and intuitive tool. It is exceptionally powerful in business because it communicates insights through data visualization. In the analytics process, Tableau’s visuals allow you to quickly investigate a hypothesis, sanity check your gut, and just go explore the data before embarking on a treacherous statistical journey.
Fusion TablesMeet Google Spreadsheets cooler, larger, and much nerdier cousin. Google Fusion tables is an incredible tool for data analysis, large data-set visualization, and mapping. Not surprisingly, Google’s incredible mapping software plays a big role in pushing this tool onto the list. Take for instance this map, which I made to look at oil production platforms in the Gulf of Mexico.
Infogram offers over 35 interactive charts and more than 500 maps to help you visualize your data beautifully. Create a variety of charts including column, bar, pie, or word cloud. You can even add a map to your infographic or report to really impress your audience.
Sentiment Tools
The OpenText Sentiment Analysis module is a specialized classification engine used to identify and evaluate subjective patterns and expressions of sentiment within textual content. The analysis is performed at the topic, sentence, and document level and is configured to recognize whether portions of text are factual or subjective and, in the latter case, if the opinion expressed within these pieces of content are positive, negative, mixed, or neutral.
Semantria is a tool that offers a unique service approach by gathering texts, tweets, and other comments from clients and analyzing them meticulously to derive actionable and highly valuable insights. Semantria offers text analysis via API and Excel plugin. It differs from Lexalytics in that it is offered via API and Excel plugin, and in that it incorporates a bigger knowledge base and uses deep learning.
Trackur’s automated sentiment analysis looks at the specific keyword you are monitoring and then determines if the sentiment towards that keyword is positive, negative or neutral with the document. That’s weighted the most in Trackur algorithm. It could use to monitor all social media and mainstream news, to gain executive insights through trends, keyword discovery, automated sentiment analysis and influence scoring.
SAS sentiment analysis automatically extracts sentiments in real time or over a period of time with a unique combination of statistical modeling and rule-based natural language processing techniques. Built-in reports show patterns and detailed reactions. So you can hone in on the sentiments that are expressed.
With ongoing evaluations, you can refine models and adjust classifications to reflect emerging topics and new terms relevant to your customers, organization or industry.
I like your blog, I read this blog please update more content on hacking,Nice post
ReplyDeleteData Science online Training
Thank you because you have been willing to share information with us. we will always appreciate all you have done here because I know you are very concerned with our. install tensorflow anaconda
ReplyDelete