Sas tool for data mining

Visually explore data, and create and share smart visualizations and interactive reports through a single, self-service interface. Take advantage of generative adversarial networks GANs to generate synthetic data, both image and tabular, for your deep learning models. Automatically generate insights, including summary reports about a project and champion and challenger models.

Simple language from embedded natural language generation facilitates report interpretation and reduces the learning curve for business analysts. Share modeling insights via a PDF report. Assess models for both performance and results bias relative to specified groups. Take advantage of reinforcement learning — through Fitted Q-Networks, Deep Q-Networks or Actor-Critic — to solve sequential decision-making problems, with support for custom environments.

Interactively adjust the splitting and pruning of decision tree nodes to reflect your business knowledge and enforce regulatory constraints. Save time and improve productivity. Automated feature engineering selects the best set of features for modeling by ranking them to indicate their importance in transforming data.

Visual pipelines are dynamically generated from your data, yet editable to remain a white box model. Take advantage of the public API for automated modeling for end-to-end model development and deployment simply by choosing the automation option. Or use this API to build and deploy your own custom predictive modeling applications. See examples on developer. Best practices templates enable a quick, consistent start to building models, ensuring consistency among the analytics team. Analytical capabilities include clustering, different types of regression, random forest, gradient boosting models, support vector machines, natural language processing, topic detection, etc.

Augment data mining and machine learning approaches using a versatile set of network algorithms to explore the structure of networks — social, financial, telco and others — that are explicitly or implicitly part of business data. Get concurrent access to data in memory in a secure, multiuser environment. Distributes data and analytical workload operations across nodes — in parallel — multithreaded on each node for very fast speeds.

Acquire and analyze images with model deployment on server, edge or mobile. Supports the end-to-end flow for analyzing biomedical images, including annotating images. SAS Viya has a completely redesigned architecture that is compact, cloud native and fast. Whether you prefer to use the SAS Cloud or a public or private cloud provider, you'll be able to make the most of your cloud investment.

Conquer all your analytics challenges — from experimental to mission critical — with faster decisions in the cloud. The latest release of SAS Viya is now available on these cloud providers. Microsoft is our strategic partner and preferred cloud provider.

With deep integration and a shared road map, SAS and Microsoft are shaping the future of AI and analytics in the cloud. Try SAS for Free.

Solve the most complex analytical problems with a single, integrated, collaborative solution — now with its own automated modeling API. Enable everyone to work in the same integrated environment — from data management to model development and deployment. Easily solve complex analytical problems with automated insights. Telecom, media and technology companies can use analytic models to make sense of mountains of customers data, helping them predict customer behavior and offer highly targeted and relevant campaigns.

With analytic know-how, insurance companies can solve complex problems concerning fraud, compliance, risk management and customer attrition. Companies have used data mining techniques to price products more effectively across business lines and find new ways to offer competitive products to their existing customer base.

With unified, data-driven views of student progress, educators can predict student performance before they set foot in the classroom — and develop intervention strategies to keep them on course. Data mining helps educators access student data, predict achievement levels and pinpoint students or groups of students in need of extra attention. Aligning supply plans with demand forecasts is essential, as is early detection of problems, quality assurance and investment in brand equity.

Manufacturers can predict wear of production assets and anticipate maintenance, which can maximize uptime and keep the production line on schedule. Automated algorithms help banks understand their customer base as well as the billions of transactions at the heart of the financial system.

Data mining helps financial services companies get a better view of market risks, detect fraud faster , manage regulatory compliance obligations and get optimal returns on their marketing investments. Large customer databases hold hidden customer insight that can help you improve relationships, optimize marketing campaigns and forecast sales.

Through more accurate data models, retail companies can offer more targeted campaigns — and find the offer that makes the biggest impact on the customer. SAS data mining software uses proven, cutting-edge algorithms designed to help you solve your biggest challenges.

Descriptive Modeling : It uncovers shared similarities or groupings in historical data to determine reasons behind success or failure, such as categorizing customers by product preferences or sentiment. Sample techniques include:. Predictive Modeling : This modeling goes deeper to classify events in the future or estimate unknown outcomes — for example, using credit scoring to determine an individual's likelihood of repaying a loan. Predictive modeling also helps uncover insights for things like customer churn , campaign response or credit defaults.

Prescriptive Modeling : With the growth in unstructured data from the web, comment fields, books, email, PDFs, audio and other text sources, the adoption of text mining as a related discipline to data mining has also grown significantly.

You need the ability to successfully parse, filter and transform unstructured data in order to include it in predictive models for improved prediction accuracy. In the end, you should not look at data mining as a separate, standalone entity because pre-processing data preparation, data exploration and post-processing model validation, scoring, model performance monitoring are equally essential. Prescriptive modelling looks at internal and external variables and constraints to recommend one or more courses of action — for example, determining the best marketing offer to send to each customer.

Data Mining Solutions. Why is data mining important? Data mining allows you to: Sift through all the chaotic and repetitive noise in your data. Understand what is relevant and then make good use of that information to assess likely outcomes. DataMelt is a free to use tool for numeric computation, mathematics, data analysis, and data visualization. This program offers you the simplicity of scripting languages, like Python, Ruby, Groovy with the power of hundreds of Java packages.

ELKI is an open source data mining tool written in Java. The tool allows us researching algorithms, with an emphasis on unsupervised methods in cluster analysis and outlier detection. SPMF is an open-source data mining library written in Java. It is distributed under the GPL license. It allows you to integrate source code with other Java Software. Alteryx is a Business intelligence and analytics solutions for the enterprise. It is a specially designed tool for data analyst and business leaders.

Enterprise Miner is a SAS software which offers you and cutting-edge algorithms designed to help you solve the most significant challenges and offers the best solutions for your business.

Datawatch Desktop is a Data mining and business intelligence solution. It allows you to focus on real-time data visualization. It offers tools to build and deploy their monitoring and analysis systems without the need to write a single line of code. An advanced miner is a useful tool for data processing, analysis, and modeling. Its user-friendly workflow interface allows you to explore various types of data. Analytic Solver is free to use the point-and-click tool.

It allows you to do risk analysis and prescriptive analytics in your browser. It offers full-power Data mining jobs. PolyAnalyst is the Data mining and analytical tool for extracting actionable knowledge hidden and actual structured of the data.

Civis empowering you to make informed decisions with data scientist and decision market in mind. It allows your team to collaborate efficiently and find solutions faster.

Viscovery is a workflow-oriented software suite. It is based on self-organizing maps and multivariate statistics for explorative data mining and predictive modeling. The system excels in intuitive user-guidance, mature implementation. A Data mining tool is a software application that is used to discover patterns and trends from large sets of data and transform those data into more refined information.