Now, Data Mining Is Within Your Reach

Transcription

1 Clementine Desktop Specifications Now, Data Mining Is Within Your Reach Data mining delivers significant, measurable value. By uncovering previously unknown patterns and connections in data, data mining enables your organization to improve business processes and make the right decisions at the right time. To help small and midsized organizations and business units within larger organizations realize the benefits of data mining, SPSS Inc. offers Clementine Desktop. Like Clementine, our industry-leading data mining solution, Clementine Desktop combines advanced analytical techniques with an easy-to-use, visual interface and fully supports the CRoss-Industry Standard Process for Data Mining (CRISP-DM), the de facto standard methodology. Streamline the data mining process Clementine Desktop provides the support you need at every step of the data mining process. Using it, you can: Directly access data in SPSS or SAS files, in Microsoft Excel spreadsheets, in flat files, and in SPSS Dimensions survey products; and access data in other programs or databases through ODBC Manipulate data in a wide variety of ways Visualize your data at every step of the process Create and validate your models Deliver results in a variety of formats, including SPSS, SAS, Excel, and through ODBC However, because it does not require server software, Clementine Desktop can be installed quickly on a personal computer so you can begin mining your data right away. You can choose the base product alone or combine it with additional modules that offer capabilities suited to the problem you want to address. Clementine Desktop is designed with business users in mind, so you don t need to be an expert in data mining to enjoy its benefits.

2 Meet your business challenges Clementine Desktop uses advanced statistical and machine learning techniques. So whatever business challenges your organization faces, you can rely on Clementine Desktop to help you meet them. For example: A business-to-business manufacturer has only a few hundred customers but finds that there are many differences among those customers. These include order size, products purchased, seasonal demand, payment history, and customer service needs. By analyzing this complex dataset, Clementine Desktop helps the manufacturer customize its product pricing and other marketing efforts and maintain more mutually satisfactory customer relationships. A regional bank wants to up-sell and cross-sell additional financial products to its customer base of 50,000 accounts. Its first step is to understand what kinds of customers are likely to be interested in these products and when they are likely to make a purchase. Matching past purchasing patterns to customer attributes and attitudes reveals several segments that may be receptive to up-sell and cross-sell efforts. This insight enables the bank to better direct customer interactions and achieve desired results more cost effectively. A regional property and casualty insurer wants to understand how to better focus its marketing efforts in order to attract customers who are likely to be loyal and profitable. The company has data describing current customers according to a number of attributes, such as age, address, claims filed, payments made, payments received, and enrollment date. By surveying these customers and learning more about their preferred media and methods of contact, and combining this information with other customer data, the company can develop profiles that increase the cost effectiveness of its marketing campaigns. A university hospital recognizes that information technology improvements can improve the quality of patient care. The hospital has created a central database of patient data that includes detailed descriptions of symptoms, diagnoses, and treatments. While fully protecting its patients privacy, the hospital can mine this data and identify the factors that influence the success rates of specific treatment regimens. A state university wants to encourage students to remain enrolled in its programs. It analyzes enrollment data at one of its campuses to determine what effect changes in course offerings, scheduling, or financial aid packages have on student retention. The results are then evaluated to determine how beneficial it would be to conduct similar analyses across the entire university system.

3 A pathway to broader capabilities Whatever type of data mining your organization needs to do, Clementine can help you carry it out. For example, if you currently use SPSS AnswerTree to develop decision-tree models, you gain a wider set of data mining capabilities by moving to Clementine Trees or Clementine Desktop. SPSS then makes it easy for you to move to our more enterprise-scale data mining offerings as your experience with data mining and its benefits grows. When you want to extend the benefits of data mining across geographic or functional lines, or engage in additional types of data mining projects, you can move to SPSS Clementine Server data mining software. Because it uses client/server architecture, Clementine Server supports a larger number of data analysts and efficiently processes larger amounts of data. You can also deploy results more efficiently with Clementine Server. Advanced features of SPSS text mining solution, such as Text Link Analysis for identifying opinions, relationships, and events, are available only through Clementine Server. A complementary product, SPSS Predictive Enterprise Services, enables you to centralize the storage and management of predictive models. This increases productivity and improves the consistency of your data mining projects. Other SPSS offerings enable you to deploy scores and predictive insights directly to operational systems. A Comparison of SPSS Data Mining Products Functionality Additional types of data Text Mining for Clementine Desktop Clementine Desktop Base and optional additional modules Additional types of data Text Mining for Clementine Web Mining for Clementine Deployment SPSS predictive applications Clementine Batch, Clementine Solution Publisher, Cleo TM Clementine Server Analytics management SPSS Predictive Enterprise Services Clementine Desktop can efficiently analyze the amounts of data that small to midsized organizations typically generate. You can add some text mining capabilities and even integrate data from SPSS Dimensions survey research products. If you need to process larger amounts of data or add advanced deployment or model management capabilities, you can easily migrate your data and models to other SPSS products. Clementine Trees AnswerTree Volume of data, number of users, number of projects

4 Focus on knowledge discovery With Clementine Desktop, your business knowledge guides the process. The product s intuitive graphical interface makes it easy to visualize every step of the data mining process as part of a stream. You don t need to write code; instead, you can focus on knowledge discovery and pursue train-of-thought analysis. This leads to data mining productivity and a faster achievement of your business goals. Clementine Desktop and its modules were designed so you can choose exactly what you need to address your particular business problems. You have all the power and versatility you need at your fingertips. You can integrate data from surveys conducted with any Dimensions product. Plus, with Clementine Desktop 10.1, you can access and analyze text data. Analyzing text adds another dimension to data mining, improving the lift or accuracy of predictive data models and significantly improving your results. Be guided by experience For more than a decade, SPSS has helped many types of organizations conduct data mining. We ve helped them achieve a variety of objectives, including growing sales revenues, improving patient outcomes, fighting crime, developing school curricula, and managing public programs. We know which algorithms and techniques are most suited to each type of business goal and type of data.

5 The versatility you need Clementine Desktop Base Includes the classification and regression tree (C&RT) algorithm, K-means clustering, GRI association, factor/pca data reduction, and linear regression. The base product provides sufficient analytical options for many typical data mining problems, but additional capabilities are available in other modules. The Clementine Desktop Classification Module Includes the CHAID, QUEST, and C5.0 decision tree and rule set algorithms and enables you to automatically identify the most- and least-relevant fields for a particular analysis. It also includes neural network multi-layer perceptrons, radial basis function networks, and logistic regression. This module provides the results you need if your problem involves prediction or classification: for instance, predicting the propensity of customers to respond, buy, or churn; and forecasting demand or sales revenues. The Clementine Desktop Segmentation Module Includes Kohonen Network and TwoStep clustering algorithms and an Anomaly Detection algorithm. These enable you to get the best results when discovering groups with similar characteristics or detecting unusual or suspicious cases. The Clementine Desktop Association Module Offers the Apriori and CARMA association algorithms and the Sequence sequential association algorithm. These algorithms enable you to find links between items, such as in market-basket analysis, or linked sequences of actions, such as Web content usage. Text Mining for Clementine Desktop Enables you to extract key concepts from free-text sources such as call center notes, open-ended surveys, s, blogs, Web pages, and documents. You can then analyze these concepts, using visualization and data mining techniques, and combine them with structured data to identify new patterns or to refine existing predictive models. Text Mining for Clementine Desktop uses SPSS sophisticated linguistic extraction technology. Integration of data from SPSS Dimensions products Enables you to include demographic and attitudinal information gained through survey research in your data mining models. This improves the accuracy of your models and helps you obtain a more complete understanding of your customers. To determine which combination is appropriate for your needs, please contact your SPSS representative.

6 Features The Clementine Desktop Base product supports the following operations: Data Sources Access files, tables, or text: Databases Tables and SQL queries via ODBC Flat files Delimiter-based or position-based flat data files SPSS files SAV files used by SPSS statistical products SAS files Data from SAS systems Dimensions Data from SPSS Dimensions databases or files Text Data in s, Web pages, documents, and database notes User input Generate test data according to a user-supplied specification Data manipulation, record level Select and transform data based on whole records: Select Select or discard records that match an expression Sample Select a random or regular sample of records Balance Sample or copy records to produce balanced datasets Aggregate Summarize data fields and counting with key fields Sort Perform multiple-key ascending and descending sorts Merge Join multiple tables or data streams together by order or key Append Append multiple tables or data streams together end to end Distinct Select or discard duplicate records Data manipulation, field level Manipulate and transform data based on fields: Type Examine and control metadata Filter Select data fields and rename them Derive Create new fields Filler Modify the contents of fields Reclassify Apply mappings to transform categorical fields Binning Partition numeric fields into sub-ranges Partition Partition datasets into training, test, and verification subsets Set-to-Flag, Restructure, and Transpose Restructure data (for instance, for market-basket analysis) Time Intervals Prepare data for time-series analysis History Create history data in time-series Field Reorder Change the order of fields Visualization Graphing operations with interactive graphical data selection and overlays: Plot Scatterplots (2D and 3D) and line plots with paneling Distribution Bar chart for categorical data with normalization Histogram Bar chart for numeric data with normalization Collection Aggregating bar chart for numeric data with normalization Web Link analysis chart Multiplot Multiple line plot Evaluation Model evaluation, including lift, gains, response, ROI, and profit charts Time Plot Visualize time-series data Note: Clementine Desktop includes the Advanced Visualization for Clementine add-on package. This package includes pie charts, bar charts, box plots, heat maps, panel plots, maps, scatterplot matrix and link analysis charts, and parallel coordinate graphics. Modeling Clementine Desktop Base module includes the following algorithms: C&RT Classification and regression trees, including interactive tree building K-means Clustering GRI Generalized rule induction association discovery algorithm Factor/PCA Data reduction using factor analysis and principal component analysis Linear Regression Best-fit linear equation modeling Output Screen display and data export operations: Table Display a table of data with interactive selection Matrix Crosstabulation Analysis Predictive model evaluation report Data Audit At-a-glance graphical and statistical summary of a dataset Statistics Univariate statistics and correlations Means Statistical tests for comparing means Quality Data quality report summarizing missing data Report Create template-based reports Set Globals Set internal global data properties Database Output to databases via ODBC links Flat File Create data files Export Export data in SAV or SAS file formats, or export to Microsoft Excel SPSS Procedure Invoke SPSS statistical operations Note: Publisher Node is not included in Clementine Desktop. The Clementine Desktop Classification Module includes: CHAID, QUEST, and C5.0 decision tree and rule set algorithms Multi-layer perceptrons Radial basis function networks Logistic regression The Clementine Desktop Segmentation Module includes: Kohonen Network and TwoStep clustering algorithms Anomaly Detection algorithm The Clementine Desktop Association Module includes: The Apriori and CARMA association algorithms The Sequence sequential association algorithm Text Mining for Clementine Desktop provides the following capabilities: Processing of text in many common formats, including plain text, HTML, XML, PDF, and Microsoft Office document formats Analysis of text in English, French, Italian, Spanish, German, or Dutch Text Mining Builder (for customizing dictionaries) can be purchased separately Note: Text Link Analysis and the Language Weaver translation node for Arabic, Chinese, and Persian are not available in Text Mining for Clementine Desktop but are available in Text Mining for Clementine. Clementine Trees is a separate product, similar to Clementine Desktop but including only modeling algorithms based on decision trees: C&RT, CHAID, QUEST, and C5.0. Features subject to change based on final product release. To learn more, please visit For SPSS office locations and telephone numbers, go to SPSS is a registered trademark and the other SPSS products named are trademarks of SPSS Inc. All other names are trademarks of their respective owners SPSS Inc. All rights reserved. CLMD10SPC-0306