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Title Date Added Company

Visualization of Host Behavior for Network Security 2008-05-30 University of Konstanz

Monitoring host behavior in a network is one of the most essential tasks in the fields of network monitoring and security since more and more malicious code in the wild internet constantly threatens the network infrastructure. This paper presents a visual analytics tool that visualizes network host behavior through positional changes in a two dimensional space using a force-directed graph layout algorithm. The tool's interaction capabilities allow for visual exploration of network traffic over time and are demonstrated using netflow data as well as IDS alerts. Automatic accentuation of hosts with highly variable traffic results in fast hypothesis generation and confirmation of suspicious host behavior. By triggering the behavior graph from the HNMap tool, one is able to monitor more abstract network entities.

Tags: Network Security, Security Management

Mining@home: Public Resource Computing for Distributed Data Mining 2008-05-09 University of Calabria

Several kinds of scientific and commercial applications require the execution of a large number of independent tasks. One highly successful and low cost mechanism for acquiring the necessary compute power for these applications is the "Public-resource computing", or "Desktop Grid" paradigm, which exploits the computational power of private computers. So far, this paradigm has not been applied to data mining applications for two main reasons. This paper focuses on one of the main data mining problem: the extraction of closed frequent itemsets from transactional databases. They show that is possible to decompose this problem into independent tasks, which however need to share a large volume of data.

Tags: File and Network Servers, Data Mining - Analysis

Extreme Business Warehousing: 60 Terabytes and Beyond 2008-04-01 IBM

This paper covers the design criteria and implementation of an SAP NetWeaver Business Intelligence (SAP BI) system of extreme size, under massive online load, and with very demanding availability requirements. The proof of concept documented here is based on real customer data, business processes and business needs. It shows the how the application, infrastructure and middleware can scale-out to meet the most extreme business requirements, therefore the name "Extreme Business Warehousing".

What's New in SAS Web Report Studio 4.2 2008-03-24 SAS Institute

Web Report Studio is a web-based reporting tool with many capabilities added over the course of three major releases. The upcoming release adds many new features driven by requests from users. This paper organizes the key capabilities in Web Report Studio 4.2 into categories. Virtually all features affect the user interface, and the first section describes key UI enhancements that are designed to improve the user experience. New prompting makes reporting more flexible for consumers and can minimize the number of reports needed. OLAP cubes enable fast navigation of the data, and enhancements will get the specific rollups one need. Visualization helps one understand report information quickly, and Web Report Studio 4.2 includes a number of graph enhancements, such as annotated reference lines.

Tags: Business Intelligence - Data Warehousing, Web Reporting

Controlling OLAP Applications End to End 2008-03-24 SAS Institute

In SAS 9.2, there are several new features that help administrators to secure and control the use of OLAP Cubes in a reporting environment. This paper highlights the following new and existing features: ability to include or exclude members from aggregated values (parent values), member Level Security user interface, subsetting report data using Information Map Filters and roles controlling report functionality.

Tags: Database Management, Business Intelligence - Data Warehousing

What's New in SAS OLAP Cube Studio 4.2 2008-03-24 SAS Institute

With the release of SAS 9.2, new functionality and enhancements have been added to SAS OLAP Cube Studio 4.2. New features include the ability to: update a cube (incremental update), view an input data set within SAS OLAP Cube Studio, view a cube to validate the build process, set cube security in SAS OLAP Cube Studio including a UI for member level security and automatically generate suggested time hierarchies based on a single date column. This paper will highlight and demonstrate the new functionality and the benefits that the user will have with SAS OLAP Cube Studio 4.2.

Tags: Business Intelligence - Data Warehousing

Adding Data Mining Support to SPARQL Via Statistical Relational Learning Methods 2008-03-17 University of Zurich

Exploiting the complex structure of relational data enables to build better models by taking into account the additional information provided by the links between objects. The paper extends this idea to the Semantic Web by introducing the novel SPARQL-ML approach to perform data mining for Semantic Web data. The approach is based on traditional SPARQL and statistical relational learning methods, such as Relational Probability Trees and Relational Bayesian Classifiers. The paper analyzes the approach thoroughly conducting three sets of experiments on synthetic as well as real-world data sets. The analytical results show that the approach can be used for any Semantic Web data set to perform instance-based learning and classification.

Tags: Learning Management Systems

Migrating Your SAS Applications to SAS 9.1.3 and Beyond 2008-03-14 SAS Institute

One has heard about the new features of SAS9, but one has several mission critical SAS 8 applications written with products that are no longer being talked about (i.e., SAS/IntrNet and SAS/AF software). One would like to be able to move these applications forward to SAS 9 so that they can work with the full-featured Business Intelligence, Data Integration, and a multitude of analytical solutions that are part of the SAS 9.1.3 Intelligence Platform. This paper describes the steps to do this migration along with some tips and tricks to ensure that ones SAS 8 application behaves nicely in SAS 9.

Tags: Upgrades and Migration

Assessments - A Mandatory BI/DW Pit Stop 2008-03-13 Investcorp

In the current competitive business environment, a successful data warehousing organization may well be the successful business enterprises of the future. A reflection on the millions of dollars spent on Business Intelligence/Data Warehousing (BI/DW) solutions by individual organizations, that has yielded less than expected ROI and the burgeoning TCO for these organizations to maintain those solutions is enough to make people focus on what needs to be done better. Even in a traditional factory setup, there is a practice of reviewing the health of the equipment by monitoring critical parameters like vibration, noise-level, wear and tear limits etc., as well as a rigorously adhered to preventive maintenance schedule.

Tags: ROI - TCO

Evaluating Predictive Models: Computing and Interpreting the c Statistic 2008-03-13 SAS Institute

Automation of predictive model selection has become the alchemy of today's Business Intelligence (BI), with BI practitioners hoping to transform jargon and acronyms into gold. While statistical modeling experts disparage 'Black-box' methods, business analysts tend to ignore theory and traditional model diagnostics, and rely on 'Lift' or 'Gain' charts; that is, evidence of improved accuracy of predictions of outcomes for groups, often represented graphically by Area Under Curve (AUC) of signal detection Receiver Operating Characteristic (ROC) plots. Even where interest in competitive advantage overrides concern for meaningful model parameter estimates, a concordance c statistic offers a simpler and more intuitive measure of accuracy of model predictions. SAS/Stat PROCs LOGISTIC and SURVEYLOGISTIC generate a c statistic.

Tags: Business Intelligence - Data Warehousing

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Title	Date Added	Company
Visualization of Host Behavior for Network Security	2008-05-30	University of Konstanz
Monitoring host behavior in a network is one of the most essential tasks in the fields of network monitoring and security since more and more malicious code in the wild internet constantly threatens the network infrastructure. This paper presents a visual analytics tool that visualizes network host behavior through positional changes in a two dimensional space using a force-directed graph layout algorithm. The tool's interaction capabilities allow for visual exploration of network traffic over time and are demonstrated using netflow data as well as IDS alerts. Automatic accentuation of hosts with highly variable traffic results in fast hypothesis generation and confirmation of suspicious host behavior. By triggering the behavior graph from the HNMap tool, one is able to monitor more abstract network entities. Tags: Network Security, Security Management
Mining@home: Public Resource Computing for Distributed Data Mining	2008-05-09	University of Calabria
Several kinds of scientific and commercial applications require the execution of a large number of independent tasks. One highly successful and low cost mechanism for acquiring the necessary compute power for these applications is the "Public-resource computing", or "Desktop Grid" paradigm, which exploits the computational power of private computers. So far, this paradigm has not been applied to data mining applications for two main reasons. This paper focuses on one of the main data mining problem: the extraction of closed frequent itemsets from transactional databases. They show that is possible to decompose this problem into independent tasks, which however need to share a large volume of data. Tags: File and Network Servers, Data Mining - Analysis
Extreme Business Warehousing: 60 Terabytes and Beyond	2008-04-01	IBM
This paper covers the design criteria and implementation of an SAP NetWeaver Business Intelligence (SAP BI) system of extreme size, under massive online load, and with very demanding availability requirements. The proof of concept documented here is based on real customer data, business processes and business needs. It shows the how the application, infrastructure and middleware can scale-out to meet the most extreme business requirements, therefore the name "Extreme Business Warehousing".
What's New in SAS Web Report Studio 4.2	2008-03-24	SAS Institute
Web Report Studio is a web-based reporting tool with many capabilities added over the course of three major releases. The upcoming release adds many new features driven by requests from users. This paper organizes the key capabilities in Web Report Studio 4.2 into categories. Virtually all features affect the user interface, and the first section describes key UI enhancements that are designed to improve the user experience. New prompting makes reporting more flexible for consumers and can minimize the number of reports needed. OLAP cubes enable fast navigation of the data, and enhancements will get the specific rollups one need. Visualization helps one understand report information quickly, and Web Report Studio 4.2 includes a number of graph enhancements, such as annotated reference lines. Tags: Business Intelligence - Data Warehousing, Web Reporting
Controlling OLAP Applications End to End	2008-03-24	SAS Institute
In SAS 9.2, there are several new features that help administrators to secure and control the use of OLAP Cubes in a reporting environment. This paper highlights the following new and existing features: ability to include or exclude members from aggregated values (parent values), member Level Security user interface, subsetting report data using Information Map Filters and roles controlling report functionality. Tags: Database Management, Business Intelligence - Data Warehousing
What's New in SAS OLAP Cube Studio 4.2	2008-03-24	SAS Institute
With the release of SAS 9.2, new functionality and enhancements have been added to SAS OLAP Cube Studio 4.2. New features include the ability to: update a cube (incremental update), view an input data set within SAS OLAP Cube Studio, view a cube to validate the build process, set cube security in SAS OLAP Cube Studio including a UI for member level security and automatically generate suggested time hierarchies based on a single date column. This paper will highlight and demonstrate the new functionality and the benefits that the user will have with SAS OLAP Cube Studio 4.2. Tags: Business Intelligence - Data Warehousing
Adding Data Mining Support to SPARQL Via Statistical Relational Learning Methods	2008-03-17	University of Zurich
Exploiting the complex structure of relational data enables to build better models by taking into account the additional information provided by the links between objects. The paper extends this idea to the Semantic Web by introducing the novel SPARQL-ML approach to perform data mining for Semantic Web data. The approach is based on traditional SPARQL and statistical relational learning methods, such as Relational Probability Trees and Relational Bayesian Classifiers. The paper analyzes the approach thoroughly conducting three sets of experiments on synthetic as well as real-world data sets. The analytical results show that the approach can be used for any Semantic Web data set to perform instance-based learning and classification. Tags: Learning Management Systems
Migrating Your SAS Applications to SAS 9.1.3 and Beyond	2008-03-14	SAS Institute
One has heard about the new features of SAS9, but one has several mission critical SAS 8 applications written with products that are no longer being talked about (i.e., SAS/IntrNet and SAS/AF software). One would like to be able to move these applications forward to SAS 9 so that they can work with the full-featured Business Intelligence, Data Integration, and a multitude of analytical solutions that are part of the SAS 9.1.3 Intelligence Platform. This paper describes the steps to do this migration along with some tips and tricks to ensure that ones SAS 8 application behaves nicely in SAS 9. Tags: Upgrades and Migration
Assessments - A Mandatory BI/DW Pit Stop	2008-03-13	Investcorp
In the current competitive business environment, a successful data warehousing organization may well be the successful business enterprises of the future. A reflection on the millions of dollars spent on Business Intelligence/Data Warehousing (BI/DW) solutions by individual organizations, that has yielded less than expected ROI and the burgeoning TCO for these organizations to maintain those solutions is enough to make people focus on what needs to be done better. Even in a traditional factory setup, there is a practice of reviewing the health of the equipment by monitoring critical parameters like vibration, noise-level, wear and tear limits etc., as well as a rigorously adhered to preventive maintenance schedule. Tags: ROI - TCO
Evaluating Predictive Models: Computing and Interpreting the c Statistic	2008-03-13	SAS Institute
Automation of predictive model selection has become the alchemy of today's Business Intelligence (BI), with BI practitioners hoping to transform jargon and acronyms into gold. While statistical modeling experts disparage 'Black-box' methods, business analysts tend to ignore theory and traditional model diagnostics, and rely on 'Lift' or 'Gain' charts; that is, evidence of improved accuracy of predictions of outcomes for groups, often represented graphically by Area Under Curve (AUC) of signal detection Receiver Operating Characteristic (ROC) plots. Even where interest in competitive advantage overrides concern for meaningful model parameter estimates, a concordance c statistic offers a simpler and more intuitive measure of accuracy of model predictions. SAS/Stat PROCs LOGISTIC and SURVEYLOGISTIC generate a c statistic. Tags: Business Intelligence - Data Warehousing