55,503 research outputs found
Business Intelligence, Analytics And Data Visualization: A Heat Map Project Tutorial
Business intelligence and analytics (BI&A) initiatives are helping countless organizations harness and interpret the vast amount of information available in the world today. The explosion of BI&A in industry has fueled the high demand for knowledge workers with advanced analytical skills. The purpose of this paper is to introduce a data visualization project tutorial for Information Systems (IS) education. The applied BI&A tutorial was designed to help students learn how to create and analyze a heat map using SQL Server Data Tools (SSDT) and SQL Server Reporting Services (SSRS). Students learn how to make decisions based on large amounts of data by presenting it in visual form. This tutorial exposes students to the decision-making power derived from data visualization. Utilizing the 5E Instructional Model, the tutorial assists in the development of BI&A professionals who can quickly make sense of mass amounts of data, identify trends buried within data sets, and are skilled in making sound decisions that add value to organizations
Teaching Business Intelligent with an Executive Dashboard
Data visualization has been an important tool for company executives to obtain timely information for decision making purposes. This tutorial session use a state-of-art executive dashboard system to showcase how data visualization can be presented in a classroom environment. Sample cases and datasets are available for participants to take home for their own teaching purposes
Business Information Visualization
With the flood of data produced by today\u27s information systems, something must be done to allow business decision-makers to extract the information the data contains. The recent advances in visualization technologies provide the capability to begin to use human visual/spatial abilities to solve the abstract problems found in business. If business problems can be visualized with an appropriate representation, then it may be possible to use innate spatial/visual abilities to allow the business decision-maker to separate the wheat from the chaff. This tutorial surveys the issues related to applying visualization technologies to business problem solving
Seeing is believing: the importance of visualization in real-world machine learning applications
The increasing availability of data sets with a huge amount of information, coded in many diff erent features, justifi es the research on new methods of knowledge extraction: the great challenge is the translation of the raw data into useful information that can be used to improve decisionmaking processes, detect relevant profi les, fi nd out relationships among features, etc. It is undoubtedly true that a picture is worth a thousand words, what makes visualization methods be likely the most appealing and one of the most relevant kinds of knowledge extration methods. At ESANN 2011, the special session "Seeing is believing: The importance of
visualization in real-world machine learning applications" reflects some of the main emerging topics in the field. This tutorial prefaces the session, summarizing some of its contributions, while also providing some clues to the current state and the near future of visualization methods within the
framework of Machine Learning.Postprint (published version
CURRENT STATUS AND FUTURE GOALS OF THE GLOBAL CC2020 PROJECT: INTERACTIVE TUTORIAL
The purpose of this tutorial is to give the conference participants an update on the current status and future goals of the global CC2020 project. It will also provide the SIGED community with an opportunity to participate in a discussion that gives the CC2020 steering committee qualitative feedback, contributing directly to the outcomes of the project. The tutorial will actively solicit participant contributions and serve as an important mechanism for interaction between the project and the SIGED community. The topics will include a) general introduction to the project and its goals; b) use of competencies as common currency for curriculum analysis; c) use of visualization to compare computing degree programs; and d) lessons for the information systems discipline from the CC2020 project
Adaptive Information Visualization for Personalized Access to Educational Digital Libraries
Personalization is one of the emerging ways to increase the power of modern Digital Libraries. The Knowledge Sea II system presented in this paper explores social navigation support, an approach for providing personalized guidance within the open corpus of educational resources. Following the concepts of social navigation we have attempted to organize a personalized navigation support that is based on past learners’ interaction with the system. The study indicates that Knowledge Sea II became the students' primary tool for accessing the open corpus documents used in a programming course. The social navigation support implemented in this system was considered useful by students participating in the study of Knowledge Sea II. At the same time, some user comments indicated the need to provide more powerful navigational support, such as the ability to rank the usefulness of a page
PCA and K-Means decipher genome
In this paper, we aim to give a tutorial for undergraduate students studying
statistical methods and/or bioinformatics. The students will learn how data
visualization can help in genomic sequence analysis. Students start with a
fragment of genetic text of a bacterial genome and analyze its structure. By
means of principal component analysis they ``discover'' that the information in
the genome is encoded by non-overlapping triplets. Next, they learn how to find
gene positions. This exercise on PCA and K-Means clustering enables active
study of the basic bioinformatics notions. Appendix 1 contains program listings
that go along with this exercise. Appendix 2 includes 2D PCA plots of triplet
usage in moving frame for a series of bacterial genomes from GC-poor to GC-rich
ones. Animated 3D PCA plots are attached as separate gif files. Topology
(cluster structure) and geometry (mutual positions of clusters) of these plots
depends clearly on GC-content.Comment: 18 pages, with program listings for MatLab, PCA analysis of genomes
and additional animated 3D PCA plot
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