http://hdl.handle.net/123456789/456 Collection of seminar series and workshop presentations by SITC Fri, 17 Jul 2026 11:03:38 GMT 2026-07-17T11:03:38Z http://hdl.handle.net/123456789/466 Database modeling & normalization Arkhipov, Evgeny Mr.; Vajjhala, Narasimha Rao Dr. This workshop will cover topics, including normalization and E-R diagrams. Normalization is the process of organizing data in a database. This includes creating tables and establishing relationships between those tables according to rules designed both to protect the data and to make the database more flexible by eliminating redundancy and inconsistent dependency. This workshop will include discussion on the various normal forms and how the five normal forms can be applied. ER-Diagrams are pictorial representation of data that describes how data is communicated and related to each other. ER Diagrams are most often used to design or debug relational databases in the fields of software engineering, business information systems, education and research. Fri, 01 Dec 2017 00:00:00 GMT http://hdl.handle.net/123456789/466 2017-12-01T00:00:00Z http://hdl.handle.net/123456789/465 The unified modeling language Thandekkattu, George Dr. Fri, 01 Dec 2017 00:00:00 GMT http://hdl.handle.net/123456789/465 2017-12-01T00:00:00Z http://hdl.handle.net/123456789/464 Ruby-on-Rails (ROR): An Agile Web Development Framework Vedishchev, Alexey Ruby on Rails Web Application Development Framework (ROR). Ruby-on-Rails is an open-source, full-stack framework for developing database-backed web applications following the Model-View-Control (MVC) design pattern. A full-featured Ruby application, Rails takes full advantage of Ruby’s agility with some additions of its own. Doing things the Rails and Ruby way means huge savings in developer time and a great way to becoming a good citizen of the Ruby and Rails ecosystem. The workshop focuses on fundamentals of programming for the web, introduction to web stack, overview of the rails framework, using models to interact with database and lots more. It provides the summary of workshop events. Sun, 01 Jan 2017 00:00:00 GMT http://hdl.handle.net/123456789/464 2017-01-01T00:00:00Z http://hdl.handle.net/123456789/463 Clustering Algorithms and its Applications in Data Science Prasad, Rajesh Dr. Data science involves using automated methods to analyze massive amounts of data and to extract knowledge from them. It is helping to create new branches of science, and influencing areas of social science and the humanities. Looking at the increase in size of data, data science is expected to accelerate in the recent future. Data science is an umbrella that contains many other fields like data mining, machine learning, big data, statistics, data visualization and data analytics etc. Clustering, a data mining technique is defined as partitioning large number of data points into smaller number of groups. It groups the objects in such a way that object with similar characteristics are in one group and objects in dissimilar characteristics are in different groups. This similarity can be measured in terms of distance measures function (e.g. edit distance). Clustering helps in summarizing the data and understanding it for a variety of data mining applications. It can be used in data summarization, social network analysis (community detection), customer segmentation and outlier detection. This presentation will focus on various types of distance measures, clustering and real life applications of clustering algorithms. Fri, 01 Dec 2017 00:00:00 GMT http://hdl.handle.net/123456789/463 2017-12-01T00:00:00Z