The document outlines the key competencies, knowledge, and skills for an information systems curriculum according to the ACM guidelines. It discusses topics like understanding organizational processes and technical solutions, acquiring and storing data, and applying IT to help organizations achieve their goals. Specific areas of knowledge and skill mentioned include designing enterprise architectures, managing IS development resources, and managing IS projects. It also summarizes the learning objectives and topics for courses in application development and data management.
The development of modern information systems is a demanding task. New technologies and tools are designed, implemented and presented in the market on a daily bases. User needs change dramatically fast and the IT industry copes to reach the level of efficiency and adaptability for its systems in order to be competitive and up-to-date. Thus, the realization of modern information systems with great characteristics and functionalities implemented for specific areas of interest is a fact of our modern and demanding digital society and this is the main scope of this Presentation.
This presentation covers data mining within artificial intelligence. Topics covered are as follows: motivation, synonym, process of data mining, operation of data mining, data mining techniques, business application, application selection, and current issues.
Data Mining: What is Data Mining?
History
How data mining works?
Data Mining Techniques.
Data Mining Process.
(The Cross-Industry Standard Process)
Data Mining: Applications.
Advantages and Disadvantages of Data Mining.
Conclusion.
INFORMATION RESOURCES MANAGEMENT UNDER INDUSTRY-INSTITUTE PARTNERSHIP: A Case...Bhojaraju Gunjal
Gunjal, Bhojaraju., Choukimath, PA and Agadi, KB (2003). Information Resources Management under Industry-Institute Partnership: A study on IRMRA-TSR-PIIT Library, In Proceedings of BOSLA Seminar, TISS, Nov. 8, 2003, Mumbai.
DATA MINING AND DATA WAREHOUSE
W.H. Inmon
OLAP, (On-line analytical processing)
OLTP, ( On-line transaction processing )
Data Cleaning
Data Integration
Data Selection
Data Transformation
Data warehouse vs Data Mining
Use in Urban Planning
The development of modern information systems is a demanding task. New technologies and tools are designed, implemented and presented in the market on a daily bases. User needs change dramatically fast and the IT industry copes to reach the level of efficiency and adaptability for its systems in order to be competitive and up-to-date. Thus, the realization of modern information systems with great characteristics and functionalities implemented for specific areas of interest is a fact of our modern and demanding digital society and this is the main scope of this Presentation.
This presentation covers data mining within artificial intelligence. Topics covered are as follows: motivation, synonym, process of data mining, operation of data mining, data mining techniques, business application, application selection, and current issues.
Data Mining: What is Data Mining?
History
How data mining works?
Data Mining Techniques.
Data Mining Process.
(The Cross-Industry Standard Process)
Data Mining: Applications.
Advantages and Disadvantages of Data Mining.
Conclusion.
INFORMATION RESOURCES MANAGEMENT UNDER INDUSTRY-INSTITUTE PARTNERSHIP: A Case...Bhojaraju Gunjal
Gunjal, Bhojaraju., Choukimath, PA and Agadi, KB (2003). Information Resources Management under Industry-Institute Partnership: A study on IRMRA-TSR-PIIT Library, In Proceedings of BOSLA Seminar, TISS, Nov. 8, 2003, Mumbai.
DATA MINING AND DATA WAREHOUSE
W.H. Inmon
OLAP, (On-line analytical processing)
OLTP, ( On-line transaction processing )
Data Cleaning
Data Integration
Data Selection
Data Transformation
Data warehouse vs Data Mining
Use in Urban Planning
Watch the companion webinar at: http://embt.co/1FTVdGF
Every year the State of Texas CIO releases the five-year State Strategic Plan with IT initiatives for government organizations to implement. How many of the items from the November 2014 plan update have you planned for or put in place? If you need help aligning with these state objectives, join this session to learn how ER/Studio can enhance your data architecture to meet these goals.
In this age of data policies and protection, Texas State agencies are required to develop controls to ensure confidentiality, integrity and availability of their data. In this webinar, we’ll show a live demonstration of ER/Studio and describe how it addresses key areas of the strategic objectives, including:
+ Data security and privacy classifications
+ Data quality and availability requirements
+ Enterprise planning and collaboration within and across organizations
UNIT 3Data and Knowledge ManagementDefining Big Data.docxouldparis
UNIT 3
Data and Knowledge Management
Defining Big Data
Big Data Generally Consist of:
– Traditional enterprise data
– Machine-generated/sensor data
– Social Data
– Images captured by billions of devices
located around the world
Characteristics of Big Data
• Volume
• Velocity
• Variety
The Database Approach
Database management system (DBMS)
minimize the following problems:
–Data redundancy
–Data isolation
–Data inconsistency
Data Hierarchy
Bit
Byte
Field
Record
File (or table)
Database
Designing the Database
Data model
Entity
Attribute
Primary key
Secondary keys
Entity-Relationship Modeling
• Database designers plan the database
design in a process called entity-
relationship (ER) modeling.
• ER diagrams consists of entities, attributes
and relationships.
– Entity classes
– Instance
– Identifiers
Database Management Systems
Database management system (DBMS)
Relational database model
Structured Query Language (SQL)
Query by Example (QBE)
Normalization
• Normalization is a method for analyzing
and reducing a relational database to its
most streamlined form for:
– Minimum redundancy
– Maximum data integrity
– Best processing performance
• Normalized data is when attributes in the
table depend only on the primary key.
Data Warehousing
Data warehouses and Data Marts
Organized by business dimension or
subject.
Multidimensional.
Historical.
Use online analytical processing.
Benefits of Data Warehousing
•End users can access data quickly and easily
via Web browsers because they are located in
one place.
•End users can conduct extensive analysis
with data in ways that may not have been
possible before.
•End users have a consolidated view of
organizational data.
Data Marts
• A data mart is a small data warehouse,
designed for the end-user needs in a
strategic business unit (SBU) or a
department.
Knowledge Management
• Knowledge management (KM)
• Knowledge
• Intellectual capital (or intellectual assets)
Knowledge Management System Cycle
•Create knowledge
•Capture knowledge
•Refine knowledge
•Store knowledge
•Manage knowledge
•Disseminate knowledge
Develop a project proposal. Write a 2-page project proposal which states the rationale for the selected industry and company. You must submit one hardcopy of the project proposal for evaluation . The Project Proposal is worth 50 points of your final grade.
Project Proposal Guidelines:
· Identification of a non-U.S. company
· Introduction of the company’s background
· Identification of possible sources:
· News reports
· Scholarly sources
· Public information about the company
· Outline of the project plan and timeline
· Discussion on potential problems and/or challenges for your project
...
Data Architecture is foundational to an information-based operational environment. Without proper structure and efficiency in organization, data assets cannot be utilized to their full potential, which in turn harms bottom-line business value. When designed well and used effectively, however, a strong Data Architecture can be referenced to inform, clarify, understand, and resolve aspects of a variety of business problems commonly encountered in organizations.
The goal of this webinar is not to instruct you in being an outright Data Architect, but rather to enable you to envision a number of uses for Data Architectures that will maximize your organization’s competitive advantage. With that being said, we will:
Discuss Data Architecture’s guiding principles and best practices
Demonstrate how to utilize Data Architecture to address a broad variety of organizational challenges and support your overall business strategy
Illustrate how best to understand foundational Data Architecture concepts based on “The DAMA Guide to the Data Management Body of Knowledge” (DAMA DMBOK)
ADV Slides: What the Aspiring or New Data Scientist Needs to Know About the E...DATAVERSITY
Many data scientists are well grounded in creating accomplishment in the enterprise, but many come from outside – from academia, from PhD programs and research. They have the necessary technical skills, but it doesn’t count until their product gets to production and in use. The speaker recently helped a struggling data scientist understand his organization and how to create success in it. That turned into this presentation, because many new data scientists struggle with the complexities of an enterprise.
Software measurement adalah proses pengumpulan, analisis, dan penggunaan data yang terkait dengan perangkat lunak untuk mengukur, memperbaiki, dan memantau kualitas, produktivitas, dan efektivitas pengembangan dan pemeliharaan perangkat lunak.
Studi tentang bagaimana membuat keputusan yang optimal dalam pengembangan perangkat lunak dari sudut pandang ekonomi.
Tujuan: Mencapai pengembangan perangkat lunak yang efisien dan efektif, sambil meminimalkan biaya dan risiko
13 Software Engineering Model and MethodsAinul Yaqin
Proses pemodelan sistem perangkat lunak dengan menggunakan metode formal, grafis, dan matematis untuk menggambarkan dan mengatur berbagai aspek dari sistem tersebut.
Membantu para pengembang dalam merancang dan membangun sistem perangkat lunak yang lebih baik dengan mengurangi risiko kesalahan dan meningkatkan efisiensi dan efektivitas pengembangan
Suatu proses untuk mengevaluasi dan memverifikasi software dengan tujuan untuk menemukan kesalahan atau kelemahan dalam software sehingga dapat diperbaiki dan meningkatkan kualitas software.
04 Software Design Strategies and MethodsAinul Yaqin
Desain didefinisikan sebagai proses mendefinisikan arsitektur, komponen, antarmuka, dan karakteristik lain dari sistem atau komponen" dan "hasil dari proses [itu]”
Desain software didefinisikan sebagai aktivitas siklus hidup rekayasa dan deskripsi struktur internal yang akan menjadi dasar untuk konstruksinya.
Hasil mendesain menggambarkan komponen pada tingkat detail dan antarmuka di antara komponen-komponen tersebut
Teknologi Konstruksi Software adalah sekumpulan alat, metode, dan proses yang digunakan dalam membangun software.
Teknologi ini mencakup alat dan teknik untuk mengatur, memantau, dan mengelola pembangunan software, seperti alat pengontrol versi, manajemen proyek, serta pendekatan dan metode konstruksi.
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
2. 2
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IS Competencies (ACM)
……………………………………..
IS professionals must design and implement information technology
solutions that enhance organizational performance. Students must
therefore:
• Possess skills in understanding and modeling organizational
processes and data, defining and implementing technical and process
solutions, managing projects, and integrating systems within and
across organizations.
• Be fluent in techniques for acquiring, converting, transmitting, and
storing data and information, including those related to data quality
• Focus on the application of information technology in helping
individuals, groups, and organizations achieve their goals within a
competitive global environment.
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IS Specific Knowledge & Skill (ACM)
• Designing enterprise architectures
• Identifying, evaluating, and procuring detailed solution and sourcing options;
configuring and integrating organizational solutions using packaged solutions
• Designing and implementing solutions that provide a high -quality user
experience
• Designing secure systems and data infrastructures
• Designing and implementing applications, application architectures and
integrated systems
• Managing and exploiting organizational data and information; designing data
and information models
• Managing information systems development/procurement resources
• Managing information systems projects.
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Application Development
The purpose of this course is to introduce the students to
the fundamental concepts and models of application
development so that they can understand the key
processes related to building functioning applications and
appreciate the complexity of application development.
Students will learn the basic concepts of program design,
data structures, programming, problem solving,
programming logic, and fundamental design techniques
for event-driven programs. Program development will
incorporate the program development life cycle: gathering
requirements, designing a solution, implementing a
solution in a programming language, and testing the
completed application.
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AD Learning Objective
• Use primitive data types and data structures offered by the
development environment
• Choose an appropriate data structure for modeling a simple problem
• Understand basic programming concepts
• Write simple applications that relate to a specific domain
• Design, implement, test, and debug a program that uses each of the
following fundamental programming constructs: basic computation,
simple I/O, standard conditional and iterative structures, and the
definition of functions.
• Test applications with sample data
• Apply core program control structures
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AD Topics
• Program design
• Program development lifecycle
• Requirements determinants and analysis
• Modular design
• Techniques for modeling program structures
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AD Topics
• Unit Testing
• Control structures
• Sequential
• Conditional
• Iterative
• Input/Output (I/O) design
• Text-based
• Graphical user interface (GUI)
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AD Topics
• Data structures
• Primitive data types, composite data types, arrays
• Memory management
• Sequential and random file processing
• Database Access
11. 11
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AD Topics
• Development approaches
• Object-oriented
• Procedural
• Declarative
• Rapid application
• Structured
12. 12
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AD Topics
• Application integration
• Prototyping
• Overview and history of programming languages
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Approaches
The course benefits from computer lab resources
either in class or available for licensing on individual
students’ computers. The choice of language should
reflect commonly used languages and tools with the
expectation that learning any language will gener
alize to other languages. For this reason it may be
best to concentrate on one language to develop
depth rather than breadth across several languages.
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Data Management
This course provides the students with an
introduction to the core concepts in data and
information management. It is centered around the
core skills of identifying organizational information
requirements, modeling them using conceptual data
modeling techniques, converting the conceptual data
models into relational data models and verifying its
structural characteristics with normalization
techniques, and implementing and utilizing a
relational database using an industrial-strength
database management system
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Learning Objectives
• Understand the role of databases and database management
systems in managing organizational data and information.
• Understand the historical development of database
management systems and logical data models.
• Understand the basics of how data is physically stored and
accessed.
• Understand the fundamentals of the basic file organization
techniques.
• Apply information requirements specification processes in
the broader systems analysis & design context.
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Learning Objectives
• Use at least one conceptual data modeling technique
(such as entity-relationship modeling) to capture the
information requirements for an enterprise domain.
• Link to each other the results of data/information
modeling and process modeling.
• Design high-quality relational databases.
• Understand the purpose and principles of normalizing a
relational database structure.
• Design a relational database so that it is at least in 3NF.
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Learning Objectives
• Implement a relational database design using an industrial-
strength database management system, including the
principles of data type selection and indexing.
• Use the data definition, data manipulation, and data control
language components of SQL in the context of one widely
used implementation of the language.
• Perform simple database administration tasks.
• Understand the concept of database transaction and apply it
appropriately to an application context.
• Understand the basic mechanisms for accessing relational
databases from various types of application development
environments.
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Learning Objectives
• Understand the role of databases and database
management systems in the context of enterprise
systems.
• Understand the key principles of data security and
identify data security risk and violations in data
management system design.
• Understand the core concepts of data quality and
their application in an organizational context.
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Learning Objectives
• Understand the difference between on-line transaction
processing (OLTP) and online analytic processing
(OLAP), and the relationship between these concepts
and business intelligence, data warehousing and data
mining.
• Create a simple data warehouse (“data mart”).
• Understand how structured, semi-structured, and
unstructured data are all essential elements of
enterprise information and knowledge management. In
this context, the students will learn the principles of
enterprise search.
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Topics
• Database approach
• Types of database management systems
• Basic file processing concepts
• Physical data storage concepts
• File organizations techniques
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Topics
• Conceptual data model
• Entity-relationship model
• Object-oriented data model
• Logical data model
• Hierarchical data model
• Network data model
• Relational data model
• Relations and relational structures
• Relational database design
• Mapping conceptual schema to a relational schema
• Normalization
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Topics
• Physical data model
• Indexing
• Data types
• Database languages
• SQL: DDL, DML, and DCL
• Data and database administration
• Transaction processing
• Using a database management system from an application
development environment
• Use of database management systems in an enterprise
system context
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Topics
• Data / information architecture
• Data security management
• Basic data security principles
• Data security implementation
• Data quality management
• Data quality principles
• Data quality audits
• Data quality improvement
• Business intelligence
• On-line analytic processing
• Data warehousing
• Data mining
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References
Association for Computing Machinery(ACM) and
Association for Information Systems (AIS),
“Curriculum Guidelines for Undergraduate Degree
Programs in Information Systems”, 2010