Refers to class of system which supports in the process of decision making and does not always give a decision itself.
Decision Support Systems supply computerized support for the decision making process.
MODEL- DRIVEN DSS
includes system that use accounting, financial models, and representational models.
2. DATA DRIVEN DSS
file drawer & management reporting system, data warehousing, geographical information.
Management Information System - MIS - ApplicationFaHaD .H. NooR
Management information system (MIS) refers to the processing of information through computers to manage and support managerial decisions within an organization. The concept may include systems termed transaction processing system, decision support system, expert system, or executive information system. The term is often used in the academic study of businesses and has connections with other areas, such as information systems, information technology, informatics, e-commerce and computer science; as a result, the term is used interchangeably with some of these areas.
Management information systems (plural) as an academic discipline studies people, technology, organizations, and the relationships among them.This definition relates specifically to "MIS" as a course of study in business schools. Many business schools (or colleges of business administration within universities) have an MIS department, alongside departments of accounting, finance, management, marketing, and may award degrees (at the undergraduate, master, and doctoral levels) in Management Information Systems.
MIS professionals help organizations to maximize the benefit from investments in personnel, equipment, and business processes.There are different areas of concentration with different duties and responsibilities in information system managers starting from the Chief information officer (CIOs), Chief technology officer (CTOs), IT directors and IT security managers. Chief information officers (CIOs) are responsible for the overall technology strategy of their organizations. Basically, they are more of the decision makers and action takers when it comes down to determining the technology or information goals of an organization and making sure the necessary planning to implement those goals is being met.
Chief technology officers (CTOs) are responsible for evaluating how new technology can help their organization. They usually recommend technological solutions to support the policies issued by the CIO.[2]
IT directors including MIS directors are in charge of both their organization's Information technology departments and the supervision of thereof. They are also in charge of implementing the policies chosen by the other top branches (CIOs, CTOs). It is their role to ensure the availability of data and network services by coordinating IT activities.
IT Security Managers oversee the network and security data as the title implies. They develop programs to offer information and awareness to their employees about security threats. This team is very important because they must keep up-to-date on IT security measures in order to be successful within their organization. Any security violations need to be investigated and supervised by this specific team.
MODEL- DRIVEN DSS
includes system that use accounting, financial models, and representational models.
2. DATA DRIVEN DSS
file drawer & management reporting system, data warehousing, geographical information.
Management Information System - MIS - ApplicationFaHaD .H. NooR
Management information system (MIS) refers to the processing of information through computers to manage and support managerial decisions within an organization. The concept may include systems termed transaction processing system, decision support system, expert system, or executive information system. The term is often used in the academic study of businesses and has connections with other areas, such as information systems, information technology, informatics, e-commerce and computer science; as a result, the term is used interchangeably with some of these areas.
Management information systems (plural) as an academic discipline studies people, technology, organizations, and the relationships among them.This definition relates specifically to "MIS" as a course of study in business schools. Many business schools (or colleges of business administration within universities) have an MIS department, alongside departments of accounting, finance, management, marketing, and may award degrees (at the undergraduate, master, and doctoral levels) in Management Information Systems.
MIS professionals help organizations to maximize the benefit from investments in personnel, equipment, and business processes.There are different areas of concentration with different duties and responsibilities in information system managers starting from the Chief information officer (CIOs), Chief technology officer (CTOs), IT directors and IT security managers. Chief information officers (CIOs) are responsible for the overall technology strategy of their organizations. Basically, they are more of the decision makers and action takers when it comes down to determining the technology or information goals of an organization and making sure the necessary planning to implement those goals is being met.
Chief technology officers (CTOs) are responsible for evaluating how new technology can help their organization. They usually recommend technological solutions to support the policies issued by the CIO.[2]
IT directors including MIS directors are in charge of both their organization's Information technology departments and the supervision of thereof. They are also in charge of implementing the policies chosen by the other top branches (CIOs, CTOs). It is their role to ensure the availability of data and network services by coordinating IT activities.
IT Security Managers oversee the network and security data as the title implies. They develop programs to offer information and awareness to their employees about security threats. This team is very important because they must keep up-to-date on IT security measures in order to be successful within their organization. Any security violations need to be investigated and supervised by this specific team.
A decision support system (DSS) is a computer-based information system that supports business or organizational decision-making activities. DSSs serve the management
A decision support system (DSS) is a computer-based information system that supports business or organizational decision-making activities. DSSs serve the management
The series of presentations contains the information about "Management Information System" subject of SEIT for University of Pune.
Subject Teacher: Tushar B Kute (Sandip Institute of Technology and Research Centre, Nashik)
http://www.tusharkute.com
El campo de DSS / BI esta evolucionando desde sus origenes como una herramienta primariamente de soporte personal y está rapidamente llegando a ser una comodidad compartida a traves de de las organizaciones
Decision Support Systems: Concept, Constructing a DSS, Executive Information ...Ashish Hande
Decision Support Systems: Concept, Constructing a DSS,
Executive Information System, (EIS), Artifical Intelligence
System (AIS), knowledge Based Expert System (KBES),
Enterprise Management System (EMS), Decision Support
Management System (DSMS).
Nonverbal Communication = Communication without words
Nonverbal communication is a process of communication through sending and receiving wordless messages.
A feasibility study is valuable for:
Starting a new business
Expansion of an existing business
Adding an enterprise to an existing business
Purchasing an existing business.
A business plan is a document that brings together the key elements of a business that include details about the products and services, the cost, sales and expected profits.
A small – scale independent firm usually managed, funded and operated by its owners, and whole staff size, financial resources and assets are comparatively limited in scale.
Is a process of identifying and starting a business venture, sourcing and organizing the required resources and taking both the risks and rewards associated with the venture.
1. Research Processes and steps in research process. Why is the problem definition stage probably the most important stage in the research process?
2. What is research problem? Define the main issues should receive the attention of the researcher in formulating the research problem. Give suitable examples to elucidate your points.
3. The process of problem definition
a. Statement of the problem in a general way
b. Understanding the nature/background of the problem.
c. Surveying the available literature
d. Developing the ideas through discussions
e. Rephrasing the research problem.
4. The research proposal and what purpose does a research proposal serve?
5. What is a hypothesis? What characteristics it must possess in order to be a good research hypothesis? List and briefly discuss in the hypothesis –testing procedure.
6. Write notes on following :
a. Null Hypothesis & Alternative Hypothesis
b. Type I error & Type II error.
c. Acceptance Region & Rejection Region
Messages can be communicated through gestures and touch, body language or posture, facial expression and eye contact.
The process of communication through sending and receiving wordless cues between people.
Neuro- Linguistic Programming (NLP) is an approach to communication, personal development & psychotherapy created by RICHARD BANDLER & JOHN GRINDER in California, USA in 1970’s.
Group Discussion is a modern method of assessing students personality.
It is both a technique and an art and a comprehensive tool to judge the worthiness of the student and his appropriateness for the job.
Business communication module 5 - Kerala UniversityNijaz N
Unit V Non-verbal communication, body language, kinetics, proxemics, para-language,
NLP; Listening - principles of effective listening, Visual communication - use of AVAs,
Technology and communication - Communicating digitally - Fax, Electronic mail,
Teleconferencing, Video conferencing.
Business communication module 4 - Kerala UniversityNijaz N
Unit IV Oral communication - Skills and effectiveness, principles. Planning a talk,
presentations, Extempore speech, Group discussions, Interviewing skills - Appearing
in interviews, conducting interviews; chairing, attending meetings, conferences,
seminars; Negotiation skills, conversation control.
Business communication module 3 - Kerala UniversityNijaz N
Unit III Persuasive communication - Circulars, Publicity material, news letters, Notices and
advertisements, Leaflets, Invitation; Internal communication - memoranda, meeting
documentation, Reports, Types of reports, Writing of reports.
Business communication -Assignment - Kerala UniversityNijaz N
1. Why do we communicate? What benefits does effective communication give you? How is the effectiveness of communication evaluated?
2. Discuss communication as a two-way process of exchange of information.
3. Discuss the important barriers in the communication process. Give practical examples of failures of communication arising from the different communication barriers.
4. Do you agree that, in its final form, communication is a manifestation of the personalities of both the sender and the receiver? Discuss.
5. How does group communication differ from mass communication? Does this difference between these two forms of communication demand greater care on the part of communicator (Sender)? Discuss.
Business communication module 2 - Kerala UniversityNijaz N
Unit II Written communication, Principles of effective writing; business letters - types, layout,
Application letter - resume - references; Appointment orders. Letter of resignation;
Business enquiries - offers and quotations, Order - execution and cancellation of
orders; Letters of complaint; Case Analysis.
Business communication module 1 - Kerala UniversityNijaz N
Unit I Nature and purpose of communication; Process and Elements - Classification of
communication - intrapersonal, interpersonal, written, verbal, non verbal, visual etc;
Barriers to communication; Principles of effective communication; Business
communication - Role, Importance, types; Deductive & inductive logic.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
2. DECISION MAKING & INFORMATION SYSTEM
Decisions are made at all levels of the firm.
Some decisions are very common and routine but exceptionally valuable.
IT provides new tools for managers to carryout decisions.
Receiving the most concrete, up-to-date information and redistributing it
to those who need to aware of it.
IT does not provide any information directly, but provides some
capabilities to the user to analyze the decision problem and generate some
meaningful information for decision-making
3. DECISION SUPPORT SYSTEM
Refers to class of system which supports in the process of decision making
and does not always give a decision itself.
Decision Support Systems supply computerized support for the decision
making process.
End-users actively work with the data warehouse.
End-users apply models to represent, understand, and simplify the decision
situation.
6. DSS: DECISION SUPPORT SYSTEMS
sales revenue profit prior
154 204.5 45.32 35.72
163 217.8 53.24 37.23
161 220.4 57.17 32.78
173 268.3 61.93 47.68
143 195.2 32.38 41.25
181 294.7 83.19 67.52
Sales and Revenue 1994
Jan Feb Mar Apr May Jun
0
50
100
150
200
250
300
Legend
Sales
Revenue
Profit
Prior
Database
Model
Output
7. FRAMEWORK FOR DEVELOPING DSS
Intelligence Phase
Design Phase
Choice Phase
REALITY
Implementation
of Solution
SUCCESS
FAILURE
Verification, Testing
of Proposed Solution
Validation of
the Model
Examination
8. CHARACTERISTICS AND CAPABILITIES OF DSS
Support decision makers at all managerial levels
Support several interdependent and/or sequential decisions
Support all phases of decision making and a variety of decision-making
processes and styles
Can be adapted over time to deal with changing conditions
Easy to construct
Utilizes models and links to data- and knowledge bases
Execute sensitivity analysis
9. DSS ANALYSIS
Sensitivity Analysis
The study of the effect that changes in one or more parts of a model
have on other parts of the model
What-if Analysis
Checks the impact of a change in the assumptions or other input data
on the proposed solution
Goal-seeking Analysis
Find the value of the inputs necessary to achieve a desired level of
output
11. COMPONENTS AND STRUCTURE OF DSS
Data Management
Includes the database(s) containing relevant data for the decision
situation
User Interface
Enables the users to communicate with and command the DSS
Model Management
Includes software with financial, statistical, management science, or
other quantitative models
Knowledge Management
Provides knowledge for solution of the problem; supports any of the
other subsystems or act as an independent component
12. DSS – CLASSIFICATIONS -RELATIONSHIP WITH THE USER
Passive DSS
System that aids the process of decision making, but that cannot bring out
explicit decision suggestions or solutions.
Active DSS
Can bring out such decision suggestions or solutions.
Cooperative DSS
Allows the decision maker to modify, complete, or refine the decision
suggestions provided by the system, before sending them back to the
system for validation. The system again improves, completes, and refines
the suggestions of the decision maker. Repeat this process.
13. DSS – CLASSIFICATIONS -MODE OF ASSISTANCE
Model-driven DSS
Use data and parameters provided by users to assist decision makers in
analyzing a situation
Eg :- Dicodess is an example of an open source model-driven DSS
generator .
o Communication-driven DSS
Supports more than one person working on a shared task
Eg:- Microsoft's NetMeeting or Groove
o Data-driven DSS
Emphasizes access to and manipulation of a time series of internal company
data and, sometimes, external data.
14. DSS – CLASSIFICATIONS -MODE OF ASSISTANCE
Document-driven DSS
Manages, retrieves and manipulates unstructured information in a
variety of electronic formats.
Knowledge-driven DSS
Provides specialized problem solving expertise stored as facts, rules,
procedures
15. MIS V/S DSS
Provide information on firm’s performance to
help managers monitor and control the
business
Produce answers to routine questions and
fixed, regularly scheduled reports
Sometimes MIS reports are only exception
reports (highlighting only exceptional
conditions)
Oriented to internal events
Make use of simple methods such as
summaries and comparisons
Provides input to operational, tactical and
strategic levels
Depend on TPS for their data
DSS support semi-structured and unstructured
problem analysis
Helps make decisions that are unique, rapidly
changing and not specified in advance
Bring information from external sources also
DSS emphasizes change, flexibility and rapid
response and works on interactive user-friendly
mode
Make use of mathematical models/statistical
techniques
Caters more to strategic decision making
Uses internal information from both MIS and
TPS
MIS
DSS
16. BENEFITS OF DSS
Improves personal efficiency
Speed up the process of decision making
Increases organizational control
Encourages exploration and discovery on the part of the decision
maker
Speeds up problem solving in an organization
Facilitates interpersonal communication
Promotes learning or training
Generates new evidence in support of a decision
Creates a competitive advantage over competition
Reveals new approaches to thinking about the problem space
Helps automate managerial processes
Create Innovative ideas to speed up the performance
18. GROUP DECISION SUPPORT SYSTEM
An interactive computer-based system used to facilitate the solution of
unstructured problems
A set of decision makers working together as a group.
GDSS make meetings more productive by providing tools to facilitate
planning, generating, organizing, and evaluating ideas; establishing
priorities; and documenting meeting proceedings for others in the firm.
Originally developed for meetings in which all participants are in the same
room.
But nowadays used for networked meetings in which participants' are in
different locations.
20. COMPONENTS OF GDSS
Hardware: Including conference facilities and electronic hardware.
Software tools: Including electronic questionnaires, brainstorming tools,
idea organizers, questionnaire tools, voting tools; stakeholder
identification and analysis tools; policy formation tools, and group
dictionaries.
People: Refers not only to the participants but also to a trained facilitator
and often to a staff that supports the hardware and software.
21. FUNCTIONS OF GDSS APPLICATIONS
Predicting decision outcomes.
Identifying factors and trends.
Developing models of business processes.
Computing optimum mixes.
Facilitating group communication, collaboration and teamwork.
Determining sensitivity of results to changes in decision variables.
Becoming familiar with a problem domain.
22. GDSS – BUSINESS VALUE
Using GDSS, productivity can increase with increase in number of
attendees
More collaborative atmosphere by guaranteeing contributors’ anonymity
GDSS software tools follow structured methods for preserving results of
meetings, enabling non-attendees to locate needed info after the meeting
GDSS meetings can increase number of ideas generated and quality of
decisions while producing the desired results in fewer meetings
Leads to more participative and democratic decision making
Most useful for tasks involving idea generation, complex problems and
large groups
24. EDSS
Help senior managers with unstructured problems that occur at the
strategic level of the firm.
Combining the internal and external sources.
Helps to monitor :
organizational performance,
Track activities of competitors,
Spot problems,
Identify opportunities
Forecast trends.
25. EDSS
It is also known as
Executive Support Systems(ESS)
Executive Information Systems(EIS)
o Benefits
o Increases organizational control.
o Reveals new approaches to thinking about the problem space.
o Encourages exploration and discovery on the part of the decision maker.
o Creates a competitive advantage over competition
26. EDSS CAPABILITIES
Drill down-ability to go to details at several levels
Critical success factors-most critical for success of business
Key performance indicator
Status access-latest data available on Knowledge Process (KP)
Trend analysis-short , medium and long term trend on KP
Adhoc analysis-analysis made anytime upon demand
Exception reporting-report that highlight deviations larger than certain
threshold