This document provides an overview of key aspects of software design, including data design, architectural design, modular design, and human-computer interface design. It discusses how software design develops blueprints to translate user requirements into implementable programs through various models and refinements. Quality is built into software during the design phase by devoting sufficient time to create a systematic, hierarchical design with modular and loosely coupled components. Data design identifies and structures application data, while architectural design defines the overall organization and relationships between program modules. Modular design divides software into independent, named modules to facilitate maintenance and parallel development.
This document provides an overview of fundamental data modeling skills that all developers should have. It discusses what data modeling is, how data models are used in practice, common data modeling notations, and how to model data through tasks like identifying entity types and attributes, applying naming conventions, identifying relationships, and normalizing data. The primary goal is to help application developers gain an understanding of the critical activities performed by Agile DBAs to improve communication between these roles.
This document provides an outline for an architect to document a software system. It includes sections for describing the functional overview, quality attributes, constraints, principles, software architecture, external interfaces, code structure, vision, risks, data model, infrastructure, deployment, operations and support, and decisions made. The goal is to model all possible failures and reasons for failure in order to understand how to avoid and fix issues when they occur. Details are only included if they can help reason about potential failures.
This document provides a design overview of the Web Accessible Alumni Database software. It includes deployment diagrams, architectural designs, data structure details, use case realizations, and interface designs. The system allows alumni to complete surveys, add and update their entries, and search for other alumni to email. It consists of a web server and client using HTML and JSP. The designated faculty member can make changes to surveys, collected data fields, and email capabilities.
CIS 532 STUDY Inspiring Innovation--cis532study.comKeatonJennings93
This document outlines the requirements for a technical term paper assignment for a CIS 532 class. It provides background information on a fictional company, Fiction Corporation, which is migrating its primary data center to a new headquarters building. The student is tasked with developing a network design document and plan to upgrade Fiction Corporation's network and address security issues as part of the data center migration, within a budget of $500,000 and without disrupting business operations. The paper should include details on the current network configuration, a logical and physical design for the new network, an implementation plan, and a projected budget and return on investment.
Iwsm2014 solution based estimating (eltjo poort)Nesma
This document discusses estimating the cost of heterogeneous solutions and CGI's solution-based estimating approach. CGI breaks down heterogeneous solutions into homogeneous components using a Solution Breakdown Structure (SBS) informed by the Solution Architecture. Research shows that applying a Solution Architecture improves budget predictability, reduces overruns, and increases customer satisfaction. The SBS decomposes the solution hierarchically into deliverable products that can be estimated independently.
Normalisation in Database management System (DBMS)Prof Ansari
Normalization is a technique to organize the contents of the table for transactional database and data warehouse.
First Normal Form :
Seeing the data in the example in the book or assuming otherwise that all attributes contain the atomic value, we find out the table is in the 1NF.
Second Normal Form :
Seeing the FDs, we find out that the K for the table is a composite one comprising of empId, projName. We did not include the determinant of fourth FD, that is, the empDept, in the PK because empDept is dependent on empId and empID is included in our proposed PK. However, with this PK (empID, projName) we have got partial dependencies in the table through FDs 1 and 3 where we see that some attributes are being determined by subset of our K which is the violation of the requirement for the 2NF. So we split our table based on the FDs 1 and 3 as follows :
This document provides an overview of key aspects of software design, including data design, architectural design, modular design, and human-computer interface design. It discusses how software design develops blueprints to translate user requirements into implementable programs through various models and refinements. Quality is built into software during the design phase by devoting sufficient time to create a systematic, hierarchical design with modular and loosely coupled components. Data design identifies and structures application data, while architectural design defines the overall organization and relationships between program modules. Modular design divides software into independent, named modules to facilitate maintenance and parallel development.
This document provides an overview of fundamental data modeling skills that all developers should have. It discusses what data modeling is, how data models are used in practice, common data modeling notations, and how to model data through tasks like identifying entity types and attributes, applying naming conventions, identifying relationships, and normalizing data. The primary goal is to help application developers gain an understanding of the critical activities performed by Agile DBAs to improve communication between these roles.
This document provides an outline for an architect to document a software system. It includes sections for describing the functional overview, quality attributes, constraints, principles, software architecture, external interfaces, code structure, vision, risks, data model, infrastructure, deployment, operations and support, and decisions made. The goal is to model all possible failures and reasons for failure in order to understand how to avoid and fix issues when they occur. Details are only included if they can help reason about potential failures.
This document provides a design overview of the Web Accessible Alumni Database software. It includes deployment diagrams, architectural designs, data structure details, use case realizations, and interface designs. The system allows alumni to complete surveys, add and update their entries, and search for other alumni to email. It consists of a web server and client using HTML and JSP. The designated faculty member can make changes to surveys, collected data fields, and email capabilities.
CIS 532 STUDY Inspiring Innovation--cis532study.comKeatonJennings93
This document outlines the requirements for a technical term paper assignment for a CIS 532 class. It provides background information on a fictional company, Fiction Corporation, which is migrating its primary data center to a new headquarters building. The student is tasked with developing a network design document and plan to upgrade Fiction Corporation's network and address security issues as part of the data center migration, within a budget of $500,000 and without disrupting business operations. The paper should include details on the current network configuration, a logical and physical design for the new network, an implementation plan, and a projected budget and return on investment.
Iwsm2014 solution based estimating (eltjo poort)Nesma
This document discusses estimating the cost of heterogeneous solutions and CGI's solution-based estimating approach. CGI breaks down heterogeneous solutions into homogeneous components using a Solution Breakdown Structure (SBS) informed by the Solution Architecture. Research shows that applying a Solution Architecture improves budget predictability, reduces overruns, and increases customer satisfaction. The SBS decomposes the solution hierarchically into deliverable products that can be estimated independently.
Normalisation in Database management System (DBMS)Prof Ansari
Normalization is a technique to organize the contents of the table for transactional database and data warehouse.
First Normal Form :
Seeing the data in the example in the book or assuming otherwise that all attributes contain the atomic value, we find out the table is in the 1NF.
Second Normal Form :
Seeing the FDs, we find out that the K for the table is a composite one comprising of empId, projName. We did not include the determinant of fourth FD, that is, the empDept, in the PK because empDept is dependent on empId and empID is included in our proposed PK. However, with this PK (empID, projName) we have got partial dependencies in the table through FDs 1 and 3 where we see that some attributes are being determined by subset of our K which is the violation of the requirement for the 2NF. So we split our table based on the FDs 1 and 3 as follows :
This document provides an architectural overview of the IEEE Montreal Web Portal system using the 4+1 architectural view model. It describes the purpose, scope, definitions, and references. It then outlines the use case, logical, process, deployment, and implementation views to illustrate different aspects of the system's architecture according to the 4+1 view model. The views are described at a high level based on the provided template.
This lab experiment aims to develop a data flow diagram (DFD) model for a given project. A DFD model graphically depicts the flow of data through various processes in a system. It includes level-0, level-1 DFDs and a data dictionary. A level-0 DFD shows the system's context and major processes, while level-1 diagrams provide more detail by decomposing high-level processes. The data dictionary defines all data elements in the DFDs. Developing a balanced DFD model involves matching input/output data between diagram levels. This experiment guides students through drawing DFDs and defining a data dictionary to model the data flow in a system.
CIS 532 STUDY Education Planning--cis532study.comShivendrasing2
This document outlines assignments and case studies for a CIS 532 networking class, including papers on network topology design, security planning, and technical term papers. It provides details on 2 papers for each assignment, which involve designing network solutions, addressing security concerns, integrating routing protocols, and developing a network migration plan within budget for a large retail company. Students are to complete networking design documents, presentations, and case study analyses on topics like wireless solutions, business goals, and quality of service requirements.
This document provides lecture notes on data structures that cover key topics including:
- Classifying data structures as simple, compound, linear, and non-linear and providing examples.
- Defining abstract data types and algorithms, and explaining their structure and properties.
- Discussing approaches for designing algorithms and issues related to time and space complexity.
- Covering searching techniques like linear search and sorting techniques including bubble sort, selection sort, and quick sort.
- Describing linear data structures like stacks, queues, and linked lists and non-linear structures like trees and graphs.
Documentation Workbook Series. Step 3 Presenting Information (Visual Document...Adrienne Bellehumeur
The document provides tips for improving documentation through the use of visuals such as diagrams, pictures, and simple drawings. It emphasizes replacing blocks of text with visual representations of key messages and processes to better engage readers. Exercises are presented for practicing visual documentation skills, such as cartooning meeting notes or modeling personal life processes.
Here are some tips for interviewees:
- Research the company beforehand so you can speak intelligently about them and the role. Understand their mission, values, products/services and culture.
- Have a few stories prepared from your background that highlight relevant experiences and skills for the role. Practice telling them concisely.
- Dress professionally and make eye contact with the interviewer. Smile and be friendly.
- Listen carefully to questions and take a moment to think before answering. Address what the interviewer is asking.
- Ask questions too. Prepare a few in advance that show your interest in the company and role.
- Bring copies of your resume and a notepad/pen
The document discusses assignments for a database management systems course. It includes 6 assignments covering topics like software development processes, software estimation techniques, database concepts, entity relationship diagrams, database normalization, and distributed database systems. The assignments include questions that require explaining concepts, writing SQL queries, and discussing steps to implement database management processes or address issues in case studies.
This Tutorial contains 2 Set of Papers for each Assignment
CIS 532 Week 2 Assignment 1 Request for Proposal Response (2 Papers)
CIS 532 Week 3 Case Study 1 Harriet’s Fruit and Chocolate Company (2 Papers)
Software Project Management: Software Requirement SpecificationMinhas Kamal
Software Project Management: ResearchColab- Software Requirement Specification (Document-5)
Presented in 4th year of Bachelor of Science in Software Engineering (BSSE) course at Institute of Information Technology, University of Dhaka (IIT, DU).
This document provides an architectural overview of the C-Registration System developed by Wylie College to support online course registration. It includes 4 views: use case view, logical view, process view, and deployment view. The use case view describes the key use cases such as registering for courses, maintaining student information, and submitting grades. The logical view shows the system divided into 3 packages - user interface, business services, and business objects. The business services package controls interactions with external systems like the billing system.
#Learnpad Project - results for the Public Survey on learning needs and chall...Andrea Sergiacomi
1) The document reports the results of a survey of 101 civil servants on their learning needs and preferences. It analyzes their responses to 22 multiple-choice questions.
2) Most respondents had over 10 years of experience and a medium level of technical skills. While familiar with social media, only 61% reported good skills with office software.
3) Respondents expected learning resources to be organized by process and ranked detailed instructions, practical examples, and graphical representations as most important in documentation. They also valued guidance from colleagues in problem-solving.
Ifsm 370 project 2 white paper instructionsbestwriter
The document provides instructions for a white paper assignment on proposing a telecommunications solution for the fictitious company Ullman, Manly, & Ulysses Corporation (UMUC). UMUC relies on its network for business operations but its current network managed by an outside company crashes frequently, interrupting customer service. The network management company is unresponsive to issues. UMUC's Chief Information Officer outlined requirements for a new reliable, secure, scalable and cost-effective network. Students must write a 3-page white paper defining UMUC's network problem, recommending a technology solution addressing the requirements, and discussing risks and mitigation strategies. The white paper will be graded based on adequately addressing the assignment requirements.
This document provides a guide for optimizing the performance of Analysis Services multidimensional models from both a development and operational perspective. It covers best practices for cube design, testing, and tuning query and processing performance. The guide is split into two parts - Part 1 focuses on building high-performance cubes through techniques like dimension design, aggregations, and efficient MDX; Part 2 addresses running cubes in production through server configuration, monitoring, maintenance and diagnostics. The document aims to help BI developers and operations specialists optimize Analysis Services solutions.
The document presents a business case for implementing a CRM system for the placements team at IIT Roorkee. It analyzes the need for a CRM to better manage industry contacts and discusses the measurable benefits, including increased productivity, reduced costs, and improved customer service. Various CRM alternatives are considered and SugarCRM is selected for its ease of use, popularity, and support resources. Financial analysis estimates a 375% return on investment over 5 years with payback in under 6 months. Implementation costs and anticipated savings and benefits are outlined.
This document discusses architectural integration styles for large-scale enterprise software systems. It proposes using architectural styles as a way to generalize common integration solutions at the enterprise system level, similar to how styles are used in traditional software architecture. The document defines key terms and presents a structure for describing architectural integration styles. It then describes several example styles, and presents a case study applying the style selection process to an energy company's system integration project. The goal is to provide an approach for selecting integration solutions based on the characteristics of existing systems and desired quality attributes.
Good software architecture for business Anil Sharma
This document discusses software architecture and potential analysis of software systems based businesses. Section 1 defines software and systems architecture, focusing on academic abilities, experience needs, and knowledge requirements for architecture work. Section 2 discusses potential analysis of software systems based businesses, including talent selection, overall industry hiring, profit potential comparisons to other businesses, and considerations for analyzing an internet service business.
This document provides guidance on estimating the effort required for a software development project. It discusses estimating human effort by rating functions as easy, medium, hard, or complex and assigning effort estimates in days. Additional activities like analysis, design, and testing are estimated as percentages of the build effort. Hardware requirements like processor power, disk space, and RAM are also addressed at a high level. The overall message is that project estimation is imprecise but essential, and estimates should be revisited regularly as more information becomes available.
Reengineering including reverse & forward EngineeringMuhammad Chaudhry
The document discusses forward engineering and reverse engineering. Reverse engineering involves extracting design information from source code through activities like data and processing analysis. This helps understand the internal structure and functionality. Forward engineering applies modern principles to redevelop existing applications, extending their capabilities. It may involve migrating applications to new architectures like client-server or object-oriented models. Reverse engineering provides critical information for both maintenance and reengineering existing software.
Machine learning engineers are computer programmers who develop machines and systems that can learn and apply knowledge without specific direction. This article explores the work of machine learning engineers, the skills and education needed for the role, and how to become a machine learning engineer. Key skills include computer programming, strong mathematical skills, and knowledge of machine learning algorithms and libraries. A master's or PhD is typically required for machine learning engineer roles.
The document describes several open positions at an organization, including a Performance Test Lead role requiring deep performance testing experience and strong management skills, a Digital Project Lead position focused on ensuring digital projects meet requirements and standards, and a Data Architect role requiring database modeling experience and knowledge of DB2 or Oracle databases. It also lists a opening for a User Centered Design Researcher to conduct user research throughout the product development process.
The Senior DevOps Engineer is responsible for designing, developing, testing, and maintaining integration processes between enterprise applications for Parker University. This includes developing automation for continuous integration and deployment, supporting applications, and responding to alerts and issues. The role also develops custom integrations involving communication between internal and external teams. Reporting and dashboards are created to aid in monitoring integration processes. A bachelor's degree and 4+ years of relevant experience are required.
The document provides information on a course titled "Software Engineering" taught by Dr. P. Visu at Velammal Engineering College. It includes the course objectives, outcomes, syllabus, and learning resources. The objectives are to understand software project phases, requirements engineering, object-oriented concepts, enterprise integration, and testing techniques. The outcomes cover comparing process models, formulating requirements engineering concepts, understanding object-oriented fundamentals, applying software design procedures, and finding errors with testing techniques. The syllabus covers topics like software processes, requirements analysis, object-oriented concepts, software design, and testing and management over 5 units. Recommended textbooks and online references are also provided.
This document provides an architectural overview of the IEEE Montreal Web Portal system using the 4+1 architectural view model. It describes the purpose, scope, definitions, and references. It then outlines the use case, logical, process, deployment, and implementation views to illustrate different aspects of the system's architecture according to the 4+1 view model. The views are described at a high level based on the provided template.
This lab experiment aims to develop a data flow diagram (DFD) model for a given project. A DFD model graphically depicts the flow of data through various processes in a system. It includes level-0, level-1 DFDs and a data dictionary. A level-0 DFD shows the system's context and major processes, while level-1 diagrams provide more detail by decomposing high-level processes. The data dictionary defines all data elements in the DFDs. Developing a balanced DFD model involves matching input/output data between diagram levels. This experiment guides students through drawing DFDs and defining a data dictionary to model the data flow in a system.
CIS 532 STUDY Education Planning--cis532study.comShivendrasing2
This document outlines assignments and case studies for a CIS 532 networking class, including papers on network topology design, security planning, and technical term papers. It provides details on 2 papers for each assignment, which involve designing network solutions, addressing security concerns, integrating routing protocols, and developing a network migration plan within budget for a large retail company. Students are to complete networking design documents, presentations, and case study analyses on topics like wireless solutions, business goals, and quality of service requirements.
This document provides lecture notes on data structures that cover key topics including:
- Classifying data structures as simple, compound, linear, and non-linear and providing examples.
- Defining abstract data types and algorithms, and explaining their structure and properties.
- Discussing approaches for designing algorithms and issues related to time and space complexity.
- Covering searching techniques like linear search and sorting techniques including bubble sort, selection sort, and quick sort.
- Describing linear data structures like stacks, queues, and linked lists and non-linear structures like trees and graphs.
Documentation Workbook Series. Step 3 Presenting Information (Visual Document...Adrienne Bellehumeur
The document provides tips for improving documentation through the use of visuals such as diagrams, pictures, and simple drawings. It emphasizes replacing blocks of text with visual representations of key messages and processes to better engage readers. Exercises are presented for practicing visual documentation skills, such as cartooning meeting notes or modeling personal life processes.
Here are some tips for interviewees:
- Research the company beforehand so you can speak intelligently about them and the role. Understand their mission, values, products/services and culture.
- Have a few stories prepared from your background that highlight relevant experiences and skills for the role. Practice telling them concisely.
- Dress professionally and make eye contact with the interviewer. Smile and be friendly.
- Listen carefully to questions and take a moment to think before answering. Address what the interviewer is asking.
- Ask questions too. Prepare a few in advance that show your interest in the company and role.
- Bring copies of your resume and a notepad/pen
The document discusses assignments for a database management systems course. It includes 6 assignments covering topics like software development processes, software estimation techniques, database concepts, entity relationship diagrams, database normalization, and distributed database systems. The assignments include questions that require explaining concepts, writing SQL queries, and discussing steps to implement database management processes or address issues in case studies.
This Tutorial contains 2 Set of Papers for each Assignment
CIS 532 Week 2 Assignment 1 Request for Proposal Response (2 Papers)
CIS 532 Week 3 Case Study 1 Harriet’s Fruit and Chocolate Company (2 Papers)
Software Project Management: Software Requirement SpecificationMinhas Kamal
Software Project Management: ResearchColab- Software Requirement Specification (Document-5)
Presented in 4th year of Bachelor of Science in Software Engineering (BSSE) course at Institute of Information Technology, University of Dhaka (IIT, DU).
This document provides an architectural overview of the C-Registration System developed by Wylie College to support online course registration. It includes 4 views: use case view, logical view, process view, and deployment view. The use case view describes the key use cases such as registering for courses, maintaining student information, and submitting grades. The logical view shows the system divided into 3 packages - user interface, business services, and business objects. The business services package controls interactions with external systems like the billing system.
#Learnpad Project - results for the Public Survey on learning needs and chall...Andrea Sergiacomi
1) The document reports the results of a survey of 101 civil servants on their learning needs and preferences. It analyzes their responses to 22 multiple-choice questions.
2) Most respondents had over 10 years of experience and a medium level of technical skills. While familiar with social media, only 61% reported good skills with office software.
3) Respondents expected learning resources to be organized by process and ranked detailed instructions, practical examples, and graphical representations as most important in documentation. They also valued guidance from colleagues in problem-solving.
Ifsm 370 project 2 white paper instructionsbestwriter
The document provides instructions for a white paper assignment on proposing a telecommunications solution for the fictitious company Ullman, Manly, & Ulysses Corporation (UMUC). UMUC relies on its network for business operations but its current network managed by an outside company crashes frequently, interrupting customer service. The network management company is unresponsive to issues. UMUC's Chief Information Officer outlined requirements for a new reliable, secure, scalable and cost-effective network. Students must write a 3-page white paper defining UMUC's network problem, recommending a technology solution addressing the requirements, and discussing risks and mitigation strategies. The white paper will be graded based on adequately addressing the assignment requirements.
This document provides a guide for optimizing the performance of Analysis Services multidimensional models from both a development and operational perspective. It covers best practices for cube design, testing, and tuning query and processing performance. The guide is split into two parts - Part 1 focuses on building high-performance cubes through techniques like dimension design, aggregations, and efficient MDX; Part 2 addresses running cubes in production through server configuration, monitoring, maintenance and diagnostics. The document aims to help BI developers and operations specialists optimize Analysis Services solutions.
The document presents a business case for implementing a CRM system for the placements team at IIT Roorkee. It analyzes the need for a CRM to better manage industry contacts and discusses the measurable benefits, including increased productivity, reduced costs, and improved customer service. Various CRM alternatives are considered and SugarCRM is selected for its ease of use, popularity, and support resources. Financial analysis estimates a 375% return on investment over 5 years with payback in under 6 months. Implementation costs and anticipated savings and benefits are outlined.
This document discusses architectural integration styles for large-scale enterprise software systems. It proposes using architectural styles as a way to generalize common integration solutions at the enterprise system level, similar to how styles are used in traditional software architecture. The document defines key terms and presents a structure for describing architectural integration styles. It then describes several example styles, and presents a case study applying the style selection process to an energy company's system integration project. The goal is to provide an approach for selecting integration solutions based on the characteristics of existing systems and desired quality attributes.
Good software architecture for business Anil Sharma
This document discusses software architecture and potential analysis of software systems based businesses. Section 1 defines software and systems architecture, focusing on academic abilities, experience needs, and knowledge requirements for architecture work. Section 2 discusses potential analysis of software systems based businesses, including talent selection, overall industry hiring, profit potential comparisons to other businesses, and considerations for analyzing an internet service business.
This document provides guidance on estimating the effort required for a software development project. It discusses estimating human effort by rating functions as easy, medium, hard, or complex and assigning effort estimates in days. Additional activities like analysis, design, and testing are estimated as percentages of the build effort. Hardware requirements like processor power, disk space, and RAM are also addressed at a high level. The overall message is that project estimation is imprecise but essential, and estimates should be revisited regularly as more information becomes available.
Reengineering including reverse & forward EngineeringMuhammad Chaudhry
The document discusses forward engineering and reverse engineering. Reverse engineering involves extracting design information from source code through activities like data and processing analysis. This helps understand the internal structure and functionality. Forward engineering applies modern principles to redevelop existing applications, extending their capabilities. It may involve migrating applications to new architectures like client-server or object-oriented models. Reverse engineering provides critical information for both maintenance and reengineering existing software.
Machine learning engineers are computer programmers who develop machines and systems that can learn and apply knowledge without specific direction. This article explores the work of machine learning engineers, the skills and education needed for the role, and how to become a machine learning engineer. Key skills include computer programming, strong mathematical skills, and knowledge of machine learning algorithms and libraries. A master's or PhD is typically required for machine learning engineer roles.
The document describes several open positions at an organization, including a Performance Test Lead role requiring deep performance testing experience and strong management skills, a Digital Project Lead position focused on ensuring digital projects meet requirements and standards, and a Data Architect role requiring database modeling experience and knowledge of DB2 or Oracle databases. It also lists a opening for a User Centered Design Researcher to conduct user research throughout the product development process.
The Senior DevOps Engineer is responsible for designing, developing, testing, and maintaining integration processes between enterprise applications for Parker University. This includes developing automation for continuous integration and deployment, supporting applications, and responding to alerts and issues. The role also develops custom integrations involving communication between internal and external teams. Reporting and dashboards are created to aid in monitoring integration processes. A bachelor's degree and 4+ years of relevant experience are required.
The document provides information on a course titled "Software Engineering" taught by Dr. P. Visu at Velammal Engineering College. It includes the course objectives, outcomes, syllabus, and learning resources. The objectives are to understand software project phases, requirements engineering, object-oriented concepts, enterprise integration, and testing techniques. The outcomes cover comparing process models, formulating requirements engineering concepts, understanding object-oriented fundamentals, applying software design procedures, and finding errors with testing techniques. The syllabus covers topics like software processes, requirements analysis, object-oriented concepts, software design, and testing and management over 5 units. Recommended textbooks and online references are also provided.
The document defines enterprise architecture and discusses its key components and levels of detail. It also reviews major industry trends like big data, data analytics, mobility, and cloud computing that enterprise architects should focus on. The benefits of enterprise architecture are outlined as more efficient IT operations, reduced business risk, and faster time to market. Customer relationship management (CRM) aims to increase profitability through solidifying customer satisfaction and loyalty. True CRM provides a holistic view of customers to inform business decisions.
The document provides information on a course titled "Software Engineering" taught by Dr. P. Visu at Velammal Engineering College. It includes the course objectives, outcomes, syllabus, and learning resources. The objectives are to understand software project phases, requirements engineering, object-oriented concepts, enterprise integration, and testing techniques. The outcomes cover comparing process models, requirements engineering, object-oriented fundamentals, software design, and testing techniques. The syllabus covers topics like software processes, requirements analysis, object-oriented concepts, software design, testing, and project management over 5 units. Recommended textbooks and online references are also provided.
Software Archtecture.
Software design is a process to transform user requirements into some suitable form, which helps the programmer in software coding and implementation.
Software design is the important step in SDLC (Software Design Life Cycle), which moves the concentration from problem domain to solution domain. It tries to specify how to fulfill the requirements mentioned in SRS.
Software design plays an important role in developing software: during software design, software engineers produce various models that form a kind of blueprint of the solution to be implemented
Requirements management and the business analystRobert Darko
The document discusses the roles and responsibilities of various professionals involved in requirements management using SharePoint. It describes the roles of the Business Analyst, System Administrator, Super User, SharePoint Designer, Web Developer, and End User. The Business Analyst acts as a liaison between business and IT, gathering requirements and ensuring alignment. The System Administrator focuses on backend configuration and integration. The Super User configures SharePoint sites to meet business needs without coding. The SharePoint Designer customizes sites using workflows, databases, and branding. The Web Developer handles complex integrations and customizations. Training requirements and workloads are also outlined for each role.
A systems analyst is an IT professional who analyzes, designs, and implements information systems to solve business problems. The primary role of a systems analyst is to study organizational problems and needs to determine how people, methods, and technology can be combined to improve the organization. Systems analysts must develop analytical, technical, managerial, and interpersonal skills. They work with users to define requirements, help design and test solutions, and ensure new systems are implemented smoothly and train users.
CHAPTER 10 SystemArchitectureChapter 10 is the final chapter.docxcravennichole326
This chapter discusses system architecture, which translates the logical design of an information system into a physical blueprint. It covers a wide range of topics to support the overall system design, including servers, clients, processing methods, networks, and related issues. When planning the system architecture, a systems analyst must consider issues like corporate organization, costs, scalability, legacy systems, security, and processing options. The chapter traces the evolution of system architecture from early mainframe-based designs to current client/server architectures and cloud-based solutions.
The document discusses the design phase of the system development life cycle. It describes the objectives and steps of the design phase, which include presenting design alternatives, converting logical models to physical models, designing the system architecture, making hardware and software selections, and designing inputs, outputs, data storage, and programs. Common design strategies like custom development, packaged systems, and outsourcing are also covered. The document then explains various system design methods and the stages of system design, including logical, physical, and program design. Finally, it discusses avoiding common design mistakes.
Computer Science Network Design and Management for a 300 Room Hote.docxpatricke8
Computer Science Network Design and Management for a 300 Room Hotel with meeting rooms that support Video Conferencing Technology.
Your client is requesting a written analysis of your design explaining the technology and why you think this design will work. It needs to be secure, scalable, and cost effective.
Deadline – January 17, 2014 - 6PM EST - Length 8 to 10 Pages
I will pay $75 for this assignment.
Course Project – Using APA Style Guidelines, Design and describe the LAN topology and
strategies
of a wireless and wired LAN for a 300 room hotel with 60 employee’s providing customer service, video conference services in the meeting rooms, Wireless service for guests, and an administrative hotel network for the hotel staff.
The hotel staff utilizes Windows 7 desktop and laptop devices with MS Office 2010 products, utilizes email, network printers, Quickbooks for payroll and invoicing, and hotel guest reservation tracking software.
Ruckus wireless equipment will be used, HP or Cisco switching and routing equipment will be used.
The fully completed Network Design Project includes a title page (include your name, date, title of your plan), the Executive Summary and the content outlined, plus any applicable tables, graphs or attachments.
Footnotes (or endnotes) and a Bibliography are required.
You must use no less than 6 verifiable resources .
Cite all sources. All references must be cited in two places: within the text and on a reference list.
Key Objectives to address in paper:
1. Analyze Business Goals, technical goals, and network constraints as you describe both the network design process and the factors that require the goals and constraints to be a part of the network management process.
2. Characterize the network traffic and network requirements as you establish the performance criteria and constraints for a data network and identify several potential solutions that yield an optimal network.
3. Utilizing the network topology, describe standards and protocols used in the network architecture ( example – VLAN’s, switching, and routing protocols ), understand major problems associated with network management, and describe standard functions and strategies to manage these problems.
4. Understand tools, equipment, and techniques required to effectively monitor and manage the Campus network, its traffic type, and the status of different devices on the network.
Compare and contrast the major management tools available for day-to-day network management.
5. Optimize and test the network design solution - identify the optimal solution for a data network to satisfy a given set of performance criteria and constraints for the support of a network carrying multimedia and videoconferencing.
Develop a design strategy that provides the high bandwidth, high QOS, and low delay required for such applications.
6. Given a network design, identify an optimal network security strategy for the network design, including wireless networks.
COURSE .
This document discusses the differences between requirement engineers and architects in the software engineering field. It aims to clarify misconceptions about their roles by outlining their different responsibilities and job profiles. The document begins by describing requirement engineers and architects, examining their roles and tasks. It looks at similarities and differences between the profiles, as well as other related job roles. The conclusion provides insights gained from comparing requirement engineers and architects.
This document discusses the differences between requirements engineers and architects in software engineering. It aims to clarify misconceptions about their roles by listing the differences in their responsibilities, job profiles, and skills. The document will examine what tasks each profile performs, any differences and similarities between them, and take a brief look at other related profiles. It concludes by providing insights gained from comparing requirements engineers and architects.
A business analyst helps bridge the gap between business needs and technical solutions. They analyze an organization's structure, business models, processes and requirements. This includes strategic planning, process design, and interpreting business rules for technical systems. The business analyst ensures the technical solution meets the business goals. Key deliverables include business requirements, functional specifications, user needs documents, and traceability matrices to track requirements throughout the project. Having a business analyst involved in software projects helps clearly define needs and prevents miscommunication between stakeholders and developers.
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Starting from January 2024, the full weekly and monthly reports will only be available for free to VCOSA members. To access the complete weekly report with figures, charts, and detailed analysis of the cotton fiber market in the past week, interested parties are kindly requested to contact VCOSA to subscribe to the newsletter.
We are pleased to share with you the latest VCOSA statistical report on the cotton and yarn industry for the month of March 2024.
Starting from January 2024, the full weekly and monthly reports will only be available for free to VCOSA members. To access the complete weekly report with figures, charts, and detailed analysis of the cotton fiber market in the past week, interested parties are kindly requested to contact VCOSA to subscribe to the newsletter.
Generative Classifiers: Classifying with Bayesian decision theory, Bayes’ rule, Naïve Bayes classifier.
Discriminative Classifiers: Logistic Regression, Decision Trees: Training and Visualizing a Decision Tree, Making Predictions, Estimating Class Probabilities, The CART Training Algorithm, Attribute selection measures- Gini impurity; Entropy, Regularization Hyperparameters, Regression Trees, Linear Support vector machines.
Discovering Digital Process Twins for What-if Analysis: a Process Mining Appr...Marlon Dumas
This webinar discusses the limitations of traditional approaches for business process simulation based on had-crafted model with restrictive assumptions. It shows how process mining techniques can be assembled together to discover high-fidelity digital twins of end-to-end processes from event data.
2. Contents
1. Systems & architecture thinking...................................................................................................4
2. Complexity handling: Job complexity, careerevents & mind changes.............................................6
3. Detailed “functional network” processing.....................................................................................9
1. Inter-personal communication: ...............................................................................................10
2. Information analysis: .............................................................................................................10
a) Reading between the lines:.....................................................................................................10
b) “A picture is worth a thousand words.”: ..................................................................................11
c) PIP or picture in picture feature:.............................................................................................11
d) “Frame of reference” context is important: ..............................................................................11
4. Skills development focus............................................................................................................12
5. Corporate fit testing..................................................................................................................14
6. Organization fit.........................................................................................................................16
7. Personal development tracks.....................................................................................................19
3. Personality aspect of a software architect
“Y” in front of “ours” is “Yours”. Anonymous
There are multiple career tracks available for individuals interested in software and computing
systems based industry and businesses (our main focus). Just to name a few at very high level:
Technology development
Technology management
Engineering management
Project/Program management
Marketing & sales
Customer and other support services etc
Some of these career tracks would need people with more hands on experience while others
would need people who are either very good in subject matter understanding or are better at things like
personal interaction, inter-personal communication, use of management procedures and tools etc. Import
aspects for some careers are macro-level personal development and keeping global views such as for
architecture and management work streams, while for some others micro view and deep focus on nitty-
gritty along with desire for deep dive into minutia and details would be more import. This is especially
true for things like hands-on technology development and question and answer type customer & sales
support type of roles.
Work relationships also come in many flavors these days. Some important ones are “permanent
employment”, consulting relationship through brand name consulting companies, boutique consulting
relationships or even personal consulting practices along other very popular arrangements such as
outsourcing, specialty tasks partnerships and channels. Based on business requirements, some functions
would become essentially internal only and some functions could easily become external outsource-able.
Since we would mainly focus on software architect role in this write-up, let’s focus on
identification of core set of attributes which would set apart a good architect from a bad one very
analytically to start with. At very high level, we can identify most important personality attributes most
needed of a successful architect kind of person and then we would venture into the detailed analysis of
some core development which happen in a person through his academics and career development which
would make him a good fit for such role.
To begin with some of the personality attributes one can easily identify for a role that would need
macro and global view, detailed micro-processing as well as high level focus needed almost at the same
time, long-term career track enabling development of technology understanding along with good
exposure to management tools and standard procedures, complexity management, knowledge gathering,
working with others, product life cycles, business requirements understanding and corporate level
overview on software, systems & solution prepositions. Let’s go in details of some of these items step by
step and understand key sub-requirements and needed results out of these expectations.
4. 1. Systems & architecture thinking
System and architecture work is not single dimensional work as are many other jobs are such as
coding, scripting, taking sales orders and voice support on phone calls.
You have to be a multi-dimensional person at the very least for good deliveries at work place if you
want to be a good software architect. For example, let’s look at a telecom standards and protocol design
architect’s role. Someone who would not only understand and verify almost legally qualify-able message
exchanges through multi-node systems but also would design systems and its components in such as way
that system is “finite” even for 30 to 40 to 50 stages of laddered processing (something that even a normal
computers can’t achieve independently over days of processing, needs processing of almost 1000 graphs).
Reading thru Text (1 Dimension work) skill wouldn’t be sufficient for development of even basic
understanding of requirements of this type of work that has structured, defined and pre-established work-
flows. Skill that enables the ability for understanding “Text with Picture & Data (2 Dimensions)” would
be minimum requirement for even proper reading and imbibing the standards and protocols specification.
For engineering design work around it though, one would essentially need skill for working with “Text
with two dimensional pictures & data (3 Dimensions)” as you would have to break the specification into
finite sub-parts and would have to get to 1 more level down before properly solving it and define needed
data structures and algorithms for working through further stages of processing. And you would have to
do this in ways that the whole system still converges and works almost perfectly with 100% accuracy for
infinite life. Some of the careers where workings in 3 dimensions like the one mentioned above is norm
are space research, electronic circuit improvement, data science or serial processing software or for that
matter econometrics would need this type of visualizing skill for heavy lifting phase of work deliveries..
One example of architecture thinking is “Continuous operations improvement” in development and
software delivery process operations. This would entail continuous data analysis and feedback control
systems’ understanding for making operations better. This is sort of data science approach to solving
problems or Devops improvements on Devops’ed processes. You could define it as Devops Squared. Any
name out of following list of names would fit the bill for further automation on already optimized tasks:
{ DevOps 2
}, Pipeline of DevOps projects, DevOps on DevOps, Data Science
Process improvement or engineering processes is a skill that you develop during you education
career at college. For example, during a four year undergrad program new skills or tools a student gets
introduced to 1 year at a time are:
Eg. Engineering processing – for engineering career
1. Engineering tasks introduction (Welding, Painting, Chisel, Filing, Cutting & Humanities etc) –
Division of engineering tasks –Job creation, steps identification (both hands together same plane)
– Mental fit testing
2. Multi-plane hands movement coordination (drawings of various types: engineering, mechanical,
electrical, electronics and computer science (flow charts))- both hand taking decisions at same
time i.e. scale and pencil – Career fit testing
5. 3. 1,2,3 -> Linear structured simple processing for normal Math Civil, Mechanical and electrical
engineering projects – Technology fit testing
4. Brain tuning for different types of processing (multi) for information, historical knowledge and
data at same time: linear, structured, decimal & binary both (Eg. Start of computer science,
electronics, communication engineering)
Bits processing in electronics and computer science:
0 or 20
= 1 value
1 or 21
= 2 values
3 or 23
= 8 values
4 or 24
= 16 values
6 or 26
= 64 values
8 or 28
= 256 values
These are very general purpose tools if you analysis and focus on fundamental requirements of
what you are suppose to learn out of these new learnings. They would mostly apply to any field of work
where such improvement and efficiencies would make sense. For example, there is a lot of focus these
days on Artificial Intelligence technologies and innovation drive that is on in this new area of computer
science development. However, unless you further break it down in its fundamental components and
make it “applicable” to task at hand, you wouldn’t get to any benefits out of new research work in this
area of computer science. For example, to make it further applicable for corporate business use, you
would have to sub-divide it and then would have to apply components of it to improvement of routine
corporate tasks. Whether it is using data science part of it or using devops part of it. Here is an example
derivation and then further subdivision:
Stage 0: Artificial intelligence
Stage 1: Applied intelligence
Substage 1.1: Business intelligence
Substage 1.2: Operations intelligence or DevOps
Substage 1.3: Data intelligence i.e. Data Science
Substage 1.4: Innovation intelligence (better computers or better networks to better
computing power and better and secure access) i.e. things like CI/CD or Orchestration
Automation
Substage 1.5: Sales and marketing intelligence, Analytics planning and reporting
With better automation capabilities and we have now become more and more dependent on
machines. These days it is easy to get to up to 80% level on automated tasks coverage if not 100%. The
80% level is better than no machine use when it has become so cheap to use them. As we know nothing is
fundamentally perfect. Perfection itself is not perfect i.e. it is not singularity in its entirety. In some cases,
you can never make better enemy of good This is more true in growing fields and there is sometime no
choice but to work with good enough and improve things little by little one step at a time until you
somehow know what is the best possible scenario and have some known way of getting to it.
6. Machines weren’t fast enough and good enough in past and lots and lots of people worked on
making machines even more faster, better looking and more cleaner until there was this “good-enough” fit
for 90%.of the users. Cars weren’t fast enough and good enough and lot and lots of people worked on
making cars even more faster and finer looking until there was this “good-enough” fit car that satisfied
the need for 90%.of the folks. Flying machines weren’t fast enough and good enough and lots and lots of
people worked on making flying machines even more faster and more reliable until there was this “good-
enough” fit plane that was suitable flight experience for 90% of the folks.
Similarly computers and networks weren’t fast enough and good enough and lot and lots of
people worked on making computers and networks even more faster, better designed until this
“goodenough” fit perfect connected computer for the only bought comport for 90% of the folks and same
things are now happening to cellular phones. Similarly businesses weren’t transparent enough and
dependable enough and lot and lots and lots of people worked on making business results and outcomes
more transparent and visible to all stakeholders and dependable for owners up to the levels of 90%.
Technological singularity has now new frontiers. There are many new areas of focus. Just to name the
few: human brain, robots & automation, applied intelligence.
Systems and architecture thinking itself has grown to new levels now and it is now good tool for
even some of these newer technologies at their very inception: certainly a better start over some of the
older innovations stories we know about falter at the very beginning because of lack of better tools and
technological understandings. Our knowledge around software and electronics use for problem solving
has improved up to the level of almost human intelligence since.There are also many types of software
systems. Some examples are as follows:
1. Software applications: Left brain or parallel system
2. Communication software over multiple nodes: Right brain or n-stage serial software
3. Data Management, Analytics & Science: Front brain, huge information memory and timeline nodal
point software
4. Social, platform and business solution context in system architecture: Back brain for adjacency
sensitivities and valuation system for software
2. Complexity handling: Job complexity, career events & mind changes
Software programming it-self is a complex function for human brain. On top of it, software systems
with lots and lots of intelligence in them, procedure automation and need for complex multi-disciplinary
and multi-language software platforms create even more challenge for decision makers and architects
working on such systems/platforms. Human brain goes through changes when it is being trained for such
work.
With slowdown in progress of advancements in technologies such as computing, electronics
(Moore’s law doesn’t work anymore!), software systems (open-source has taken out “IP” novelty out of
lots of software systems), storage and networking etc; process understanding, improvements in
7. performance, multidisciplinary knowledge and multi-dimensional experience has already started
becoming forefront technological competition. It’s no wonder that people with such skill set would be
sought after resources in years to come.
About 10 years ago processer clock speeds stopped doubling every 18 month (density of transitors) or
so and miniaturization stopped decreasing (already at atoms level) sizes. Almost 20 years of global focus
and competition has brought computing technologies’ innovation to a point where it has now become
highly dependent on almost revolution in other technology areas for further improvement in this space.
Few new choices or dimensions of growth are
1. Social computing
2. Quantum computing
3. Genetic computing
Intellectual Property creation is again back to “Human” from machines and systems (sort of IP
manufacturing that was on for years!!). With these high level changes in technology landscape, human
brain neuron would become new set of electronic transistors.
Development of human brains’ computing capability i.e. activation of more and more neurons in
human brain (Moore’s law’ on human brain neurons!) would also become a competitive parameter and
would add to total computing power of states, countries and the world. Capable, well trained and fresh
talented brain source would be sought after destination for innovative work.
With education, experience and knowledge gathering human brain goes through multiple changes as
was mentioned before. Here is a sequence of changes that is sort of a normal progression of brain
development for someone who is involved in complex, multidisciplinary, decision making job:
1. Neuron firing: Simple steps
2. Neuron path in brain: Organized but simple and straight forward control procedures
3. Neuroplasticity: Complex, Challenging and Risky decision making
4. Neural networks: Multidimensional, multi-field, multidisciplinary work (switch)
5. Hippocampus activation for neural network management: More than 3 -4 thinking areas active at
the same time for decision support
Graphical representation of above mentioned process can be shown as follows:
(Hippocampus management of procedural memory, language switching and decision making for conflict
resolution)
Stage 1: Neuroplasticity because of longer term complex work -> Hippocampus activation
(Brain capability achieved: Multi-disciplinary decision making, memory ready for multi-dimensional
knowledge gathering, operations and procedures simplification capability, connectivity for multi-field
decisions)
8. Stage 2: Brain ready for multi-disciplinary, multi-dimensional work
Following diagram shows effects on human brain of multiple active areas working at the same for
years. Because of work experiences which involved working with different sections of brains at the same
time and needed active switching between brains parts, brain would have developed higher level neuron
plasticity between different parts of brain in this second case thereby activating hippocampus.
A person who is involved in operations understanding and simplification work (procedures and
programs both), works on systems which need activities in multiple areas of brain i.e. front brain (data
science) left side brain (business/economic) and right side brain (physics, programming) at same time and
is also responsible for multi-field work (active switching of technologies and programming languages)
Multidisciplinaryactivitytraining
Three differentswitchesactive atthe same-
time (complex programmingformulti-
disciplinary,multi-languageplatform)
9. because of involvement in complete system and platform development would have almost developed such
brain.
A good example person would be a devops system/platform designer and architect who is
involved in multi-field/multi-disciplinary work from below technology area:
{ DevOps 2
}, Pipeline of DevOps projects, DevOps on DevOps, Data Science
In the realm of “organization behavior studies”, above developments in human brain and its
manifestation in day to day work life could be outlined and compared with average development of
normal resource as follows:
3. Detailed “functional network” processing
For roles in which subject matter expertise in multiple areas is almost must such as a system
architect’s or software platform architect’s role, person has to not only know and be handy at a lot of
decision parameters and facts about the whole work-stream area but also should have capability to dive
deeper in the context when needed. For deeper understanding of any concept, content and background
material you would have to properly process, analyze and synthesize it.
Connectivity between parts of subject matter and it’s connectivity with other known facts and figures
has to be established and stored. On top of it, it has to be easily accessible again in memory for future
reference. Consistent exercise of these faculties of human brain would develop certain capabilities in
10. person’s body and brains. Here are some memory, brain use and decision processing impacts which
would become easily noticeable in such a person’s work related information processing:
1. Inter-personal communication:
Communication skills development happens over growth period in early and mid career life of any
individual when the person inside gains his attitude, creates his persona and establishes his relationship
circle. Here are few stages a person goes through when he goes out and work in the bigger world outside
of his personal social circle. He deals with different types of folks in different stages and walks of life and
learns to share information, feelings and thoughts with external world. Language skills development
happen in following stages:
Stage 1: Speak (mind, heart, feelings, thinking etc)
Stage 2: Speak – Listen (empathetically, sympathetically, honestly)
Stage 3: Speak – Listen – Connect (in full light, proper understanding and context)
Stage 4: Speak – Listen – Connect – Process (intellectually, intelligently and timely)
Stage 5: Speak – Listen – Connect – Process – Analyze (using proper tools, learnings, education)
Stage 6: Speak – Listen – Connect – Process – Analyze – Weigh (emotionally, fairly and equitably)
Stage 7: Speak – Listen – Connect – Process – Analyze – Weigh – Tell (to people, audience, learners)
2. Information analysis:
a) Reading between the lines:
Reading through text would not be just simple reading through text for multi-subject matter
expert as it is for a normal “single” subject matter area person. Reading would generate a mental picture
of this new “information” to multiple memory storage areas in such a person’s brain as his memory will
read this new “text” information in the light of a lot of existing knowledge from multiple subject matter
areas stored in many different brain and memory parts. Brain would try to associate this new processing
to multiple areas simultaneously and it would trigger “decision” making about each and every opinion
statement which would be generated by different subject’s understanding. Hence new information would
be stored as a branch with multiple leaves pertaining to multiple different subject matter areas.
Dimensional or disciplinary view of text as it gets stored in human brain in summarized way
would stay there for longer period of retention:
“Text summary” as it gets stored within a node in multi-disciplinary human brain
Textprocessing
Pointersubjectmatter1
Pointersubjectmatter2
Pointersubjectmatter3
11. b) “A picture is worth a thousand words.”:
This is more true in some subject matter areas over others i.e. statistics would have more
information summarized and presented to you in the form of 3 to 4 dimensional charts while history
would mostly have simple dimension timeline in text. Otherwise, in simple words, some people would
generate that thousand word’s information from a picture more effectively over others.
Some subject matter areas expertise would trigger multi-dimensional or multi-disciplinary
analysis for picture formation in human brain and some others would not enable that feature in human
brain “picture” would just stay as picture element. Multi-field multi-dimensional information would
generate an image or understanding in brains of and information analyst as follows:
This image would clarify difference around text processing and image processing both by some
brains and just single timeline text processing by others.
c) PIP or picture in picture feature:
“PIP” or picture in picture sort of processing for multi-disciplinary and multi-dimensional
elements helps deeper understanding of complex subject matters. This is sort of saying that not only text
and pictures are properly processed but also sub-content in them is processed at the same level of
technical expertise. In terms of “programming lingo” you would define it as processing structures of
multiple programming languages and multiple varied sources of code origin to the level of elements to
elements mapping for proper assignments and associations.
d) “Frame ofreference” context is important:
Especially in diverse work, multi-disciplinary and multi-dimensional view is highly important. A
person who would work in such work-area would develop some faculties and abilities inside of him.
Single view) Textprocessingwith1D imagesin-line with text
Multi-view) Addl.storage of X,Yand Z elementsandsummaryfromchartinfo
Some timelinepointeratsame level
Textprocessingwith3-D
imagesin-line withtext
One level
deep
Textprocessingwith3-D
imagesin-line withtext
One level
deep
Subjectmatter
linkages
12. Some of these would even be physically visible in the form of anatomical changes. Someone who solves
complex problems would developer highly efficient categorization or data management skills to the
extent of properly framing even the unimportant and minor things in very efficient and “beveled” frames
of content in brain. They come handy many times in decision making.
In other words notion of nodes or hierarchical connectivity (sort of well outlined frames of reference)
between work elements would be visibly strong and mind-mapped in such brains and brain would have
proper frame based categorical processing for these element as shown above.
4. Skills development focus
For multi-disciplinary, multi-field and complex work, constant focus and deeper idea development
skills are needed. In such jobs, perfect knowledge along with very strong background and constantly
progressive experience is must. One such example would be mathematics knowledge development along
with development of computer science knowledge in computing careers. Usual development track for
such careers would certainly have basic requirements of constant learning, knowledge accumulation and
skill-set development. Someone whose job is highly analytical would have developed mathematics
knowledge with career progression as complexity of the jobs would have required deeper understanding
of core and adjacent concepts both from science and mathematics field.
Along with that, person would have to have risk taking and challenge seeking ability developed by
developing penchant for attempting “unsolved”, “unique”, “8x8 multiple subject areas” and “multi-field
complex” problems. One example mathematic skills development ladder that such a person would have
followed while solving computer science problems in last 30 to 40 years of constant computer science
development is as follows (“10” levels of mathematics knowledge development in computer science in
this period):
Skills development track: Eg. Mathematic
(Last 30 years of computer science & computer engineering development):
Contextframe
Textprocessingwith
3-D imagesin-line
withtextandits own
inertial frame
One level
deep
Contextframe
Textprocessingwith
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13. 1. Arithmetic
2. Algebra
3. Geometry
4. Trigonometry/Time
5. Calculus/Metrics
6. Probability, Statistics, Number systems, Abstract and dimensional math, Signals, circuits &
control systems, Defense science math
7. Stochastic, Randomness, Space, Computational and informational theory
8. Spatial/geo, n-discreet, n-order, n-dimensional
9. Hypothesis testing, Game theory, Decision science, Optimization, Econometrics, Business
Ratios, Modeling. Valuations
10. Deductive & Predictive Analysis, Derivatives, Multiple regressions and data science
algorithms
As one would have already noticed, complexity increases as you go down the “learnings” list for
mathematics shown above. In case someone uses this knowledge for solving problems in some other area
“such as computer science”, complexity for understanding of that area increases as well as one would
have to map newer learnings to newer requirement in that adjacent area. Multi-field knowledge “use”
based highly differentiated jobs would needed academic calibration type of calibration for job
performance measurements. One such test scale is shown below:
Academic: Day to day work performance level based on academic ability calibration:
Performance in knowledge industry jobs highly co-relates with person’s academic ability as most of
the work requirements are similar to requirements for a good student. High memory retention, good
problem solving skills, good reasoning ability and highly disciplined behavior are some of such
Case 1
Case 2
Case 3
14. requirements. One such academic ability calibration method that can easily be used in performance
measurement for such jobs is shown above. There is example of 3 different types of performers in the
above diagram:
Case 1: Day-to-day performance level: 40%, Exam prep drive: 25%: Very low stickiness for future
reference; “Longer” time for exam prep. Highs and lows around exam time. No time for value add work,
over cramming even over “mental” and “genetic” abilities
Case 2: Day-to-day performance level: 60%, Exam prep drive: 25%: Very low stickiness for future
reference; “Longer” time for exam prep. Highs and lows around exam time. No time for value add work,
too much cramming for storing pre-solved problems
Case 3: Day-to-day performance level: 80%, Exam prep drive: 5%: Very high stickiness for future
reference; don’t have to exert two much for exam prep (5%) because of constant disciplined learnings;
Can devote time to useful value additions such as creativity, extra projects and new challenges, attempt at
problems in exam over writing “bookish” pre-prepared, pre-canned answers
The difference between 3 categories of individuals would be very clear and would show up in their
job as lack in risk taking, no creativity and highly undisciplined behavior.
Other such tool for similar kind of benchmarking is comparison between examination performance of
two test candidates. For example, here is a comparison between two students on their exam attempt
philosophy. Similar data analysis would give you your right choice:
Name Total
Score
Attempted
Exam.
Scored
Marks
% Scoring Accuracy Rate
(confidence interval)
Comment
“A” 100 85 81 95% Excellent read, good drawing, good
handwriting and story telling
“B” 100 100 85 85% Just average throw away story. No
use of good writing tools such as
drawing, handwriting and story telling
5. Corporate fit testing
As and when an employee or researcher joins a new team, a “corporate” fit test for him starts in new
place of work almost on the first day. Multiple groups or job ladders at work would test the person for his
fit in new organization in a real testing environment or in a virtual one. Some examples of corporate
laddering are:
Workers ladder
Idea generation ladder
Research focus and industry association ladder
Employee and corp. “identity” ladders
Learners, trainees and researchers ladders
Such laddering even exists in academic community and colleges. Students are profiled and placed in
some “bucket” based on their core abilities either in education rankings or in other academic testings such
15. as general knowledge and intelligence testing, sports and leadership performance or social group
networking abilities.
Following example shows students’ rankings for learners or subject matter focused students who are
highly efficient in scoring on subject matter and in some cases even using any means. Electronics,
Communication and computer science student careers benchmarked on masters or undergraduates scoring
range of student (another academic type of scale):
S. No. %age Scoring
Range
Career choices Class %age in such careers
1. 85%
Research, knowledge &
consulting
5% (A+ students)
2 80%
Knowledge, consulting &
management functions in
same area
10% (A students)
3 75%
Administration, Management,
Process & procedures
improvement consulting
15% (B= students)
4 70%
Industry & brands roles,
Management track in
companies
20% (B students)
5. 65%
Industry & brands,
Supervisory roles
25% (C+ students)
6 60% Jobs market 20% (C students)
7 55% Jobs market chance 5% (qualified, grace, * students)
Different types of work places or for that matter research environment/institute of higher learning
provide you different types of culture, feel and opportunities. From my own experience, I can hardly
forget my past experiences about certain places. For example, following memories from my past
experiences at workplaces, research opportunities or higher study opportunities are always going to stay
with me:
From my past experiences:
DIT education program provided unparallel and exceptional tailoring autonomy and for that
purpose to just an undergraduate student i.e. open selections from wide range of course work
from electronics-mechanics-communication engineering and computer science/engineering.
Who can forget CDOT India and Duet India breakfast line interactions with colleagues?
DRDO India shadowing opportunity was fantastic and equally good was New York City weekend
study experience.
Cisco University & training programs were that of a top 20 university level.
Cornell classroom learning experience and Santa Clara classroom presence was incomparable.
Avaya 1:1 with executive was unique and so was Sandvine small company feel.
16. Google café would always be unforgettable and so would part-time education experience at
University of California, Santa Cruz.
Similarly every workplace or education place has some uniqueness. You would just have to imbibe
and inhale it to savor it. At very high level engineering or technical work can very well be mapped to
education goals of technical programs. For example here is a table that show target goals for technical
education in generality which should apply to any field of engineering in work place too.
Above mentioned three core groups would define even three or four major work groups in technology
oriented companies’/workplaces when it comes to major classification.
1. Job and employee groups
2. Behavioral and fit based grouping
3. Corporate organization groups
4. Social network and people groups
5. Education, research and workplace training relationship groups
One would have to pass the test and on success become part of one of these corporate groups for
sure to find a place in company for longer period of employment in any workplace.
6. Organization fit
Organization fit is also highly important attribute for proper mapping of talent to right groups.
Corporate growth or for that purpose, talent growth would hugely suffer if development of resources in
any of the needed corporate groups is not proper. It would not only affect company and career selection
“variables” of job seekers but also free market nature of job placements. These types of imbalances in
17. any organization would also affect internal and external outlook along with culture and makeup of the
company. Here are some parameters which would be very visible to people making jobs and careers
sections first time or mid-career:
1. Salary distance in the company eg. Mgmt L3 vs. Support L1 financials: Total life style and
living standards variability in the corporate or company setup i.e. someone who is Mgmt level 3
person and someone who has just joined company as support level 1 employee. Test for this
distance’s testing would be
a) Could they even become part of same type of neighborhood and by the way just forget about
same company. This is just based of salary differences.
b) Other human dignity level parameters would be secondary parameters in such comparison.
“Generative” human life differences created by social, financial and life standards differences
can only be laughed at and derided if they distance is too big.
2. Career choice distance in company eg. Mgmt L1 vs. Support L3 choice: Career selection would
also suffer. Some jobs would not only need deeper understanding of needed subject matter but
also global and social variables understanding. A person who is not a fully developed and
educated outperformer person would not be a good fit for global management type of roles in
most cases. On the other hand very good benefits for support type of work would affect initial
career selection choices of individuals giving rise to career choice option “imbalance”. You
wouldn’t have right management talent and your support talent is from a pool that has already
made compromises on education and work performance efficiencies just for probably “money”
and is probably over-fit for position resulting into problems like sandbagging, absence at work
place (un-interesting work but pays) and unnecessary anger.
And on top of it other management colleagues are not adequately prepared for managing
problem resources. Career switching world be visible and so would be clashes between parts of
corporate. Problems such as “Mgmt ladder not better qualified over R&D ladder” and support
ladders “in-charge of everyone’s life” with operation ladder usually absent and nowhere to be
seen would result. Proper company work levels laddering and qualified management development
programs would not happen or work and inadequate and less qualified operations and support
people with very generalist experience wouldn’t leave for any other similar opportunities making
room for better hiring. Both distances are shown below in the diagram:
“Corp knowledge ladders” and “ranks ladders” connectivity amongst different orgs
18. There are multiple factors of association which would attract someone to an organization and
vice-versa i.e. personal attributes of a personal would push him or attach him to certain specific
groups in an organization. Some of these attribute parameters are very simple such as regional or
locality match, language affinity, schooling, sexuality, hobbies and interests. But some of the other
factors are way too complex factors of association such as special interest groups, career or job match
groups, associations on daily activity and discipline level, outside of work associations, eating habits,
sports interest, interests in social organizations etc.
Underneath hidden drivers for interests in a company could be many. For example learning
capability and daily activity level of a person is highly associated with person’s age group. Young
people usually are very good learners and would choose very structured ways of learning.
Usually they have very active life style and better prepared for busy routine and stress. Preference
for efforts with such requirements would be more in this ground while people who are in little older
age group by body and personality development would prefer stress-less work and easy learning
choices. Genetics would also dictate person’s behavior:
For example age groups and learning attitude genetic tuning based on person whole life expectations:
A person who is genetically from let’s say a lower life expectancy group would usually age faster and
would show signs of older age much earlier in life. Choice set around following life activities would also
be such
Active life style
Attitude towards obstacles and problems
Mindset for education and learning
Social connectivity needs
19. On the other hand person who is from a higher life expectancy group would usually age slower than
peers and would stay active, would have better learning ability and would be ready for stressful work
even in middle part of life. Some of such events would be
open for relocations,
ready for travel and longer hours per day
“diverse” type of job requirements.
7. Personal development tracks
Career planning involves doing things with deeper analysis and data driven decision making whether
it is at the start of someone’s career or it is something a person plans mid career. It is also an important
step in setting up personal development goals along with other necessary life goals. Different type of
folks would do things differently based on factors of differentiated development in their life as everyone
knows that diversity is almost essential for uniform growth of humanity and it creates vibrancy and colors
added different “faces” of folks in social life.
Some folks are “macro” decision makers and some are “micro” decision makers. And many people
depend on someone else for their effective decision making. That is why we have so many career choices
and so many types of job performers.
Along with career choices, career growth planning differs as well among people. Line focus is the
only choice for some employees while multi-dimensional growth “even if it is horizontal” is almost an
“OK” and good enough choice for others. Vertical growth at the cost of limiting knowledge and
compromising with ethical and moral code is not even a choice for many even if rewards are handsome.
This creates imbalances in career growth for people.
Comparison between two career choice scenarios and their effect on personal development is outlined
below and is also shown in diagram that follows the scenario comparison.
Scenario 1:
Candidate with only one focused area through 4 levels of growth and only focusing on vertical
management ladder growth track, essentially transferring few years of work as simple and straight
forward tasks and 1 field “jobs” to levels below thereby adding more and more simple easy to replicate
jobs for lower skill job groups. Some of the important characteristics for such jobs would be:
1) Number of active words in vocabulary: Up to 1500
2) Number of easily accessible information elements: Up to 150,000
Scenario 2:
Candidate with preference for diverse horizontal growth over vertical growth for same period while
ignoring people management opportunities and adding adjacent skills (up to 6 in example case) with each
new such pass thereby creating a job profile that is not very easy to replicate and but is essentially a
20. higher skill hard to replicate new “job” type for future learners to ponder and work on. Mentionable
characteristics for this type of job creator would be:
1) Number of active words in vocabulary: Up to 6000
2) Number of easily accessible information elements: Up to 600,000
Two circles in above diagram show all-round growth as shaded area on the wheel. Covered area
on wheel shows achieved personal growth and essentially control realm of decision making for any type
of simple, multi-dimensional & multi-disciplinary work. It is very clear from these simple circles that
decision making for someone who has focus on growth in just one area would be limited to that area only.
Hence skill set would mostly be only suitable for “line” work type of jobs. While a person who has
focused on all-round growth would be a better decision maker for “whole” decisions involving multiple
organizations and work teams using tools from multiple fields of study.