Notes for Fundamentals of IT .pdf

Keywords: Span of control: Number of employees that the manager has control over Chain of Command: The route at which information and organisation instructions passes through the business from the top to the bottom. It shows who answers to who. Subordinates: Members of staff that work under a manage...

Keywords: Span of control: Number of employees that the manager has control over Chain of Command: The route at which information and organisation instructions passes through the business from the top to the bottom. It shows who answers to who. Subordinates: Members of staff that work under a manager. And are below them in the chain of command. Hierarchy structure. Commonly used for larger businesses. This is because it has a long chain of command with many layers of communication. And a narrow span of control because there are many managers with a small number of subordinates. The greater up you are, the more responsibility you have. ADV. Motivation VIA promotion. With many manager positions there is a higher chance of promotion Clear accountability (you can see who is in charge of who) DIS Slower communication through layers of the business. Where a manager may misinterpret something and the message gets lost down the chain of command. Higher cost to run the business. Flat Structure Fewer layer of managers with a wide span of control and short chain of command. Managers main have more subordinates ADV Faster communication between positions No need to follow lengthy approval processes. Engagement. Employees are more involved with day to day decisions with less interference from more managers. Employees have more authority. Can save the organisation money DIS Little to no progression/promotion Reduced motivation Matrix Structure Has traditional departments such as product, finance, promotional managers. They create project teams across the functions of the business to work on a task or project. Project team gets formed from across departments with different skills to finish a task. ADV Utilises many skills from the org Effective communication. Information flows freely Strong team spirit and improved morale. DIS Split across two managers, normal and project manager which can conflict ideas and try to push other ideas to their subordinates. Takes time to get together as a tea How does IT affect a business? Cloud computing: Cloud computing utilises IT to capitalise on its ability to provide improved agility and time and resource management for business. It is a cost effective solution for smaller businesses Is growing with immense popularity needs a good connection Automation: Automation of business processes improves efficiency and increases workflow. IT is essential in developing automated process for business reduce cost of operation and save time Working Remotely: Implementation of IT provides the ability to remotely access a company's network. It equips employees with the ability to get the work done even if they are not physically present in the workspace. Since Feb 2020 we have pretty much all had the experience of working or studying from home. Mobile Technology: This has been a key growth area over the past decade. Implementation of mobile technology has gained a lot of ground quickly. The trend of BYOD has been on the rise. Protecting information: Every organisation has a mammoth database comprising various information related to business transactions, client details and so on. Whilst such information is extremely valuable to a business and can cause a host of legal issues if it's lost. It provides the right resources to store info that provides max protection. Providing customer satisfaction: Customer experience and satisfaction are crucial aspects of all businesses. It provides the best tools for communicating with customers and solving their problems. Management of resources: A business has a variety of resources and larger organisations have found difficulty in managing resources. IT plays a vital role in managing these resources effortlessly by introducing a wide range of feasible solutions. Example, ERP has improved efficiency of various business processes Open source software: IT has paved the way for various open source software that allow free usage of certain tools for various organisations. The primary benefit of open source software is its flexible licence which allows modification to the source code, to customise the software functions according to the company’s requirements. The main role of IT in a business is to: Improve productivity Increase Performance Save Money Improve customer Experience Streamline communications Enhance Managerial decision making What is the software development life cycle? TheSDLS is the application of standard business practices to building software applications. It is typically divided into 6 to 8 steps Planing Requirements Design Build Document Deploy The SDLC is a way to measure and improve the development process It allows a fine grain analysis of each step of the process The SDLC is a framework defining tasks performed at each step of the sdlc The life cycle defines a methodology for improving the quality of software and development process.\ The SDLC outlines each task required to put together a software application It helps reduce waste and increase the efficiency of the development process. Seven Stages of the SDLC 1.Planning: In the planning phase, project leaders evaluate the terms of the project. Calculate labour, materials, timetables and goals. Planning can also include feedback from stakeholders. It is recommended to get feedback from customers. 2.Planning/Analysis: Planning should clearly define the scope and purpose of the application. It plots the course and provisions the team to effectively create the software. It helps set boundaries 3.Define Requirements: Defining the requirements is simply figuring out what the application is supposed to do. A social media application would require the ability to connect with a friend. An inventory programme might require a search feature. Requirements also include defining the resources needed to build a project. A Team might develop software to control a custom manufacturing. 4.Design/Prototype: The design phase models how the software will look Architecture: Specifies programming language, industry practices, overall design User interface: Defines the way the customers will interact with the software and how the software responds the input Programming: In addition to coding, including methods of problem solving. Communications: Defines the methods that the application communicates with other assets. Platforms: Defines the platforms on which the software will run. (apple, windows) Security: Defines the methods take to secure the application(SSL, Password) A prototype is like one of the early versions of software in the iterative software development model. It demonstrates a basic idea of how the application looks and works. This hands-on design can be shown to stakeholders. Feedback can be used to improve the application. It is less expensive to change the prototype phase than to rewrite the code to make a change in the development stage. 5.Software development: This is the actual writing of the programme. A small project might be written by a single developer. A larger project might be broken up and worked on by several teams. In a larger project, software control software is required to be used. These systems help developers to track changes to code. Also ensure compatibility between different teams. Software developers also appreciate well written technical specifications. 6.Testing: Testing is a very critical part of the software development life cycle. Much of the testing can be automated like security. Other testing can be done in a specific environment( eg creating a simulated environment for complex deployments. Testing should ensure each function works correctly. Different components of the software can be tested individually but the software application must be tested, as a whole, several times to ensure that all the components work seamlessly together. Testing phase helps to reduce the number of bugs and glitches. 7.Deployments: In the deployment phase, the application is made available to users. Many companies prefer to automate the deployment phase (eg simple as payment and download link on the company website or testing the application on a smartphone. Deployment can also be complex (e.g upgrading a company wide database to a newly developed application. Typically, multiple systems can be used by the database therefore integrating the upgrade can take a long time. 8.Operations/Maintenance At this point development is almost complete. The application is done and being used in the field. The operation and maintenance phase can discover bugs that were not found during testing. Dech errors need to be resolved which can spawn new development cycles Models like iterative development plan additional features in future releases. For each new release a new development cycle is launched Waterfall The waterfall SDLC is the classic method of development. Each phase completes, the project spills over into the next step. This is a tried and tested model. One ADV of the waterfall model is that it can be evaluated for continuity and feasibility before moving on. Its limited speed however since phase one must finish before another can begin. Agile The agile method was designed by developers to put customers' needs first. This method focuses strongly on user experience and input. This solves much of the problems of older applications that were arcane and cumbersome to use. Agile seeks to release software cycles quickly making it highly responsive to end user feedback and able to respond to a changing market. This require a strong team with excellent communication Iterative In the iterative development mode;, developers create an initial basic version of the software quickly. The application is reviewed and improved on in small steps. This approach is mostly used in very large organisations. It can get an application up and functioning quickly to meet a business need. A negative to this process is that it can exceed its scope quickly and risks unplanned resources. Devops The DevOps security model incorporates operations- the people who use the software into the development cycle. Like agie tis seeks to improve the usability and relevance of the applications. One significant advantage of this model is the feedback from actual software users on the design and implementation seps. One drawback is that it requires active collaboration and communications. Those additional costs can be offset by automating the development process. Rapid Application Development. RAD was the buzzword of the 90s. In the 90s it was a relatively new approach that promised the seamless and gas product of new applications to meet ever growing development requirements of copaninges from various industries. In the 70s and 80s the waterfall model was the prevalent approach to software development. A rigid approach like the waterfall model is intuitive when it comes to engineering fields such as constudeciom but it is insufficient when it comes to software development in a fast paced environment. A project driven by RAD models is more adaptable and flexible and can easily incorporate any feedback received into further development. Since software changes are based on the end user the resulting product is more likely to be appreciated by the end users and be user friendly. ADV Due to its flexibility and adaptability to new inputs a RAD approach carries far less risk than a basic plan based method. A RAD approach allows user to tweak and adapt the prototype it address any feedback DIS Increases the reusability of components and highly specialised and skilled developers are required. Reason: The client may create an unrealistic product vision leading a team to over or under develop functionality specialised and skilled developers are not readily available. Change Management: It is a systematic approach towards dealing with a charge. It involved coordinating resources, applying tools and managing knowledge in order to effectively drive organisational success. Kurt Lewin Social psychologist whose extreme work covered Studies on leadership and their effects Work on group decision making The development of force field theory The unfreeze change refreeze change management model Group dynamics approach to training especially in the form of T groups Kurt Lewin's change management model is linked to force field theory. He considered that to achieve change effectively it is necessary to look at all the options from the existing present to a desired future state. The nevaluate the possibilities of each and decide on the best one rather than aiming for the desired goal Let's say you have a large cube of ice but realise that you want a cone of ice What do you do Melt the ice Mould the ice Solidify ice By looking at change as a process with a distinct stage it is simpler for one to prepare oneself for what is coming and make a plan to transition. For a successful change to take place Lewin said that motivation for change must be generated before any change occurs. This is the unfreezing stage. Allow time for people to embrace the new direction and participate proactively n the change Understand how the change will benefit then. If people can see that there is a benefit for them, the change becomes acceptable. Types of changes in an organisation. There are many types of change in organisations. The first is structural changes in the overall formal relationships within an organisation example: Organising departments or business units. Adding employee positions Revising job roles and assignments These changes should be made to support broader objectives such as to centralised/decentralised operations, empower employees or find greater efficiencies. The second is TECHNOLOGICAL change This has to do with implementation of new technologies, often forced upon an organisation as the environment shifts. Example: An industry upgrade in a commonly used software platform may require employees to learn new ways of working. Upgraded machinery/hardware may require employees to learn new procedures or restructure the way they interact with another Technological change often induces structural change because it requires different ways of connecting across an organisational system. The third is CULTURAL CHANGE Organisational culture refers to the common patterns of thinking and behaving within an organisation. Culture is rooted in the underlying beliefs and assumptions that people hold of themselves and the organisation. These Beliefs and assumptions create mindsets that shape the culture. Culture change is among the most difficult changes to create within an organisational system. A typical culture change process, if it is successful, requires many years to achieve.. When supermarkets installed scanners to read the product price, this was an example of technology change. Ana individual is likely to resist change because of Uncertainty Concern over personal loss Belief that change is not the organisations best interest An individual is likely to accept change if; There is increased productivity Some benefits Data Ethics: Data Ethics ecompasses the moral obligations of gathering, protecting and using personally identifiable information and how it affects individuals. Data ethic asks, Is it the right thing to do? Can we do better? 5 Principles. IN THE TEST 1.Ownership: The first principle is that an individual has ownership over their personal information YOu cannot take an item that does not belong to you Likewise its against the law and and ethical to collect someone's data without their consent You may have noticed checkboxes on websites asking you to allow cookies, checking the box ispermitting the website to track a users behaviour online 2.Transparency In addition to owning their own personal information, data subjects have a right to know how you plan to collect and store their data. When gathering data, you must exercise transparency Example A website might be tracking a user's buying habits. There must be a website policy explaining how the cookies are used and that the data will be stored in a secure database. 3.Privacy Another ethical responsibility that comes with handling data is ensuring the data subjects privacy Even if an individual gives a business consent to collect, store and analyse their personally identifiable information, That does not mean that they want it to be available to the public area Examples of PII include Full name Birth date Contact details IRD Credit card Passport number To protect an individual's privacy Ensure that the data is stored in a secure database Ensure that data security methods are in place 2fa De identifying a dataset leaving only anonymous data Analysts can still find relationships between items of interest e.g number of people in a store between a particular time period to glean most popular shopping times. 4. Intention Before a company begins collecting data, the following questions need to be answered Why is the data needed? What benefits will come from collected data What changes occurs as a result of analysis If the intention is to hurt others, profit from the subjects weaknesses, or any other malicious intent, then it is not ethical to collect their data 5. Outcomes Even if intentions are well meaning, the outcome of data analysis can inadvertently cause harm to individuals or groups of people This is known as disparate impact Harvard prof Latanya Sweened decided to do her own search of her name Her name appeared in an advertisement “Latanya sweened, arrested?” She had never been arrested but decided to do some research. She found that if your name was given more often to a baby of a particular race/ colour, your name was 80% more likely to appear in an ad saying you have been arrested Its not clear from this example whether the disparate impact was intentional or a result of unintentional bias in an algorithm Either way it has real potential to do real damage that disproportionately impacts a specific group of people. By considering the possibility of disparate impact before carrying out data analysis, give the opportunity to catch any potential occurrences of disparate impact. If your role includes writing, training or handling machine learning algorithms, then you must consider how they could potentially violate any of the five key data ethics principles. Algorithms are written by humans, therefore bias may be intentional or unintentional Biassed algorithms can cause serious harm to people Maori Authority Maori heaven inhere right to exercise control over maori data andmaori data ecosystems The right includes, but is not limited to, the creation, collection, access, analysis, interpretation, management, security, dissemination, use and reuse maori data Jurisdiction Decisions about the physical and virtual storage of Maori data shann enhance control for current and future generations -> Where possible, maori data shall be stored in NZ Self determination Maori have the right to data that is relevant and empowers sustainable self determination and effective self governance Relationships All data has a genealogy All accurate memta data should provide info about provenance of the data, the purpose for its collection the context of the collection and the parties involved Data Disaggregation The ability to disaggregate maori data increases its relevance for maori communities and iwi Maori data shall be collected and coded using categories that prioritise maori needs Obligations Individuals rights risks and benefits in relation to data need to be balanced with those groups they are a part In some contexts, collective Maori rights will prevail over those individuals Accountabilities Individuals and organisations responsible for the creation, collection, analysis, management , access, security, or dissemination of maori data are accountable to the communities, groups and individuals from whom the data was derived. Collective benefit Data ecosystems shall be designed and function in ways that enable Maori to desire individual and collective benefit Maori data sovereignty requires the development of a Maori workforce to enable the creation, collection, management, security, governance and application of data.\ Connections between Maori and other indigenous people shall be supported to enable the sharing of strategies, resources and ideas in relation to data Reciprocity The collection use and interpretation of data shall uphold the dignity of Maori communities , groups and individuals Data Analysis that stigmatises or blames Maori can result in collective and individual harm and should be actively avoided Free, prior and informed consent shall underpin the collections and use of all data from or about maori Guardianship Maori data shall be stored and transferred in such a way that it enables and reinforces the capacity of Maori to exercise Kaitiakitanga over Maori data Tikanga, kawa and matauranga shall underpin protection, access and use of maori data Maori shall decide which maori ata shall be controlled or open access. BiasCreep Training Machine learning algorithms learn based on the data they have been trained with An unrepresentative dataset can cause your algorithm to favour some outcomes over others Code: Although any bias present in the algorithm is hopefully unintentional, don't rule out the possibility that it was written specifically to produce biassed results Algorithms can also learn from users feedback A job search platform may use an algorithm to rec roles to candidates Using data for good Whilst the ethical use of data is an everyday effort, knowing that your data subjects safety and rights are intact is worth the work. When handled ethically Data can enable you to make decisions Drive meaningful change in your organisation and in the world CRITICAL THINKING People's normal mode of thinking is bound within the parameters of certain rules and systems. This is due to the thousands of years of evolution. In the jargon of psychology, human thinking uses certain heuristics (mental shortcuts) There are few problems though Automatic and well established ways of thinking can stop you from seeing new possibilities The great majority of people thinking gos out the window without them being aware of it. Although quick and efficient it can result in wrong conclusions Evaluating what you Read Hear and Think Critical thinkers: Actively question assumption Approach and issues without preconceived assumptions Quick to prepared to to acknowledge a good argument Will refuse to resort to a bad argument The attributes of critical thinkers are Tolerance Analytical Skills Confidence Truth seeking Curiosity Three kinds of thinkers Sticklers: People who form their beliefs by tenaciously sticking to whichever view they liked the most originally Ig asked to justify their view, they can be very thorough in finding facts to support it but refuse to look into anything that appears likely to run against it Followers: People who respect anyone or anything that represents itself as authoritative They form their view in a group[ discussion on what they think Wikipedia offers security give that there is a reluctance to consult websites run by individuals System builders: People who do their best to fit everything into a pre existing framework They are a more sophisticated version of sticklers Systemisers are willing to consider new info but if it requires dismantling the pre existing structure then they are likely to reject it. Investigating, inventiveness and imagination Creative insight is linked to the imagination and to peoples in build to make connections between two different things Think Like a Computer Programmers have to be very clear in their own minds and communicate their message without ambiguity. Computers cannot guess what a programmer was meant to say. Software designers have to figure out exactly what the problem is before they can work out how to program a computer to do it. Another principle of computer science is modularity. Instead of having a great long text with everything in it, a programme is made up of blocks which can be reused. Taking tips on clarity from programmers A computer has to first of all learn how to express themselves clearly. Computers just follow instructions. The most dangerous step that a computer can take is one that starts with a circle. When a computer stops working in the middle of an operation, it is usually because the programme has followed a circular sequence of instructions that have no ending An algorithm is simply a sequence of steps taken to solve a problem It's a methodical strategy for solving problems in a systematic manner This type of approach is integral to critical thinking, particularly creative writing. If you were writing an instruction manual, then the sequence of steps is crucial if your reader is going to understand them. Semantics VS Syntax To express yourself clearly like a computer and effectively in writing on speech Try being more like a computer and less like shakespeare Construct your sentences so that the meaning is unambiguous Listeners should be able to easily follow your line of reasoning Do not leave your readers imagining Computers don't mind trying lots of options mainly because the ca do so quickly Semantics Covers questions about the meaning of words or phrases Syntax Putting words and phrases together correctly It considers their positions and relations to each other Trainee programmers often get that awful message SYNTAX ERROR - but computers never ever return a semantic error- programming language is converted to 1’s and 0 S so anything inside quotes is ignored by the programmes compiler THINK LIKE A COMPUTER Thinking like a computer is a more effective way for problem solving The best way to solve problems is to Have a framework Practising it Almost all employers prioritise problem solving skills The steps to take when encountering a new problem 1. Understand Know exactly what is being asked Most hard problems are hard because you don't understand them How do you know when you understand a problem? When you can explain it in plain english 2. plan Don't dive straight into solving without a plan Nothing can help you if you don't write down the exact steps Give your brain time to analyse the problem and process the info 3. Divide Do not try to solve one big problem Break it down into smaller subproblems because the are easier to solve Begin with the simplest sub problem Then continue until all sub problems are complete Connect the dots to find the solution to the original problem. 4. Stuck The difference between the best problem solvers and the bad ones is that the best ones are more curious about bugs and errors rather than irritated. Debug. Go step by step through your solution Reassess. Take a step back and take a look at the problem from another perspective. It is amazing what a fresh set of eyes see Research: No matter what problem you have, someone else has probably already solved it, or you can learn from another solution 5. Practice If you want to be a good problem solver, you have to solve a lot of problems, practice with puzzles or maths or sudoku. Neuroscientists have proven that your brain cannot find solutions if you focus on the problem. This is because focusing on the problem feeds negativity which in turn activates negative emotions in the brain. These emotions block potential solutions, This doesn't mean ignoring the problem. Move your focus to a solution orientated to what the answer could be. The 5 Whys Repeatedly ask yourself Why? Try to list out all possible solutions even if they sound ridiculous at first, It is important to keep an open mind. It's often the crazy ideas that trigger more viable solutions Change the direction of your thoughts by thinking laterally. Try to change your approach and look at things in a new way. Even if it feels dumb, A fresh and unique approach usually stimulates a fresh solution Lead your thinking with phrases like “What if” and “Imagine if” These terms open up our brains to think creatively and encourage solution Avoid negative language such as “I dont think” or “But this is not right” Problems to not need to be scary A problem is really an opportunity for improvement If you think about what a problem is, it's really just feedback on your current situation. Practice Defining a problem, keep calm and don't make things to challenging What is a data model? Data modelling is the process of creating a data model for the data be stored in a database The Data model is conceptual representation of data objects, the associations between the data objects and the rules. Data modelling helps in the visual representation of data Why do we use a data model? The primary goal of using a data model are: Ensures that all data objects required by the database are accurately represented Omission of data will lead to the creation of faulty reports and produce incorrect results A data model helps design the database at conceptual,physical and logical levels Although The initial creation of the data model is labour and time consuming, in the long run it speeds everything Types of Data Models In DBMS There are three Conceptual Logical Physica Eachon Has a specific purpose,the data models are used to represent the data Conceptua Defines WHAT the system contains Typically Created by the business stakeholders and system architects Purposes to organise scoreland define business concepts and rules Physical Defines HOW the system should be implemented using a specific DMNS system Propose is the actual implementation Typically created by the DBA and database developers Logical Defines how the system should be implemented Purpose to provide a technical map of the rules and data structures Typically created by the Data Architects and the system analysys