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Showing posts with the label Information Systems

Describing the Web 2.0 design patterns developed by O’Reilly and Dougherty (2005) and give examples of each.

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 Article in response to:  https://www.oreilly.com/pub/a/web2/archive/what-is-web-20.html What is Web 1.0 and are its characteristics?  This was everything that could be found on the web before the .com bubble of the year 2000/2001. Websites tended to be very static and just displayed text. There was little to no gathering of data and pages did not encourage participation from visitors to comment or add to the conversation. Websites were effectively, “you get what you see” and not a lot more. There were no inbuilt applications like messaging to be found. People also could not tag content and again change the internet environment.    What is Web 2.0 and are its characteristics?    -          large number of very diverse technologies fall under the Web 2.0 umbrella even though they lack any common characteristics   -          Difference between Web 1.0 and Web 2.0 refers ...

Outlining the challenges of managing big data

Introduction As the question and paper from the above-mentioned writers, suggests above, big data and the ability to analyse it is, and will continue to have a huge impact on how businesses work and evolve in the future. Big data is changing not juts computer savvy companies like Google and Facebook but companies from different industries. This answer will first define what big data is and it will then discuss how this is impacting businesses of all kinds.     Big Data Intro There are many different definitions of what big data is. As the name suggests it is when a lot of data needs to be processed but there is no exact cut of point when data as we have known in the past enters the world of “big data” that we have had in recent years. The general consensuses is that we ca consider a dataset to be “big data” when the dataset to too large to be managed by people or basic databases like Microsoft access. The data is impossible too big represent with a few simple graphs....

An enquiry in the ethical challenges facing data-driven firms

  Intro There is an increasing dilemma when it comes how data is collected. It is easy to see why when many writers have said that we have created more data in the last two years that we have in all of human history. The old saying is that knowledge equals power and with great power comes great responsibility. Teachnology in itself is becoming less of a competitive advantage as the latest tech is so assessable. This means the way the way to gain an advantage is with the use of data and becoming “data driven” Data is king and organisations are finding new ways of getting it, often in ways that people are not aware off. One does not need to go far to find someone who is convinced that their device is listening to their conversations for example.    How has this data collection happened? Data has gotton out of control for many reasons but one big reason is that people had and still don’t understand how their data is collected. Many companies offer people terms and conditions...

An evaluation of the utility of the Data Value Map (Nagle and Sammon, 2017) as a framework for developing a shared understanding on data initiatives.

  Introduction First of all, for context, it is vital to start this answer it is important to quickly describe what the six boxes in the above framework are. The four main drivers of this framework are people, processes technology and most recently data. While the main steps to managing data successfully according to the model are as followed. The paper written by the authors states that the framework should be used as a medium for conversation about data using the question words of why, who, when, where, what and how. It is these discussions under the six primary headings or building blocks of the framework that help create a shared understanding of data initives.    6 Pillars Business Value  refers to what activities the organisation could do to better manage its data. Also, what it could start and stop doing to achieve the same goal.  Data behaviours/Governance:  What data needs to be anticipated by a firm about their data and how does the data need to b...

A discussion of the inherent issues in managing concurrent accesses to a transactional database and the type of mechanisms which a RDBMS might use in defence of data integrity and to resolve potential deadlocks.

General Info Concurrent access is something that all databases and dbas need to deal with daily. This is the case for internal databases but also the case for bases that deal with external users like the booking system mentioned in the question. Maintain data integrity is the primary goal of a database is slightly out of date, data is better than inaccurate data.    Concurrent access is when two transactions are trying to accrue at the same time on a database. For example, two people booking the same year or downloading the same file at the same time.    Mechanism 1 The first mechanism an RDBMS (relational database management system)  is the locking of the database. This can mean both users are locked out of the system but often it is the second user trying to access that gets locked out. This is most likely to happen when someone is trying to buy a unique product.    The most common examples of this are the buying of a ticket for public transport...