Week 5 Summaries:
Why is it so
important for tourism businesses to integrate data in the ATDW?
The ADTW is Australia’s
national Tourism Marketing platform, supporting the industry through the
provision of a centralised storage and distribution network. It was originally designed to help the smaller
businesses take part in the digital platform to attract online presence.
The database helps
travel agencies promote the destination in their State or Territory. This supports the economy with international
revenue, world travellers find it easy to book and travel.
The ADTW expands
and grows continually and has now developed a training and education platform
for tourism – e-Kit. They also partner
with other third-party suppliers, such as Eventfinda – which provides another
database for consumers to use.
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| FAVOURITE TOURIST ATTRACTION IN MACKAY |
What are some
potential disadvantages of consolidating tourism data into one data warehouse?
The most obvious
one is that the speed of the database is limited by the network speed and can
become unresponsive. It can become
unresponsive in the worst of times. There
is also the risk of a crash and loosing the information if backups are not done
on a regular basis. Even though
cloud-backup may be in place, there is a possibility of complete loss.
There is also the
potential of information hacking. It has
been in the news regularly lately – e.g personal information stolen form Medibank,
and a bank Heist in Bangladesh in 2016 (
Is big data really a problem on its own, or are the use, control,
and security of the data the true problem? Provide specific examples to support
your answer. Refer to the following link for further information to add to your
response (i.e. volume, velocity and variety of big data): https://www.zdnet.com/article/volume-velocity-and-variety-understanding-the-three-vs-of-big-data/
Digital
information is measures in bits and bytes.
To understand Big Data, we need to know what the smallest part is – that
is a “bit” the binary digit that is either 0 or 1. Eight bits would make up a “byte”. A byte would store the information to produce
one letter of the alphabet. A Kilobyte
is 1024 bytes!
Where does that data go? Where does my information go? Customer
information, transactions, all the metrics generated in planning. Social communications? We need this data to analyze, and track make
recommendations to add value to all the information. What is the problem?
Volume – insane amount of information e.g., the number of
images stored in FB.
Velocity – how fast the data is entering the platform. Looking again at how fast people are posting
photos on FB or Twitter
Variety – i.e.- e-mails, photos, spreadsheets, audio, attachments
etc.
Big Data needs to be stored and managed. There are 2 types of database structures for
storage – single-file (flat file) or multi-file (structured) databases. A Flat-file
database stores data in plain text, a very simple data base. There are 4 different types of multi-file or
relational databases. The latest trend
is the noSQL database (MongoDB and Cassandra)
Each of these databases has their own Pros and Cons. The needs and requirements of the company
will determine the type of database they will engage. For most people, security is at the
forefront. Confidentiality of
information is an element that is easily breached. Another problem that is common is human error
– Information out is just as good as information in. also of course malware, malicious insider
attacks, Hackers etc. are all common problems for Big Data bases.
What are
the implications of having incorrect data points in your big data? What are the
implications of incorrect or duplicated customer information? How valuable are
decisions that were made based on faulty information derived from incorrect
data?
Implications for incorrect data is uncontentious – the information
retrieved will be invalid and of no use.
Data can be outdated, duplicated,
Missing, inaccurate data
Decision cannot be
made on that information, as it will be wrong. This will cripple your business
strategy, damage reputation etc. we ony
have to look at an example health care – making wrong entries regarding patient
information which could be fatal. Or even
law enforcement – booking the wrong person.
Or deciding on a business proposition based on the wrong information.
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| BIG DATA |
ADTW. (n.d.). ADTW Online. Retrieved March 19,
2023, from Australian Tourism Data Warehouse:
https://atdw.com.au/2018/10/25/atdw-eventfinda-partnership-leads-greater-exposure-events-australia-2/
Axel. (2018, October 30). Major Centralized Systems
are Hacked Multiple Times a Year. Retrieved from Medium,com:
https://medium.com/@AxelUnlimited/major-centralized-systems-are-hacked-multiple-times-a-year-9c2ad612462b
Fatima, N. (2019, June 11). A Quick Overview of
Different Types of Databases. Retrieved from Astera :
https://www.astera.com/type/blog/a-quick-overview-of-different-types-of-databases/
Gewirtz, D. (2018, March 21). Volume, velocity, and
variety: Understanding the three V's of big data. Retrieved from ZDNet:
https://www.zdnet.com/article/volume-velocity-and-variety-understanding-the-three-vs-of-big-data/
The pictures illustration is spot on
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