Big Data EC1702991

6. Traditional statistics Traditional Statistics is simply the act of gathering data and searching for trends among it. It is widely used in many different ways in our society. Medical uses could be for vaccines, as doctors can recover results information from different types of vaccine for a disease to insure safety when administering it to large amounts of people Communication companies also use statistics to help identify faults within the network so that they can be fixed faster which in term ensures that customers will be able to regain full functionality in a shorter time Government agencies around the world rely on statistics for a clear understanding of their countries, their businesses and their people.

Big Data and Bitcoins Recently, Bitcoin has seen a recent spike in value, which has prompted many people to begin "mining" for more. This in turn has had a knock on effect with computer parts, sending the price of dedicated graphics cards far more expensive than before. Big data can be used for both of these problems through methods such as google trends. For bitcoin, google trends can be tracked for how often people are giving attention and searching google for bitcoin or similar terms. Big data can also be used for tracking the current value of bitcoin and analyzing any patterns in the price changes to help predict whether the value will rise more or fall.

Week 3 Big and small data Small data is a way of keeping the size of data down. A file such as an image could take a lot of space depending on the size of the image, but by compressing it and losing some of the quality you can massivly reduce ths size. An example of small data could be Meteorological Aviation Report (METAR). The image below shows this off, each section of the code represents a different piece of information and saves entire data entries from being typed out and takes less time to process.  https://www.futurelearn.com/courses/big-data-and-the-environment/3/steps/420387 Citizen Science Is the collection of data about the natural world that has been gathered by the general public, usually as part of a project with other data scientists. This can be used to gain vast amounts of information quickly since many people at once can gather the information as opposed to just one scientist or one sensor. One example is Thames 21, a charity which worked with Cit...

Week 2 Open Data Open data, by definition, is data that is free to use by anyone for any purpose at any time. This includes republishing data and not being affected by Copyrights or Patents by doing so. One proposed example of this is satellite data. By allowing this data to be "open data" we can allow it to be analysed to learn more about how our atmosphere is being affected by greenhouse gasses as well as monitor current changes and prevent new problems from arising.  https://www.futurelearn.com/courses/big-data-and-the-environment/3/steps/420374 Data Scientist A data scientist is someone who's job it is to analyse and interpret data, like usage statistics for a website in order to aid/assist a company or business with making important decisions. IEA data scientist Dr Ben Lloyd-Hughes states that there are 7 phases of a data science project which a data scientist will complete. 1. Problem Statement 2. Data Acquisition 3. Data Preparation 4. Data Ex...

Week 1  Environmental Sources of Big Data The best example of Big Data the is provided by the environment is the weather and the changes within it. Supercomputers are used to create weather simulations in real time to analyse current weather and look for patterns, and furthermore use this data to predict the weather that is still to come. This data includes things such as air pressure, humidity and sea surface temperature.  https://www.futurelearn.com/courses/big-data-and-the-environment/3/steps/420355  Observing Earth from space with Big Data Big data can also help humans observe the planet from space and choose to view select parts of it. Satellites in space can be used to 24/7 monitor the planet and can send back data such as weather or communications data. These can also be used for sending mapping data for earth and cartography data. Google earth is an example of that, where the entire planet is available to be viewed thanks to the data that has b...

11. Big Data in society One application of big data within society is tailoring specific ads or sites etc to the public based on past search results or views. Netflix is a prime example of this. Netflix uses a person's previously watched films and shows and suggests content it thinks would be perfect for that user. for example, if a user watched a nature documentary, Netflix would use this to suggest other nature documentaries to watch. Social media platforms are also an example of Big data being used in society. take Facebook. Every user on Facebook will upload or share countless amount of pictures and videos, all of which can be analysed by companies and can even allow companies to target a user based on things like age or race.  https://www.mentionlytics.com/blog/5-real-world-examples-of-how-brands-are-using-big-data-analytics/

10. Big data in science Big data has recently become an integral part of working in science, with a good understanding of algorithms being an essential trait required of modern day biologists, physicists etc Not long ago, sequencing an entire genome (determining the order of all 3 billion pairs of DNA letters in the helix) took years. The Human Genome Project, the first completed sequence of an entire human genome, took around 13 years from conception to its completion in 2003, and cost more than £2 billion. Today, next-generation sequencing can do the same thing in 24 hours for not much more than a thousand pounds. This has completely changed how scientists work. It's not just that they get their hands dirty less often, nor simply that the required skills have changed. It's that the whole process of science – how you come by an idea and test it – has been upended. This has left a lot of senior scientists needing to understand and supervise techniques that didn...

9. Big Data in Business Big data analytics are used in business any many different situations to aid the company by either saving time, money or both. Fast food chains have began using big data to aid their business in areas such as their drive-through lanes, namely McDonald and Burger King. The restaurants are using big data to monitor the length of the queues and change the menu items appearing accordingly. For example, if the line is really long the menu will suggest items that are easier and faster to prepare. but if the line is short then the menu will adjust to show the fancier more appealing items on the menu. This adaptation hopes to make people choose easier to prepare food at busier times as this is what will be shown to them on the menu. https://www.datapine.com/blog/big-data-examples-in-real-life/

8. Characteristics of Big Data Analysis Volume: This is the amount of data that the company can/will collect. With big data growing larger all the time this is a crucial factor in analytics. Velocity: This is the rate at which the amount of data increases, which is forever getting faster due to our dependence on the internet etc. Variety: Is in reference to the fact that big data comes in many different forms i.e. video, audio, sensor data, etc. understanding of which is crucial when analysing big data Veracity: is making sure that any data that will be analysed comes from a completely legitimate and credible source. failing to do this can have a massive impact on analysis  https://intellipaat.com/tutorial/big-data-and-hadoop-tutorial/introduction-to-big-data/

7. Limitations of traditional data analysis Security: Security is foremost aspect for every technology. Big data is prone to data breaches. The important information that is provided to some third party may get leaked to customers. Proper encryption must be made in order to protect the data.  Large growth in data : data is growing faster than the processing power. Large volumes of data are being exploded in past years. We need some new machines to work; otherwise we will get over run by data. Large Data centres can solve this problem.  Inconsistencies: Sometimes the tools we use to gather big data sets are imprecise. This will happen when the data is collecting for example, consider Google search Edinburgh College results of the search on one day will be different from other day, this is mainly due to inconsistency in data collection.

5. Value of data The Big Data market was worth approximately $125B in 2015, and has likely grown a lot since that time. That’s a measure of how much companies were investing in Big Data, not how much value they were deriving from it. However, it provides a sense of just how much companies are pouring in to data operations.  In 2013, analysts predicted that the "Return on Investment" of investment in Big Data would increase from 50 cents per dollar invested at that time to $3.50 per dollar in three to five years’ time./ Better use of data analytics by marketers can improve "ROI" by around 10-20%. Since companies typically spend roughly $1T total on marketing efforts, that means they can save between $100B and $200B through Big Data.  A 2010 investigation of the Fortune 1000 companies at the time found that the middle-range companies in the group could gain $255M every year through incremental improvements in data effectiveness. http://blog.syncsort.com/2017/03/...