Annabelle McCulloch

 There are many ways in which big data applications affect people especially businesses everyday such as: Transportation - Big data powers things such as GPS on smartphones which helps people get from one location to the next in the easiest and quickest way possible, the GPS data is also for images and government agencies. Additionally airplanes generate data for long flights such as seeing the weather and also figuring out how much fuel is needed to get from point a to b while saving energy and being as safe as possible. Additionally traffic control, managing and sorting congestion, traffic safety and lastly route planning to save fuel, money and time.  Advertising and marketing - this also links to media and entertainment where they create ads that focus towards people and their own interests such as if someone’s trying to watch a movie on Netflix for example and they are known to enjoy action movies then the data will give them more action movies to watch rather than just r...

 It’s often described using five main characteristics these being: Volume, value, variety, velocity and lastly veracity.  Volume being the size of the data that is needed to be analysed, value is from the eye of the business which leads to better operations, decisions, customer satisfaction and also being able to see what the business needs to make it succeed, variety which is the range of the data types, velocity is the rate at which companies get, store and manage their data such as on social media if someone asks a question how long it takes for the company to reply to this, and finally veracity which shows the actual accuracy behind the data and the information.   https://www.teradata.com/glossary/what-are-the-5-v-s-of-big-data#:~:text=Big%20data%20is%20a%20collection,variety%2C%20velocity%2C%20and%20veracity.

 Some limitations of traditional data analysis are: Lack of data sources meaning that it relies solely on very particularly organised data such as ones through surveys, interviews, questionnaires or really any other form of data collection. Because of this it’s limited to give a complete picture of what the business world it truly like.  Limited scope means that it’s most often limited in information and provides insight to a specific part of the business world. For example, a survey about customer experience at a business may say that the employee was rude or unkind but it doesn’t give an insight about how the customer may have behaved to receive this kind of treatment.  Another part is that it’s time consuming to complete because if this it means the business can’t make decisions fast or efficiently. An example would be that if a survey or questionnaire took a long time to be taken and additionally to be sorted and analysed which can take weeks if not months to be finis...

 The traditional statistics of big data mainly revolves around structured data. It involves around statistical techniques which is things such as surveys, interviews, experiment data etc and visualisation's. But it also may include machine learning, data storage and additional techniques. Using a range of data sources such as social media, lot devices or sensors which is used for big data analytics.  https://www.geeksforgeeks.org/difference-between-traditional-data-and-big-data/#:~:text=Traditional%20data%20analysis%20methods%20typically,be%20stored%20and%20managed%20effectively. https://www.linkedin.com/pulse/whats-difference-between-big-data-analytics-traditional-statistical-ojodc#:~:text=Traditional%20statistical%20analysis%20primarily%20deals,surveys%2C%20experimental%20data%2C%20etc.

The value of Data allows to gather and process data in real time which helps to analyse them to adapt rapidly to gain a competitive advantage. This helps to guide businesses for example with getting ready to plan, produce and launch new products, features and updates.  https://cloud.google.com/learn/what-is-big-data

 Some reasons the the big data growth include the creation of 5G, the growing number of devices such as smart phones, cloud computing and increased use of the internet. Additional reasons for the rapid growth of big data is the cost for data storage, business analytics, security also while using ubiquitous devices such as CCTV, tablets, handheld scanners, GPS, wireless sensors etc.  What's causing the exponential growth of data? The 10 Reasons for the Rise of Big Data - Simplicable

Big data is so large and just keeps on expanding every second. It’s believed that the market size will grow from 220.2 billion dollars (2023) to 401.2 billion dollars (by 2028). which means that it’s expected to grow at a 12.7% rate.  Because of big data’s large and rapid growth it means that AI and analytics will become way more advanced. There’s suspected to be a 28% increase in data science jobs by 2026.  

 Big data dates back to the 60/70s when computers were first introduced for data processing. However, in the 90s the term big data was used to describe the growing value of data (volume, variety and velocity)  In the early 2000s, the introduction of the internet and increase of people having devices meant a massive increase in the amount of data being generated and collected, in turn created new tools and technologies to collect and analyse the data. In 2004, google introduced MapReduce which allowed large scale data processing on distributed systems using commodity hardware. This tech became the starting point for Hadoop which is an open source platforms for data storage and processing which released in 2006. 

Big data is large and varied collections of data. That cannot be managed by traditional systems. It’s studied to reveal patterns, trends and associations. It was created by Roger Douglas in 2005. The data is so large and complex in its volume, velocity and variety that normal data management/storage systems can’t store, process or analyse due to the mass size of the dataset.