Big Data Is Monitoring You - But It Is For A Good Reason
“Big data is high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.” - Gartner
What is big data?
Though complex in application, big data can be explained simply. Since the information explosion of the late 20th century, industries have been desperate for a method to process large volumes of complicated data from various data sources - this is where big data technology comes in.
Traditional processing methods can’t cope with the mass amount of data produced every single day, so big data is used to organise and analyse important pieces of information efficiently. Such data can be extracted from social media platforms, consumer transactions and GPS tracking. Big data is less about storing data, but deciphering patterns and trends from large volumes of information to benefit business, security and finance.
What is the history of big data?
By 2005, people started to realise that the vast amount of data produced by Facebook, Youtube and various other online platforms, was too much for previous software to process. In response to this need, Hadoop, Spark and NoSQL were released, all of which being open-sourced frameworks specifically designed to effectively analyse big data.
These frameworks were developed to manage the growth of data, making the results of user behaviour easier, cheaper and quicker to analyse. With the creation of IoT (the Internet of Things), which enables devices to send and receive data, the heightened connectivity with the internet has enabled ease of access to data, including customer purchasing patterns and product performance.
What are the everyday uses of big data?
Understanding what big data actually is is one thing, knowing how it is being practically applied to our day to day lives is another. Big data is improving nearly every sector of society, due to its reflective nature on behavioural habits. Though to some being analysed may feel intrusive, big data is actually shaping how seamless business, finance and security weave into our everyday lives.
No one wants to buy a bruised banana or receive a damaged Amazon order, so big data is being used to monitor the condition of goods while they are in transit. Logistic companies have been tracking orders for years, but once they are out on the road, in the skies or sailing across the seas, it can be difficult to directly report on its status. That is where big data comes in.
Losses from damages can be estimated while a product is in transit, due to the real-time traffic and weather data available to delivery companies. Transportation routes can be updated live to mitigate potential risks and maintain the best quality products possible. Ultimately, businesses can deliver high-quality products faster, as they can have control over goods whilst they are being delivered.
Thanks to big data, hospitals can drastically improve the quality of patient care on offer. With a wealth of insightful knowledge on hand for hospitals to evolve their care strategies, resources can be used more effectively to reduce waste. For example, 24/7 monitoring can be implemented in intensive care units, to reduce the need for direct supervision from individual nurses. This reduces the pressure on hospital staff and increases the response time for patients.
The timescale for processing medication can be lengthy, so big data is being used to analyse the past records of patients. This ensures that the medication isn’t just appropriate, but provided quicker than ever. During the actual production of biopharmaceuticals, variables can be reduced and quality can be increased by exercising risk management, through big data analysis.
The best attack for cybercrime and fraud, is defence. Due to this, emerging markets like big data and blockchain, are being used to predict and prevent such crimes in the first place. Customer data and previous cyber attacks can be analysed for trends or patterns, and therefore future attempts can be predicted.
On a broader scale, big data can help to resolve issues relating to missed transactions or failures in net banking, and can even plan for potential spikes in server activity. In doing so, banks are better equipped to manage transactions safely, quickly and with limited risk.
For years, The Securities Exchange Commission (SEC) has been taking advantage of big data analysis, in order to monitor financial markets for illegal trades and other suspicious activity. By using network analytics and natural language processors, potential fraud of various financial markets can be quickly identified.
Advertising is one of the biggest users of big data. From social media giants like Youtube and Google to Twitter and Instagram, user data is tracked and analysed to further improve the platform. With the amount of data flooding into such services from users, big data is essential to filter the information. Amongst other uses, advertisers highlight patterns that can be used in targeted campaigns.
Arguably one of the most influential current social media platforms is Facebook, mostly due to its business benefits. Companies of all sizes can target potential consumers based on buying intent, website visits, interests, job role and demographics, in order to market to the customers most likely to make a purchase. This algorithm uses big data analysis to monitor the characteristics of each user.
Similarly to advertising, entertainment services use big data to target users with the right content. Rather than simply supplying viewers with all of the films or television shows available, services like Netflix and Youtube can recommend content based on the individuals previous viewing patterns. On top of providing the most suitable videos, this method can increase engagement and drive revenue.
A practical example of this can be found in Netflix’s thumbnail algorithm, which uses big data to improve the user entertainment experience. Their recommendation process uses viewing habits to track common patterns, and then suggest videos that are more likely to be well received.
But big data’s influence stems further than that. Even the thumbnails, which many believe to be consistent amongst all users, evolves to suit our viewing preferences. If the user is more to watch a romantic genre, then other thumbnails may be more likely to show a couple kissing. Alternatively, if the user is more likely to watch a comedy genre, then other thumbnails may choose a recognisable comedian.
Analysed user data is, or will be, used in every industry. From security to entertainment, the benefits of big data are endless - as such more and more keynote speakers specialising in the topic are emerging. But it can also be daunting and complicated to understand different types of data, so we have the solution.
By booking a big data speaker, with their expert experience and passionate enthusiasm, you will gain an insight into not just why you should use analysed information, but how you should use it to benefit your industry. Data science is showing no signs of slowing down, so find out what structured and unstructured data can do for you.