Or maybe it’s just good old-fashioned bars and coins made of gold. After all, a currency’s worth is defined by what you make of it — and the more there is to go around, the more that can be made.
That’s why in the world of business and technology, today’s most valuable currency is data. The more data an organisation harnesses, the greater the possibility it can use that information to carry out real-time analysis and build powerful new applications. Across every industry, big data makes it easy to draw new conclusions, recognise patterns and predict future trends. The result is a world that’s better informed by behaviour, trends and reality.
Of course, that’s not to say every application of big data has a benevolent purpose. Many privacy advocates worry that collecting massive amounts of information about individuals, groups of people and behaviour could lead to new technologies that can have devastating and nefarious consequences for people around the planet.
While it’s easy to understand those concerns, the vast majority of big data applications exist in order to improve analysis that helps users make better decisions. Coupled with the vast amounts of data already stored and collected, real-time data collection and analysis make it possible to truly transform business by instantly offering insights that could only previously be gathered with intense amounts of time and energy.
Here’s our breakdown of the pros, cons and everything in between about today’s big data boom:
The term “big data” refers to the technologies related to the capture, collection and processing of information. Big data doesn’t simply describe data sets and databases: It applies to the frameworks, techniques and tools meant to analyse information.
Data is often collected through any sort of process that generates data in the first place, including social media sites, utility infrastructure and public records, search engines, mobile applications, connected devices like smart televisions and any other source with information that companies have permission to access.
Source: Forbes
Upon being collected, big data sets may be placed in a semi-structured, structured or unstructured database for further analysis and processing.
Source: IBM
Typically, data gets collected and analysed at specific intervals, but real-time data analytics services make it possible to acquire and analyse on a continuous basis. The transformative nature of a real-time data processing loop makes it possible to offer users instant insights without the need to wait for additional analysis.
Collecting, processing and analysing data in real-time offers users incredible benefits. With large data sets, for instance, real-time data analytics companies make it possible to quickly detect anomalies like errors or fraud. It’s a significant defence mechanism to ensure an organisation can safeguard against the loss of crucial financial data or proprietary information.
Real-time data analysis also allows businesses to create effective strategies that weren’t possible in the past. Sales data, industry trends and market indicators can help organisations stand out from their competitors by better understanding customer behaviour and the products and services they prefer.
Armed with this data, companies can also improve their operations across areas like customer service. The more information an organisation collects about a user’s tastes and preferences, the more it’s possible for big data technologies to turn that information into action to create experiences that are more personal, responsive and accurate than ever before.
In industries like healthcare, for instance, real-time analysis of big data makes it possible to improve and save the lives of patients through the collection and analysis of vital health information. Electronic health records coupled with data collected from wearable health devices make it possible to prevent deadly hospital infections or ensure an incorrect drug is not administered to a patient. Despite concerns over privacy and the sheer amount of personal data that could be collected by a healthcare organisation, the fact that big data makes it possible to prevent catastrophic accidents and save lives makes for a compelling argument.
While big data offers incredible potential to transform lives and businesses around the world, it’s not without challenges. Logistically, companies looking to deploy big data must rethink their entire approach to data collection. Real-time analysis requires constant data collection rather than periodic collection, requiring major changes to business strategies and a significant investment of money.
And in order to carry out real-time analysis, companies can’t simply depend on software alone: They must hire data scientists, experts on big data visualisation and other related professionals in order to make sense of the information, which further adds to the price of admission.
Without the tools or staff in place to properly handle data management, a company doesn’t just risk squandering the opportunity to make valuable insights: It could also place the company in legal jeopardy. Thanks to legislation such as the European Union’s General Data Protection Regulation (GDPR), the security and privacy of personal information and data trump the desires of any business. Mishandling or misrepresenting data collection and processing can result in serious fines that can greatly impact a company’s bottom line.
But above all, one of the biggest concerns the public at large has regarding big data is the threat that mass data collection poses to privacy. Data gathered from license plate scanners, drones and security cameras gives civil libertarians concern over being constantly monitored when going about their private business. The manipulation of data sets from social media has made it possible to disrupt elections and political activities around the globe. And in countries like China, big data is being used to track and analyse the behaviour of citizens, creating a modern police state where a citizen’s every move is watched.
With the explosion of artificial intelligence and Internet of Things (IoT) devices, big data has become more valuable than ever before.
Considering data powers everything from machine learning algorithms to a meal delivery user’s food preferences, companies have only begun to scratch the surface of the possibilities big data holds. But no matter the business, government or organisational need for big data, it remains crucial for big data operations to develop best practices for real-time analysis that protect private user information.
Editor’s Note: This post was originally published in September 2015 and has been updated for accuracy and comprehensiveness.