It can be said that almost every organisation that’s currently active in the market makes use of big data. And nearly every department in a company can benefit from the insights that big data can offer. But handling vast amounts of information can come with problems as well as benefits, which we will explore later on in this post.
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Big data is the term used to describe a collection of data sets that are so large and complex that they require more than just the conventional means of processing. Big data is easiest to understand in terms of the 3 Vs: Volume (the amount of data), Velocity (the speed at which data is generated) and Variety (the different formats of data)).
Big data is typically categorised as structured, semi-structured or unstructured:
Structured data is information that’s highly organised and formatted. It’s typically numeric in nature and represented by columns and rows in a database, e.g. Excel or CSV files. Databases that hold data in tables like this are called relational databases.
Semi-structured data is information that doesn’t reside in a relational database – it doesn’t consist of structural data – but has similar organisational properties that make it easier to analyse, e.g. HTML code.
Unstructured data is qualitative. It’s information that does not have a pre-defined structure. Because of this, unstructured data can be difficult to deconstruct. It comes in the form of images, social media posts, pdfs, text files, video, audio, application data and so on. Unstructured data is the most abundant and is growing at the rate of 55-65% per year.
A couple of decades ago, in the 1990s, big data referred to volumes of digital information that were too big, varied and disparate for a business’s software to handle. Of course, the data didn’t stop growing. As we know now – the opposite happened. However, thanks to the likes of cloud computing and technological advancements, it’s now possible to utilise big data; accurately store it and discover patterns and correlations that offer valuable insights to inform business decisions.
How big is big data?
Research shows that we are generating almost 30 times more data today than we were 10 years ago. This isn’t too surprising when you think about how digital has advanced over the past decade with the growth of data-generating devices, the IoT (Internet of Things), and peoples’ ever-increasing dependence on, and utilisation of, AI (artificial intelligence).
But let’s talk numbers – 2.5 quintillion bytes of data are created each day. On average, office workers each receive 110 to 120 emails daily, equaling approximately 124 billion emails on any given day. And by the end of 2018, there was an estimated 22 billion internet of things (IoT) connected devices in use around the world.
As with most aspects of business, and life in general, there are both benefits and drawbacks to consider. Let’s take a look at some of the primary pros and cons of big data right now.
The pros and cons of big data
This year (2021), a report created by NewVantage Partners surveying 85 Fortune 1000 industry-leading firms found that, of those surveyed, 96% acknowledged that big data and AI efforts were yielding results, an increase from half that number (48.4%) just half a decade ago. What’s changed? With things like advanced analytical insights and data integration, organisations can now utilise big data for the benefits of the company. Here are some of the main ‘pros’ that big data can provide:
- Optimised customer experience: the most valuable asset of any business is undoubtedly its customers. So having big data at your disposal allows you to delve into advanced analytics and create special offers and communications or develop individual approaches that are personalised to each customer. Big data is drawn from places like your CRM (customer relationship management) system, social media, email transactions, etc. Being able to identify the touchpoints, pain points, trends and values of customers will enable you to action market segmentation, and therefore personalise experiences to build loyalty, enhance relationships and, essentially, improve the satisfaction of your customers.
- Increased productivity: big data tools enable businesses to analyse large amounts of data more quickly, which facilitates heightened visibility within the company and deeper customer insights. Research reported by Syncsort (now Precisely) has shown that big data tools can boost user productivity by 59.9%; this increase in operational efficiency helps to improve sales and boost customer retention, too, win-win!
- Detection of errors and fraud: AI and machine learning can detect anomalies or transaction patterns that are irregular, preventing fraudulent behaviour and security breaches that may have occurred otherwise. This advantage is most commonly experienced by the financial services industry.
- Improved decision-making: competitive edge and growth are the two main wins that businesses achieve when they optimise their decision-making. When there is a vast amount of information available in a usable format, what customers do and don’t want and their behavioural tendencies are made clear to businesses. This insight enables companies to create well-informed campaigns and strategies, tailor products, services and messages and compete within their field. With big data, decision-making becomes far more streamlined due to advanced analytical insights and the business intelligence that it facilitates. Essentially, the more customer data a company has, the more in-depth the overview of its target audience will be.
- Business agility: analysing big data provides a way to become more agile and disruptive in markets – it allows businesses to address pain points more effectively and access customer insights ahead of competitors. Having a vast amount of data at your disposal also means you’re able to effectively reevaluate risks, improve upon products, services and communications and improve your product development.
The information that businesses now have at their fingertips leads to strategic moves within the market as well as enhanced targeting and identifying and/or preventing emerging threats.
It’s true that the advantages that big data has for companies globally are many. But there are also some prominent drawbacks, too.
Let’s explore the cons of big data:
NewVantage Partners found that 90.9% of firms surveyed cite people and process challenges as the biggest barriers to becoming data-driven.
- Increased costs: whilst big data can identify more efficient ways of doing business which saves companies money, it can also incur costs. Expenses related to bandwidth, implementing software, regular updates, maintenance, extra storage and training employees, hiring data scientists and/or outsourcing.
- Cultural change: as with other technological revolutions, big data has social impacts. In order to compete in today’s digital marketplace, companies essentially have to be data-driven. That means utilising big data which changes business strategies, entails hiring new staff, reconfiguring budgets, redesigning how you analyse customer experiences. All of which, in turn, influence and affect company culture.
- Data quality: the usefulness of the analytical insights that a company draws totally depends on the quality of the information an organisation collects. Making decisions based on poor quality data can have negative and unpredictable consequences for businesses. By ‘poor quality data’ we mean data that is incomplete, in different formats or contains duplicates. Therefore, for big data to be of any real value, the information gathered must be relevant and accurate.Companies can struggle to gain a comprehensive view of their data if it’s siloed – existing in separate, unified applications. Hurree specialises in application integration for your marketing tech stack, ensuring that the tools you know and love can work better, together. Hurree offers:
- 1000s of two-way integrations
- Highly targeted customer data segment building
- Integrated workflow builder with single user interface
- Superior campaign analytics
- Security & privacy concerns: the fact that big data exists conjures questions of ownership, which in turn, creates more curiosities. Misuse of information can violate the principles of customer privacy and company security. So it’s important to remember that although big data analytics allows you to detect fraudulent behaviour, the framework itself can be subject to security breaches. Customers often have issues with big data and the idea that it is easily capable of collecting and retaining detailed information about their identity. Individuals often want to, and have the right to, know what information that companies or websites hold on them; failing to comply with data security standards and compliance requirements can result in a loss of customer trust and hefty fines.
Organisations that collect and utilise big data need to be able to ensure the privacy of customers. This means protecting the spread of confidential information, i.e. health, employment and credit records. On the business side of things, it may involve maintaining security over trade processes, products, competitive analysis, marketing strategies and sales plans. In an age where information is power, and big data is able to facilitate that power, acts like GDPR (General Data Protection Regulation) are increasingly more significant.