Big data has become a bit of a business buzzword over the past decade or so, and it can be hard to separate myth from reality. An explosion of tools, startups, courses, and blogs aimed at “solving for big data” just add to the cacophony.
Despite the hype, the concept of big data and concurrent topics such as business and marketing intelligence are useful things for all businesses to leverage. Data is here to stay, and data is something that all businesses can benefit from – both at enterprise and small-business level.
So, in a nutshell: what is it about big data that you need to know?
What is big data?
Big data is a concept that is quite hard to define despite its ubiquity: in fact, researchers regularly churn out articles on how hard it is to define. This quote from an academic journal is a good example of some of the challenges of defining big data:
“The term Big Data is commonly used to describe a range of different concepts: from the collection and aggregation of vast amounts of data, to a plethora of advanced digital techniques designed to reveal patterns related to human behavior. Despite (sic) its widespread use, the term is still loaded with conceptual vagueness”.
Oracle defines big data through the “3 Vs”: volume, velocity, and variety. This describes the nature of modern high-volume, high-velocity data gathering that does not discriminate between types and forms of data.
Talking about big data in the office the other day, one useful description came up: big data is collecting all the possible data that your business can lay its hand on, not worrying about annotating it, and just chucking in into one bucket for now, ready for it to be sorted out later.
Whether that data is structured, unstructured, annotated etc doesn’t matter: it could be usage statistics, server logs, market data, ecommerce data, analytics, app data, video feedback etc.
| Structured data | Unstructured data |
| Highly organised | Not organised |
| Formatted | No predefined format, could be anything |
| Finite | Scattered |
| Does not require further sorting | Variable |
| Can be searched through in relational databases | Needs standardising and harmonising |
But essentially, no matter how you define big data, data and being data-informed are essential business assets, feeding into better business intelligence (BI).
Business intelligence is another important concept: making your business smarter by leveraging data, e.g. knowing when the best time is to order in new stock based on purchasing trends, knowing how much to charge for a project based on previous utilisation rates etc.
What you need to know about data
What data measurement concepts are useful for your business? Here are some data insights that we have gleaned from working with our clients and their data, both big and small:
- Not all data can be compared but mixing data is powerful: power up your reporting by mixing data sources. You may have to work on your data first to make it measurable and meaningful though.
- Integrations across different data platforms and sources can help you improve your processes at a rapid pace. You might be surprised how much an integration can help you save time and money.
- Analysis is key; in fact, data storytelling and insights might be even more important than data measurement itself. It is important to get beyond the figures to what they really mean.
How can you use it for your business
So, what can big data do for your business?
Big data is great for forecasting. Whether it is tracking business trends, getting more accurate with your budgets, or using it for idea validation, big data can help you predict the future by looking at the bigger picture.
Predictive analytics can be used to predict consumer behaviour and influence supply chain decisions, and it can also help you predict the repairs and maintenance cycle too.
Machine learning is another way to leverage big data. You can use machine learning to automate parts of your business and speed up customer service, editorial work etc. This is something we have maximised in our publisher products and services.
Big data will probably help you level up your data infrastructure, or even just your infrastructure. There are lots of big data tools out there, but it is probably safe to stick with big the players. Google Cloud Platform, Microsoft PowerBI, Tableau, MongoDB, and various open-source Apache solutions are out there for you to choose from. But remember, it is not about the tools though, but rather, what you do with them.
Business benefits
There are countless advantages to embracing data, but here are some of the key ones:
- Agility and a more streamlined way of doing business
- The ability to make better business decisions
- Competitiveness and deeper insights on consumer and market trends
- Innovative business practices enabled by data
- Security improvements and risk mitigation
- Personalisation, especially in marketing.
Data pitfalls to avoid
What about what to avoid?
Not knowing what to track is probably the first hurdle, or specifically, not knowing where to locate data. At the same time, tracking everything without a strategy can be just as bad. This kind of data blindness can lead to overenthusiastic tracking with little to no strategy. Investing in data literacy is a good idea to help team members get the most out of data.
GDPR tends to create a lot of anxiety and misinformation. This can make cookie and consent management challenging in data collection environments. It is important to really understand data and privacy laws in their proper context and seek professional advice whenever you are unsure.
Not considering storage and data warehousing can come to haunt you later. We always recommend clients look at the bigger picture and start by mapping out their data environment before diving in to avoid overcommiting to any specific tool or method.
3 big data myths to bust
- Small businesses have big data too. Business intelligence is not just for massive enterprise brands, everyone can benefit from better data practices and management.
- Leveraging big data for your business is not as hard as you think. You might not need as many specialist skills as you first think, as a lot of good data management comes down to strategy and common sense.
- Lastly, big data is not some mythical thing: in fact, data is everywhere – algorithms, predictive intelligence – all of these are part of our everyday lives now. In some ways, data is quite banal and big data is becoming ‘normalised’.
