Data Cubed is 5! Here are 5 top data tips…

By Helen Tanner – Founder @ Data3 and BoomBoard

It’s our birthday and we’re 5 years old. Here are 5 top data tips that I’ve learnt over the last 5 years…


STOP! Don’t touch it. Walk away from the data. 

If you start with the data, you’ll explore it in the ways you’ve always done, you’ll find the same answers to the usual business questions, you’ll drown in data, or you’ll end up with a load of pretty graphs that don’t help anyone in any way.

Instead, start with the business requirements… 

  • OBJECTIVES – What do you want to achieve? What do you want to report on? What do you to analyse? What hypothesis do you want to test? What types of hidden knowledge are you trying to discover?
  • AUDIENCE – Who are you sharing the outputs with? Are they data experts or data novices? What do they need to make better decisions in their roles? What business levers can they push/pull? What level of detail do they need? How will they need to slice & dice the data?

By starting here, you can ensure that your data project, and data outputs, add value to the business and enable the business to make data-driven decisions, and ultimately make/save more money.  

We’ve all seen dashboards that are never/rarely used right? Or data projects that are never-ending and disappointing to stakeholders? Don’t do it…don’t start with the data – start with the business requirements.


Look at me – I’m clearly a gal who loves a dashboard. But creating a suite of dashboards is just the first part of any data journey, so don’t get stuck there. The reporting side, where you just share the facts and figures about a business, is just the beginning of the value you can derive from your data. That’s just chapter 1!

Instead, consider all the different types of things you can do with data…

  • Create customer segments of customers with similar behaviours or attributes
  • Augment your internal data with external data sources, to add more value, and show you the impact of external trends, such as the weather 
  • Build new data-driven products and services, such as analytics modules within your online portal
  • Apply artificial intelligence techniques to discover deeply hidden patterns and trends
  • And so much more

We’ve all worked in businesses with lots of dashboards, reports, and spreadsheets than no-one ever looks at. Don’t do it…go beyond reporting and think about your data as an asset that can be fully exploited to fulfil many different business opportunities.


Yep, I had to mention the G-word. GDPR has probably had the best marketing campaign of any regulation and everyone I speak to has heard of it, fears it, and nearly all remember what the G stands for.

Now this is a very good thing, as GDPR is all about remembering that the data most businesses use belongs to the person the data is about – it’s not the business’ data, it’s the person/business who provided the data in the first place. And GDPR is all about treating their data with care and only using it for the intended purpose.

But what I’ve seen happen is some businesses get so scared of GDPR, that they delete data ‘just in case’, they don’t analyse the data because they’re not sure if they can, and if in doubt, they just ignore it. Sometimes they’re paying more money to store the data, than they are deriving value from it!

Instead, do your research…

  • What permissions do you have to use your customers’ data? What have you told them in your T&Cs?
  • Should you follow the ICO best practice and complete a legitimate interests self-assessment about a data opportunity?
  • Do you need some expert legal help to help your internal DPO assessment?

We’ve all seen businesses making highly risk-averse decisions relating to GDPR. Don’t do it…don’t be too scared of GDPR – do your research and you can derive huge value from your data in line with GDPR best practice.


We all like to think our businesses are unique, special, different, and totally unlike any other business – we have different business models, different charging structures, different structures, and similar. It’s therefore tempting to look at off-the-shelf solutions and see all the ways that they won’t work for our business because “we’re different”…so we end up creating our own ever-so-special hand-crafted solutions from scratch…often with time-consuming, cost-increasing, and scope-creeping results.

Instead, consider the benefits of off-the-shelf solutions…

  • They are built by experts in their field
  • They incorporate lessons learnt from tons of other businesses out there
  • They are often quicker to set, cheaper to run, and easier to switch to another solution when you need it
  • They are often independently assessed, user-rated, and award-winning

We’ve all seen proprietary solutions built by in-house people, in niche programming languages, that end up becoming behemoth, toxic tech solutions that cause a ton of business headaches and legacy issues. Don’t do it – don’t DIY or BYO – there are a ton of amazing off-the-shelf data tools out there, so make the most of them.


It’s always easier to focus on the burning problem in front of you, right? It’s got everyone’s attention, it’s on fire, it’s causing loads of problems…so let’s solve that problem first.

That’s not necessarily wrong, but there’s a risk that you might think too short term and come up with a quick fix solution that needs to be built again in future.

Instead, stand back, think 2/5/10 years ahead and think about the bigger picture…

  • What does the business need across all functions/departments/regions/countries?
  • How might the business change in future, such as launching new products/services, selling in new countries/currencies, merging/acquiring other businesses, and acquiring more customers?
  • How might our people, clients, suppliers, and stakeholders change in future?
  • What might we want to do with our data in future that we don’t do, or can’t do, today?

Then make a data plan that starts small, and fixes the biggest problems first, yes, but also ensures it’s a first step towards the long term end goal. This probably means developing a data technology stack that is modular, flexible, and scalable. This probably also means ensuring you have the right permissions to use data in the way you want to in future. 

We’ve all seen interim, temporary solutions stick around for years, right? And we’ve all experienced the pain of transitioning from legacy systems to a new system? Don’t do it…don’t think short term – think bigger and longer term.


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