Asking The Right Questions of Your Data

Asking The Right Questions of Your Data

As data and the value it offers businesses and organisations gather increasing importance, its influence on how we develop our businesses grows. It’s an industry now worth billions of dollars, with everyone from mom and pop stores through to global multinationals investing in collecting and understanding their data through a variety of tools and platforms.

Recent research has shown that over 55% of senior executives and decision-makers will increase their investment in data over the coming years, and for long-established and traditional companies their fear is losing out to start-ups and tech-savvy organisations embracing big data and the knowledge leverage it offers them. Case studies in recent years also show that organisations who invest in managing and analysing their data not only increases sales and engagement with their customers or audience but substantially reduces operational costs.

Data’s impact on businesses and organisations is clearly on the up and many of the decision-makers believe investing in it will solve many of their problems. However, it’s not a one-size fits all issue, and no matter how good or complex the systems you invest in are, the answers and solutions you need won’t come unless you ask very specific and relevant questions. Asking the right questions comes through experience and in improving your own understanding of what your data tells you.

Viur allows you to aggregate and easily review and understand your data. But what sort of questions should you be asking? Get more from your analysis with our five-point strategy to asking the right questions!


1. Start with a target. What do you want to find out

While the hype means many executives and decision-makers often focus on the acquisition of data, this seems a good time and place to remind of the importance of the acquisition of the right data. There’s no point in creating volumes of data without a specific end-goal in mind, though many organisations do keep the open approach with a mind to retaining data that may have a future, unseen use. The organisation with the most data to hand isn't necessarily the one to come out on top.

Everyone agrees that data can help to build your business, improve customer and audience relations, and fine tune operations. But how? Consider your end goals and the KPIs relevant to getting you there. Clearly determining targets helps to define the questions that need to be asked, as well as putting you on the road to using the right platforms for acquiring and analysing the data.

Understanding the purpose of the data helps greatly with understanding how to read and interpret it, and how to ask further questions or identify the changes and decisions that will benefit and grow your business.


2. What are your data sources?

Your source of data naturally plays a vital role in accuracy and relevance of what’s collected to help achieve your goals. The more information you have available for analysis, the more relevant data you should be able to retrieve, particularly today when the analytics tools available are higher and more sophisticated than ever before. It’s possible to get micro levels of detail almost at an atomic level.

If you’re clear about the questions you want to ask - which you now are after reading point 1 - you can easily identify the exact platforms you need to unearth your valuable data. When setting up your BI system, be sure to select all the fields you’ll need. Consider potential future data needs by going beyond than just selecting the fields for today, allowing for gathering even more meaningful data. Double-check everything and pay attention to detail. This might sound obvious, but many projects or organisations fail to get the big picture simply because five minutes weren’t taken to double-check.

There are an abundance of data and analytics platforms out there for every imaginable form of analysis, from marketing to medical to inventory-keeping, so be sure to match the right one for your needs.


3. Know the Measures and Dimensions of your data

A key fundamental for new Business Intelligence users is understanding the Measures and Dimensions of their data, which are the most tangible aspects of data aggregation.

A Measure is data aggregated by a formula such as the average, minimum, maximum or median, resulting in a numerical value for each. Alone these measures result in information indicating how the overall process is behaving. The absence of other data makes understanding the meaning of the measure's actual value harder. Which is why we need Dimensions.

A Dimension is the breakdown of the measure, creating a context for the user to understand the meaning of their measures, such as the total number (measure using sum) of users by country (dimension). Dimensions can be strings (such as country), dates (hour, day, week, month, year, etc) or numbers in bucket form. These combinations’ context bring a more meaningful result in the creation of a single "average duration" measure.

As new measures are introduced to the dimension, new values are created offering the user further insights into their data.


4. What types of Visualization should you use?

Aggregating and visualising your data from a variety of sources into a clean and easily readable form can be hard work. One solution is to use a dashboard from a service like Viur. The right presentation of data not only presents it in visually pleasing manner, but in the right manner with simple charts and graphs making the information more attractive to the end user, and easy to interpret and understand.

Viur supports the all the most common and fundamental charts and tables, including:
Bar chart, Line chart, Pie chart, Area chart, Funnel, Scatter/Bubble chart.

The topic of visualisation is important and we’ll detail all the best options, and offer our tips to help you make the most of it in another blog post.


5. Your data’s end users

One final consideration to make when working out your strategy is to remember who is the end user and how will they use the data. Every data user, whether they're an individual or an organisation, will have different expectations and demands, not to mention different levels of expertise, understanding and skills in analysing the reports given to them.

If reports are for internal use, the user already has a head-start in understanding the information reported and the level of complexity required. Visualisation of data should be easily absorbed and actionable, so be sure they can be read and understood easily. The level of background knowledge and depth of the user’s integration into the organisation will greatly impact their reception of the report.

Data analysis isn’t there to discipline employees or attribute blame for failure but to improve performance and motivation.

Sign up for a 21-day, no-ties free trial today, and discover the advantages Viur can bring to your business.