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Create a data-driven culture with Business Intelligence

As the complexity and pace of business increases, organisations are continuously on the lookout for new ways improve business performance and operational efficiency. Key to this is ensuring everyone has access to real-time, accurate information that will support them to make the right decisions. With the volume of data generated by businesses, many are recognising data as an incredible internal resource. But true value can only be extracted when it is managed intelligently.

Enter Business Intelligence (BI) - a cyclical approach for transforming related business data into information, turning that data into knowledge and leveraging knowledge to generate real, actionable intelligence.

What exactly is Business Intelligence?

BI is a technology-driven process that involves a wide category of applications and technologies in order to collect, store, analyse and provide access to data to help executives, managers and end users make fact-based business decisions.

It can be applied across many areas of a business including customer support or profiling, market research or segmentation, product development and profitability, statistical analysis, even inventory and distribution analysis. But the end game is often similar - to reduce costs, identify new business opportunities or spot inefficient business processes.

If you’re considering adopting a BI initiative at your company, it’s important to get the foundations right. In this article we highlight the four key steps that should be at the core of your BI efforts.

Articulate your vision and goal

Prior to diving into a BI initiative, you first must consider what you want to do with your data. After all, you want to turn your data into knowledge you can use. You should also set out what you want to accomplish – both as a whole and incrementally.

Looking at the bigger picture is essential if you want to ensure your path forward is aligned with organisational strategies and delivering business value.

Ask yourself:

· What do we want to achieve?

· Are there any smaller goals we would like to tick off throughout the project?

· What problem are we solving that has previously been elusive?

· What will we be able achieve by unlocking insights from specific data sets?

· How will we use this knowledge to improve our performance or efficiencies?

· How will we measure the success of the project?

By understanding these high-level goals, you will be able to better design and guide your BI project.

Getting the foundations right

A recent report found that 84% of CEOs are concerned about the quality of the data they’re basing decisions on[1]. Meanwhile, according to Gartner, the average financial impact of poor data on businesses is $9.7 million per year[2]. Clean, reliable data is certainly critical.

In the BI world, you need to trust your data and be confident the decisions you’re making based on that data are sound.

Because you will be extracting information from multiple sources of data you need to create a a central source of truth – or data mart. This involves moving, merging, and consolidating enterprise data into one central system. Not only does this create a system of record, it also helps avoid the problems associated with disparate and redundant data, such as conflicting data or multiple versions of the truth. This will ensure clean data in, clean analytics out.

At this point you can also begin to consider the tools and platforms you will be using to support users to perform their own information exploitation, analysis, and visualisations.

Coming to grips with your data

This step involves understanding and visualising your business data. It’s all about exploring the data sets in more depth - browsing, modelling and presenting the data in unique ways. Sometimes called data mining or knowledge discovery, this is really when you can synthesise useful knowledge from your collections of data and begin to get the answers you set out to find.

As you become familiar with the data, depending on your goals, you can estimate trends, integrate and summarise disparate information, validate models of understanding or predict missing information.

To help the brain quickly extract meaning, dashboards and visualisations will also help during the exploratory stage. At this point, end users can be given access to undergo their own exploration or align the strategy to the data.

The continuous value loop

You may have found the answers you were looking for, but it doesn’t spell the end of a BI program. Data is an evolving asset. It is constantly growing and changing.

This is why BI programs are often multiple-phased - the early findings can shape future initiatives and programs. Or even reshape the entire initiative.

It’s also important to remain sceptical. Always analyse data from at least two angles and manage any blind spots that could jeopardise your analytics. By remaining vigilant, you will start to get answers you can trust, and be confident you’re making true data-led decisions.

How Cubicus helps

Be confident that you're making the right decisions and taking the right actions to drive your business forward with Cubicus. We help organisations get more value from their data — and make better-informed business decisions — with an integrated, holistic approach to the data and analytics lifecycle. Contact us here.

[1] IBM, How can you trust your data without the big picture? Available at:

[2] Forbes, Poor-Quality Data Imposes Costs and Risks on Businesses, Says New Forbes Insights Report. Available at:

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