Data is the new oil. A tagline used over and over again to indicate the value & potential of raw data points as a resource for better decision making within business (& other) environments. While this might be true, the misconception with this tagline is that data as such is a product ready for use. Mind you that cars do not run on oil, they run on a refined form of oil - gasoline. That raises the question “how do you turn oil into gasoline” & what does this mean for the world of data?

The purpose of collecting data

First let’s ask ourselves the most important question before solving this riddle; if the role of gasoline is to power cars, which they in turn take us places, what is the role of data, what is its final product & what purpose does it serve?

The goal of collecting data is fairly simple.From raw data insights are derived in order to build better products & customer experiences. This in turn will grow the business. A growing business in turn allows for even more data collection & the cycle restarts. It’s a never ending self-feeding optimisation process.

The true purpose of collecting data is to derive insight from it, to build better products & to grow your business.

How to turn data into gasoline?

Simple; take it to a refinery. How does this apply to the world of digital business intelligence? 

Insight from data comes through analysis. Where analysis used to be fairly simple as the number of data signals used to be fairly small in the past, today’s world brings us a heap of data impossible to analyze using only human capabilities. Today’s need to refine insights from data requires increasing computing power. This comes in the form of Artificial Intelligence. More specifically Machine Learning algorithms. Think of this as the refinery. Where the refinery turns oil into gasoline, AI will help turn data into insights. What should you imagine in terms of insights derived from running your data through these AI/ML algorithms? When it comes to analysing for marketing purposes a couple of examples come to mind. ML can help predict churn rates on top of your customer base, build conversion prediction models for customers based on website visits, classify users in Recency Frequency Monetary classifications (RFM) and as such pre-qualify 3rd party data.

But how do you get oil to a refinery? Through pipelines. Just as miles of pipelines are bringing raw oil into refineries in order to be transformed into gasoline, the cloud acts as a pipeline in order to get data into AI’s perimeter. Here data points are transformed into insights ready to be put into action. Cloud serves as the gateway to Artificial Intelligence & allows organisations to leverage existing pre-trained Machine Learning (and other) models without going through a huge sunk cost of building their own infrastructure.

Once refined, the insights are ready to be put into use & improve products & experiences across the board. The end-game of all of this? Growing your business.

Welcome to the new way of running analytics

Just like cars need oil to go through a pipeline & to be transformed in a refinery in order to move forward, businesses need their data to be transported into the cloud & analysed by AI in order to build better products & grow their business as a whole.

publication author Glenn Venderlinden
Glenn Vanderlinden

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