Extracting data insights can be painful. Raw, unstructured data has the information you need, but you need to work for it. There’s no easy way to do it and larger data sets require a data architect, a data engineer, or a collaborative team of experts from different fields. To understand the insight extraction, you need to understand the entire process of analytics. Through analytics, you’ll be able to interpret the data more clearly and bring key insights to the surface.
Data Insights – Simplified Steps
- Organize the data – Raw data means nothing if you can’t learn from it
- Analyze the data and look for correlations or patterns
- Create context and data story
- Assemble specific data insights
Extraction
Raw data is overwhelming, especially when you’re not sure what you’re looking for. Maybe it’s something with opportunities or customers or growth, but what are you actually able to understand? Structuring the data into a readable format comes first. You’ll be able to read the data at face value by seeing all the metrics and values. The intersection of specific metrics enables a better understanding of potential contexts. From there, you’ll be creating a data story. How does geography affect this or that or what’s the scale of events after considering isolated events? Start with a wide net and work your way into key patterns.
Don’t be afraid to use some creative efforts when building context. Experimenting with the data story can reveal a range of opportunities and insights that can change everything. All the big industries do it, for just about everything and it proves to be a profitable asset. Whether it’s a unique customer behavior or risk management, you can tap into it with data insights.
And then?
The application of insights can improve anything from company budgeting to global advertising. Ideally, the insights you’ve uncovered will guide you into another data set and analysis process because you can bet it won’t be the last time. Data doesn’t rest since everyone and every digital piece of technology creates an infinite wave of data. More data and analytics will lead to more data exploration. Data is everywhere and the key to navigating the digital landscape, so make sure you’re up to speed with it.