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Build a Custom Analytics Platform for In-Depth Data Insights
Why you need a custom Analytics Platform
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When it comes to starting your data journey, setting up an Analytics Platform should be your top priority.​
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A well-designed Analytics Platform acts as a powerful, self-serve tool that allows end users to access and interact with all the metrics and dimensions of your business in one place.​
This enables employees across the organisation to make truly data-driven decisions in their roles. This also frees-up your data analyst from fielding requests and enables them to focus on high-impact analysis. ​
Key features of Datagator Solutions' custom Analytics Platforms
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​​​​​​​​​​​1. Data is connected together
Behind the scenes, where possible, all the data should be seamlessly connected to each other. This integrated view eliminates data silos, giving you a more accurate and comprehensive understanding of how changes in one area affect changes in another.
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2. Users can self-serve
Self-serve analytics empowers employees at all levels to access and explore data independently, without relying on data teams. In addition to speeding up decision-making, it delivers more tailored results by allowing users to refine their data needs in real-time. As data analysts, we often see a gap between what teams initially request and what they truly need. Self-serve analytics closes this gap by enabling users to iterate and adjust their analysis, ensuring insights are aligned with the actual business questions at hand.
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3. Intuitive, click-and-drag interface
The interface should be designed in a way that makes intuitive sense to any user, whether they are familiar with the business or not. It should be organised by key business functions, such as 'Registrations', 'Add to Basket' actions, 'Sales Conversions', 'User Journeys', and so on.
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4. Everyone has a personalised workspace
It's essential for each user to have their own personalised workspace where they can freely explore and experiment with data in private.
This setup not only gives them the confidence to dive deeper into their analysis without the risk of disrupting anyone else's work, but users can freely refine ideas and test hypotheses without worrying about others seeing ‘messy’ analysis (which is an inherent part of the analysis process!).
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5. Access to a variety of visualisations
There are some analytics platform tools out there that offer a limited range of visualisations. Having access to a wide variety of visualisation options is crucial for effective data exploration. Simple visuals often work best for final presentations, but during the exploratory phase, data needs to be viewed from different angles to uncover hidden insights.
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6. Custom calculations
In an analytics platform, users should be able to create custom calculations to categorise data based on specific criteria. For example, users could set up a calculation that segments products into "High-Performing" or "Low-Performing" categories based on a sales volume threshold. This type of flexibility allows users to dynamically analyse performance, tailor insights to business objectives, and quickly identify key trends within their data.
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In conclusion, an analytics platform transforms your business into a truly data-driven operation. It empowers teams to independently explore and act on insights, while reducing the burden on overloaded data analysts who should be focusing on strategic insights.
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