The Full Spectrum: How a Visual Analytics Platform Empowers the Business

The Full Spectrum: How a Visual Analytics Platform Empowers the Business

The Full Spectrum: How a Visual Analytics Platform Empowers the Business

A little knowledge is a dangerous thing – and that’s especially true in information management. If you only know part of the story, you can easily make a bad decision that takes your company down the wrong path. It’s only by getting the whole story from your data that you can responsibly guide a company.

BI and analytics software can help uncover this story, but there are now hundreds of companies offering technologies designed to dig into data. This proliferation of tools is both a blessing and a curse. While competition breeds excellence, there are a few standards or best practices embraced across the board. As a result, the onus is on individual businesses to embrace and uphold policies that will enable the effective use of data in a responsible, governable way.

One increasingly attractive solution for doing data right is to leverage a visual analytics platform. Unlike standalone data visualization tools (which can provide useful but sometimes misleading views of the enterprise), a visual analytics platform weaves together all the elements of a full technology stack. This enables analysts to see the big picture, but also to drill down and across the data landscape, to not only understand what’s happening – but also why it’s happening.

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The term "platform" gets thrown around a lot in tech – what does a platform really mean, in the context of visual analytics?

Data integration has long been a challenge in BI and analytics. It was true back when companies were only dealing with a handful of important systems, and now, the explosion of cloud-based systems has made things exponentially more challenging. In marketing alone, there are more than 3,500 cloud-based solutions on the market. And while there are similarities between these applications, the reality is that they all generate different forms and formats of data.

Traditionally, organizations used ETL software to load data into data warehouses to deliver a single, unified view of data. This led to tremendous duplication of effort, which resulted in unnecessary costs, inefficiencies, and most seriously, data quality issues.

A first-class visual analytics platform will therefore include built-in data integration to help improve quality and lower cost. By marshaling data acquisition through a single platform, every aspect of the process becomes both simpler and more governable. Data governance in particular has become a major touchpoint these days; but without a centralized, manageable platform: governance is all but impossible.

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Freeform discovery is critical to data analysis. The key requirement here is to enable a "conversation with the data". Here, business users can start with one query, get a good visual representation of what the data reveals, then quickly iterate to get to an increasingly accurate picture of the data that really gives them the answers they’re looking for.

As the business world has become more multidimensional, so have the visualizations to understand that business. Analysts need the ability to add dimensions, remove them, and re-render them to get a better view.

 



Data Science Congress 2017

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