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Augmented Analytics Isn’t Really Scary at All

How many times have you heard the words “big data” or “data science,” and couldn’t help feeling a bit daunted or intimidated by the words BIG and SCIENCE?

As billions to trillions of records of millions of people’s activity—online sales, customer center contacts, use of social media, mobile data and so on—continue to grow, big data and data science are inevitable and unavoidable. Where do you start? How do you begin to take control of and leverage all this data to your advantage?

Enter artificial intelligence (AI) or machine learning (ML), which enables accessibility of data and ease of use through natural language generation, text mining and automated data processing. While equally as scary-sounding, this trend—coined Augmented Analytics by Gartner, a leading research and advisory company—means that a user (not necessarily an IT professional or a sophisticated analyst) can take advantage of advanced analytical systems.

Analytic and business intelligence (BI) tools are quickly becoming easier to use with drag-and-drop user interfaces that require little to no knowledge of statistical analysis or algorithms, but Augmented Analytics takes it a step further by incorporating ML to automate data profiling, data quality, data models and adding metadata and storing it in catalogs.

Augmented Analytics can facilitate the gathering, cleansing, organization, integration and analysis of data with ease. I can personally remember spending countless hours (and sometimes days) scrubbing and categorizing data. These labor-intensive tasks can now be automated with ease. Relationships, patterns and trends in data are quickly identified and used to forecast or predict results without personal biases. Even the most inconspicuous but nonetheless meaningful drivers of performance that would otherwise be missed can be exposed and/or leveraged. Data discrepancies and outliers can be identified and used to recognize either challenges or opportunities. Effective visualization techniques and formats are also suggested.

What does this mean? Business intelligence capabilities are shifting from user-created reports and dashboards to automatically generated insights based on data. Mind blown!

This breakthrough is just beginning and expected to grow FAST in the next few years. Integration of AI or ML is already found within many analytics tools. But while these systems can detect some correlations and anomalies in data, they often fall short of connecting these discoveries with business situations or actions to give practical recommendations. That’s our job. While AI is closing the gap, there’s simply no substitute for human thoughts and ideas.

I personally can’t wait to see what’s next. (See that wasn’t really scary at all.)

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Digital Analyst

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