Augmented Analytics: The Future of Data & Analytics
Monday November 26, 2018, by Naresh Agarwal
Recently in Analytics Insight magazine I shared my insights on augmented analytics and how it is transforming the way enterprises interpret data as they undergo digital transformation. Simply put, augmented analytics is a transformative approach to data analytics through automation of insights from machine learning and natural language processes. Augmented analytics relieves enterprises from relying on time intensive manual processes for preparing and analyzing data and enables them to make meaningful discoveries while shortening the entire data analytics lifecycle by 50-80%. For organizations that have initiated augmented analytics projects, they are able to more quickly improve processes and business results by dramatically streamlining the path to finding the most accurate and relevant data.
- Accelerating data preparation and discovery
- Democratizing data analytics
- Enabling adoption of actionable insights
The reality is that augmented analytics is evolving, and as such, companies are still testing the waters and learning piece by piece. But based on the promise of what augmented analytics can bring to an organization – improved processes for competitive success – I believe that we will see more and more companies start to adopt augmented analytics as they begin to understand the benefits it can provide: speed, democratization and broad adoption. While getting started can seem a bit overwhelming given the large number of solutions available, as I recommend in the article, a good way to move forward is to work with a consulting partner with deep data and analytics experience, which can create a custom journey for your organization.
To read Augmented Analytics: The Future of Data & Analytics, visit here.
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