Today’s business environment is dominated by a single topic: data
With each enterprise sitting on a potential goldmine of data from user behavior, sales, marketing campaigns and systems operations, company leaders are under pressure to derive as much value as possible from their first-party resources.
Many companies, however, have taken an under-informed and ill-leveraged approach to data and analytics, putting rudimentary systems in place without understanding what they do or how to maximize their performance.
In the past, effective data analytics required expensive, highly specialized talent to sift through mountains of raw data. However, a growing collection of augmented analytics tools have more recently evolved, making data-driven insights accessible to any business, regardless of whether they have the budget to field a large, experienced data analysis team.
What exactly is augmented analytics, and how does it help to democratize data-backed decision-making?
Augmented analytics, according to Gartner, “is the use of enabling technologies such as machine learning and AI to assist with data preparation, insight generation and insight explanation to augment how people explore and analyze data in analytics and BI platforms. It also augments the expert and citizen data scientists by automating many aspects of data science, machine learning and AI model development, management and deployment.”
As more companies begin to turn to augmented analytics to support their operations, what should they look for when assessing a new tool or platform?
Read the five questions to ask before investing in augmented analytics technology in the full article on Forbes here