When it comes to the new world of analytics, the augmented analytics approach allows business users with no data science background to readily access and use analytics in an intuitive way. There are some important aspects of this approach, including auto machine learning, natural language processing (NLP) and intuitive search analytics.
Even if your business results are on target, even if you feel you have a good handle on how to run the business and what your customers want, there is always room for improvement, and the issues that arise can often come out of nowhere. Even the best business managers cannot anticipate and see how every detail of the business might come together to create a challenge OR an opportunity.
If Data Science was once the sole domain of analysts and data scientists, Augmented Data Science represents the democratized view of this domain. With Augmented Data Science, the average business user can engage with advanced analytics tools that allow for automated machine learning (AutoML) and leverage sophisticated analytical techniques and algorithms in a guided environment that uses auto-recommendations and suggestions to lead users through the complex world of data science with ease and intuitive tools.
What is Automated Machine Learning? Quite simply, it is the means by which your business can optimize resources, encourage collaboration and rapidly and dependably distribute data across the enterprise and use that data to predict, plan and achieve revenue goals.
