Smart data visualization tools should include augmented data discovery with features that guide and show business users how to get the most out of data and how to display that data in a way that will make decision-making and analysis as easy as drag and drop. Data visualization does not have to be complicated, nor does it require software or features that take months to learn and master.
Augmented analytics can help your business users to find and understand critical data and to do their jobs more effectively. Without the knowledge of a data scientist or an IT professional, business users can perform advanced analytics, using features that guide and make recommendations at every step so that data is prepared, viewed and analyzed in a way that ensures clarity and a comprehensive understanding of trends, patterns, and data sensitivity and success thresholds.
Augmented Analytics and augmented data discovery is a form of advanced data discovery that automates data insight using machine learning and natural language generation. It automates data preparation and makes it easy for business users to enjoy data sharing.
Assistive Predictive Modeling allows business users to leverage a self-serve advanced analytical tool and to enjoy complex, sophisticated forecasting and business predictions in a simple, user-friendly dashboard environment – all without the skills of an analyst, data scientist or IT professional.
There are so many new terms in the business intelligence and advanced analytics domain. So, what is augmented data discovery, and why is it important for your enterprise? Augmented Data Discovery (aka Smart Data Discovery), takes the enterprise beyond data monitoring and helps users discover the more subtle yet crucial factors that affect business success. It identifies hidden issues and patterns within the data so the organization can address challenges, capitalize on competitive and market advantages and plan for the future with more confidence. There are a couple of components to the augmented data discovery continuum.
Your business users are ready to do the job! They have a lot of data spread across the enterprise in various data repositories and forms and they want to pull it all together and analyze the data to get the answers to the questions you ask them every day. But, preparing that data is not easy.
Assisted predictive modeling is no longer the sole domain of data scientists and IT staff. With the right predictive analytics tools, your business users can accurately plan and forecast results and share data to build a dependable picture of the future for your organization, and for each team, division and individual.
The concept of Augmented Analytics may sound complicated (and it may, in fact, be a challenge for a software vendor to accomplish), but the new augmented data discovery tools are quite easy to use. Unlike the data discovery tools of old, business users do not need to look to the IT staff or data scientists to perform advanced data discovery.
Does your business intelligence solution provide true advanced analytics capabilities? Can your BI tool satisfy the needs of business users, data scientists and IT staff? That may seem like a tall order but with the right business intelligence software, you can provide predictive analytics for business users, including assisted predictive modeling that walks users through the analytical process and allows them to achieve the best results without a sophisticated knowledge of data analytical techniques.
Self-Serve Data Preparation (aka augmented data preparation) is all about efficiency and the presentation of sophisticated data preparation tools in an easy-to-use environment. The idea behind self-service data preparation is to give the average business user the ability to prepare, use, report on and share data without the assistance of IT staff or analysts, thereby making their jobs easier and making every team member more of an asset to the organization.
