Creativity is the lifeblood of an enterprise! But, it is easy to get into a rut and do what has worked in the past. If a business is to succeed, it must constantly generate new ideas and new ways to address the market and its consumers. Augmented Data discovery and the new world of self-serve tools has added an interesting dimension to this discussion as it encourages business users to become Citizen Data Scientists and encourages organizations to embrace data democratization.
As businesses struggle to remain competitive and to do more with less, every enterprise is looking for a way to optimize resources, and to get the most out of every team member. To do that, the business management team must leverage the knowledge and skills of each team member as those skills relate to their role and their responsibilities. Businesses must use team member knowledge gleaned from experience and education and merge that knowledge with data and analytics to make context-based, data-driven decisions.
Advanced Analytics is the new frontier of competition and business success. While some businesses have the luxury of employing data scientists and professional analysts to help them sift through and analyze data, others do not have the budget or the structure to support these roles and, even those who employ professional data scientists do not have unlimited resources or budgets.
Business Intelligence isn’t new but the way we gather, analyze and digest this intelligence is definitely changing. In the past, business intelligence was delivered to senior executives by IT and/or business analysts. The combination of a fast-paced business environment and a limited budget and limited resource reality means that most organizations must optimize resources and time to produce results. There are few businesses today that have the luxury of waiting for information, data or reports.
How does an organization help the self-serve advanced analytics model grow and thrive? Responsibility lies in a number of places within the enterprise.
SSDP (otherwise known as self-serve data preparation) is the logical evolution of business intelligence analytical tools. With self-serve tools, data discovery and analytics tools are accessible to team members and business users across the enterprise.
How does one measure the effectiveness of a new Augmented Data Discovery solution? Once the business has chosen data democratization and implemented a self-serve analytics solution, it must measure ROI & TCO and establish metrics that will compare business results achieved before and after the implementation.
Whether we know it or not, we use Natural Language Processing every day. It makes it easier for us to interact with computers and software and allows us to perform complex searches and tasks without the help of a programmer, developer or analyst.
The successful implementation of an augmented analytics solution for business users is not just about choosing a cost-effective tool and completing a timely deployment, nor does the process stop with training. In order to get business users to embrace and adopt self-serve augmented data discovery tools, the enterprise must approach the implementation with appropriate change management processes.
The Merriam-Webster dictionary defines the word ‘augment’ this way: ‘to make greater, more numerous, larger or more intense’. If you are wondering how this applies to the term ‘augmented analytics’, you are not alone. Let’s take a closer look at Augmented Analytics and talk about why it has gotten so much attention in the business intelligence world.
