Analytics and advanced analytics techniques can seem daunting to the average business user but they need not be. If a business wants its users to adopt and use analytics tools, an augmented analytics solution is the way to go. These solutions are easy to use and provide guidance and auto-recommendations to help users gather and analyze data using the right analytical technique.
When a business decides to undertake a data democratization and data literacy initiative, it is important to recognize that not all advanced analytics solutions are created equal. Business users who are expected to take on the task of analytics, will need an augmented analytics solution that can support their needs. They aren’t data scientists. They aren’t business analysts. They are business professionals who will want to use an analytics solution that can give them sophisticated output and information. It has to be easy enough to use without the need for assistance by IT or data scientists and it has to be a solution that can be personalized to produce reports and analytics that are easy for each user to leverage to make decisions, solve problems and identify opportunities.
The average business user does not have a full grasp of Advanced Data Discovery or Data Preparation methods, and most organizations would not want business users to waste precious time trying to navigate the complexities of a manual data preparation process. If a business provides a solid foundation for self-serve business intelligence with augmented data preparation features, business users can quickly and easily prepare data for analysis and get the results they need to move forward and make decisions.
When businesses take on the task of forecasting and planning, it is important to provide the tools to go through this process at all levels with data integrated from the various systems and databases across the enterprise and to provide simple tools for all users that can be adopted and used to take on the various tasks and responsibilities involved in planning and accurate forecasting.
If you are trying to convince your executive management or IT team of the benefits of augmented analytics, you really don’t have to look far for support. Augmented analytics benefits are numerous and, while some benefits are self-evident, many are more subtle and will be uniquely effective within you own enterprise.
Assisted predictive modeling! The term sounds complex and intimidating, doesn’t it? But nothing could be further from the truth. The word ‘assisted’ is the key! It is true that without the skills and knowledge of a data scientist or a business analyst, predictive analysis can be a daunting task.
Predictive analytics is more refined, more dependable and more comprehensive than ever. The foundation for predictive analysis is a great predictive analytics tool, and features and function that include assisted predictive modeling.
Smart data discovery is not dependent on a few geniuses sitting in a science lab somewhere! With appropriate data discovery tools your team members can leverage their knowledge of their role and domain, and the needs of their division, team or business unit to find the data and insight that is most meaningful to them.
When we use terms like ‘predictive analytics’, it sometimes puts off the general business population. Team members might envision everything from a crystal ball to complex charts and graphs with unreadable numbers and conclusions. While predictive analytics techniques and predictive modeling does include complicated algorithms.
