If you have attended technology conferences or read industry publications, you have probably heard the term ‘Data Literacy’. If your enterprise is considering undertaking an initiative to encourage and nurture data literacy in your organization, you may be looking for a better understanding of the concept and the benefits.
I hope you would agree that every team member in your business is an important and valuable resource. When we talk, in the tech world, about self-serve apps and the concept of cascading analytics to everyone in the organization, managers and team members start to get nervous.
The term ‘data analytics can seem daunting to the average business user. Isn’t analytics something that is the sole domain of data scientists? No, actually it is not!
Discover the Smarten approach to Augmented Analytics and Advanced Data Discovery tools. These tools allow business users to leverage augmented analytics that provide guides and suggestions to help the business user more quickly and effectively produce clear advanced analytics with little to no training, thereby transforming the average business user into a Citizen Data Scientist. Using the Smarten approach, users can quickly and easily prepare and analyze data and visualize and explore data, notate and highlight data and share data with others.
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.
Data discovery is not data management. If one is to make the right decisions in business, one must engage in data exploration and data profiling. In other words, one must gather, prepare and analyze data to truly understand how the business is working, what must change, what activities and tasks support the goals of the business, and what the business should anticipate in the future in terms of revenue, risk, resources, financial investment, growth, products, location and all other aspects of business.
If you want to include predictive analytics and forecasting in your planning process, there are numerous analytical techniques and algorithms at your disposal.
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.
Business markets and competition are moving much more quickly these days and predicting, planning and forecasting is more important than ever. It is also important to ensure that every team member is a real asset to the organization and can contribute their knowledge and skill with full Insight into the effects and outcome of activities and processes and the ability to correct the course and make recommendations using clear, concise information. Advanced analytics is the logical tool to help a business optimize its investments and achieve its goals.
There are a myriad of predictive analytics techniques and predictive modeling algorithms and you can’t expect your business users to understand and use them. If you are taking on an advanced analytics initiative and you want to leverage data democratization to cascade data analytics and data literacy throughout the organization, you will need a data modeling solution that takes the guesswork out of the process.
