You have probably heard a lot about the concept of Citizen Data Scientists in industry conferences and journals. Whether you are managing a business, or a team or you are a team member in a business, you should take heed of these discussions as they will definitely change the landscape of every type of business from start-ups and small companies to large enterprises, and you would be wise to get on board.
As one of its Strategic Assumptions, Gartner predicted that ‘By 2020, more than 40% of data science tasks will be automated, resulting in increased productivity and broader usage by citizen data scientists.’ Gartner also predicts that the number of Citizen Data Scientists will grow five times faster than the number of expert data scientists through 2020, and that by 2019 the amount of advanced analytics produced by citizen data scientists will surpass that produced by data scientists.
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.
Let’s talk about data preparation! That often cumbersome, always complex process by which data scientists and IT professionals gather and prepare data for analysis. Data prep involves the extraction and transformation of raw data to prepare that data for analysis. It includes cleaning and reducing that data by removing outliers and standardizing data formats, among other things. Without data preparation, data analysis can often be misleading and incorrect – garbage in/garbage out, if you will.
If you read industry and technology journals, you have probably seen the term, ‘digital transformation’. So, what is digital transformation Gartner asked, and here is what the Gartner glossary of terms says about that: ‘Digital business transformation is the process of exploiting digital technologies and supporting capabilities to create a robust new digital business model.’ So, that is the digital technology business definition and that definition will translate differently for every organization in terms of where the enterprise will begin to focus the transformation process and how it will get to its goal.
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.
Smarten, an advanced analytics service provider, has announced that it will act as a Silver Sponsor for the Gartner Data & Analytics Summit 2019, June 10 through June 11 in Mumbai, India where it will demonstrate its Smarten Advanced Analytics solution and its product roadmap for the future of the Smarten Augmented Analytics product suite.
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.
