As the need for advanced analytics increases in organizations, enterprises large and small struggle to find and sustain the professional resources they need to meet their requirements for data, analysis and strategic direction.
In some businesses, Data Scientists, professional analysts and IT staff are often buried under requests for analysis and data and, as a result, these teams are unable to focus on strategic issues and on crucial questions that require 100% accuracy to drive the direction of the business.
For other businesses, the issue is more pressing. When a company cannot afford to hire data scientists or analysts because of budgets and financial constraints, the problem is clear. There is a need for Advanced Analytics but there is no funding to hire the required resources.
The Gartner report entitled, ‘Augmented Analytics Is the Future of Data and Analytics, published on October 31, 2018, includes the following strategic assumptions:
- By 2025, a scarcity of data scientists will no longer hinder the adoption of data science and machine learning in organizations.
- By 2020, automation of data science tasks will enable citizen data scientists to produce a higher volume of advanced analysis than specialized data scientists.
In this rapidly changing, increasingly competitive business landscape, the wise enterprise will focus, not on adding dozens of data scientists, but on capitalizing on the time and skills of those data scientists and analysts by giving business users the ability to tools they need to make the day-to-day decisions and to produce data-driven analytics that are accurate and timely without the assistance of a data scientist.
As businesses incorporate self-serve advanced analytics into their technology landscape and business users adopt these tools and begin to share and learn from Data Analysis, the business can transition to a more balanced environment that allows data scientists and analysts the time and focus to perform critical activities.
Augmented Analytics, Assisted Predictive Modeling, Smart Data Visualization, Self-Serve Data Preparation and Search Analytics are designed to help the average business user with auto-suggestions and recommendations on how to prepare and view data to achieve the best outcomes and make analysis easy and clear.
When business users can transition to Citizen Data Scientists, the organization will enjoy numerous benefits, including:
- Support for day-to-day business decisions
- Insight, perspective and analysis
- Quick hypothesis and prototyping
- Improved agility for business development
- Timely and accurate decision-making
- Emergence of power users and data popularity
- Transformation to citizen data scientists
- Reduction in day-to-day requests
- Ability to focus on strategic projects
- Focus on projects that require 100% accuracy
- Ability to achieve mature modeling goals
Original Post: Can My Business Achieve Optimal Analytics Without Hiring Dozens of Data Scientists?Share