A recent report revealed that by, 2028, the Augmented Analytics market is projected to reach USD 46.26 billion at a CAGR of 24.30%. The business intelligence solution market has evolved into augmented analytics and these solutions designs have progressed to support average business users with simple solutions that combine sophisticated analytical techniques and algorithms with easy navigation, reporting and insight.
If you are a business owner, executive or manager, you have already heard about (and are probably implementing) strategies for Citizen Data Scientists. If you are a business user, you may be hearing rumblings of this in your everyday work and wondering exactly what this type of initiative means for you and why you should consider it beneficial.
Natural Language Processing (NLP) may not be a term that everyone is familiar with but all consumers and business users are certainly aware of its power. You use natural language processing every day when you perform a search in Google using questions written in the same way one would speak or write to another person. Whether you know it or not, you are using NLP to process, interpret and return results that meet your criteria.
By now, every wise business team has acknowledged the advent of digital transformation and the transformation of business users into Citizen Data Scientists. But acknowledging the reality and enabling that reality within the walls of an enterprise are two very different things. Where many businesses fail in implementing the Citizen Data Scientist initiative, it is typical to find that the business has simply decided to deploy the strategy without much planning or culture change. Without understanding the shift in workflow, responsibilities and how the use of data will change the enterprise, it is unlikely that the business will succeed in its Citizen Data Scientist initiative.
Our Partner is a healthcare service provider in the United States providing a web-based, patient-centric, healthcare management solution and workflow solutions to increase operational efficiency and reduce costs for its hospitals and healthcare facility Clients. Since 1999, the Partner has provided services to the durable medical equipment and supply market with solutions that benefit many healthcare organizations and clinics in the U.S.
The Client is one of the largest Rural Fintech companies in India with more than 700,000 Rural Entrepreneurs and services to benefit 100 million consumers. The Client business is currently growing at 150% year over year with a transformative impact on digital, financial, and e-retail services across rural and semi-urban regions.
Predictive analytics may seem too complex for business users but with advanced technology like machine learning and features like assisted predictive modeling users can dive into the process without the skills of an IT professional or a data scientist. Assisted predictive modeling frees the user by providing system recommendations that will suggest the right analytical technique and achieve the best fit for what the user wants to do, ensuring that they use the most appropriate algorithm for the data they wish to analyze.
The Partner is based in India and offers an Audit, Compliance and Risk Management solution for banks, insurance companies and financial institutions. The comprehensive solution helps organizations to improve efficiency and effectiveness of audit department operations by standardizing organizational audit procedures to manage internal risks and compliance.
The focus of this article is on Data Democratization within the business enterprise, but the concepts and approaches involved in implementing this type of initiative are worth considering for any kind of major change within an organization.
When your enterprise turns to you to inhabit the Citizen Data Scientist role, it may (or may not) provide information on what that role is, why it is important for business users to transform into the role and exactly how the transformation will work. Online training programs, like the one mentioned in the closing lines of this article, provide information on the role, its purpose, how to collaborate with data scientists and IT, how augmented analytics solutions work and the types of analytical techniques you will be using.
