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.
Wise business owners and managers are taking on the challenge of implementing data democracy, digital transformation (Dx), and Citizen Data Scientist initiatives. The reason is simple! These businesses understand the benefits and the advantages of providing augmented analytics access to business users, thereby improving fact-based, timely decisions and improving the planning and forecasting process. These initiatives also optimize resources and allow the business to do more with less – which is something every business needs!
While many of you may follow the research and market analytics provided by Gartner, you may sometimes find yourselves wondering if their predictions and market analysis are correct. When it comes to the predicted transformation of business users into Citizen Data Scientists, that particular transition has been happening for a while now. If anything, the global pandemic has simply made the prediction more pressing than ever.
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.
Many accounting and finance professionals use Tally ERP for data entry and reporting. If a business adds analytics to the Tally ERP environment, it can provide user-friendly augmented analytics that will optimize resources, increase productivity and add value to the business and the user by offering insight into the mountain of data contained within the Tally solution modules.
When you tell someone you work in a finance-related position, their eyes might glaze over. They picture you ‘counting beans’. Whether you work in inventory management, purchasing, accounting, enterprise finance or any other related position, your job can seem mysterious (and even boring) to many people. But, yours is the lifeblood of the organization.
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.
Perhaps you have resisted the temptation to democratize data in your organization. Your resistance may come from in-house, in the form of those who tell you that data governance is impossible in an environment where you spread your data far and wide. Perhaps you believe that the average business user cannot and will not use business intelligence tools, so any expense or time to implement such a solution would be wasteful. Perhaps you feel that the value of such a solution and of user adoption of these tools is overrated, and that ROI and TCO would not be worth the time and effort.
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.
