Life of a Product Manager with “No-Code BI”

“PolusAI, A No-Code BI” Changed the Life of a Product Manager?

The ongoing debate surrounding the efficacy of No-Code BI/Low-Code BI solutions has sparked my curiosity and doubt. Particularly the study shows that for CEOs and CFOs, the prospect of accessing Data or generating reports through coding can be complex and time-consuming. 

However, the Gartner and Forbes reports say that the implementation of No-Code BI (Business Intelligence) tools can be a game-changer in the world of Analytics. 

I had a lot of doubts 1year ago, but my journey with the NewFangled Vision and their product “PolusAI” changed my perception towards No-Code completely. 

Let me narrate the impact of a No-Code BI platform called “PolusAI” in the Manufacturing Industry, where I created 650 KPIs from SAP S/4 HANA applications without writing a single line of Code or Query. 

Identifying the Data Analytics Challenge

Upon joining a manufacturing company as a Product Manager, I discovered that stakeholders faced so many challenges in daily Decision-Making due to slow Data Analysis Processes. Each stakeholder had to wait for days to weeks to receive their reports. The key challenges faced by the industry are:

Dependency on the IT team and departmental members for Data Access

Stakeholders were fully dependent on the IT team and departmental members to retrieve the necessary Data for Analysis. This reliance on others created bottlenecks and increased the overall time required to obtain essential Insights.

Absence of a Data Analytics Platform

The company lacked a dedicated Data Analytics Platform, which meant stakeholders could not access efficient tools or systems that could streamline Data Analysis. This absence further hindered the speed and effectiveness of decision-making processes.

No Analytics from existing ERP SAP HANA

Despite having an ERP system in place, specifically SAP HANA, the company had not fully leveraged its Analytics Capabilities. This meant the ERP system’s Valuable Insights and Data-Driven Decision-Making potential were left untapped.

These challenges collectively contributed to the slow Data Analysis processes, significantly impeding the agility and effectiveness of Decision-Making throughout the organization.

What can be the Solution for Slow Data Analysis Process?

To address these challenges, I engaged in detailed discussions with each stakeholder, understanding their specific Data Analytics requirements. Collaboratively, we compiled a comprehensive list of reports for each department and mapped their needs with SAP HANA. 

Analyzing the current Data landscape, we proceeded to implement our  No-Code BI product of PolusAI, which comprised two essential components:

Conversatix ETL: PolusAI helped by capturing the Data from SAP S4 HANA cleansing transform and making it ready for Analytics. 

Conversatix BI: PolusAI BI enabled the creation of AI-driven reports and dashboards through three interactive modes:

NLP – Natural Language Processing: Users could employ Search and Analytics functions powered by NLP, simplifying Data Exploration.

Drag & Drop: With an intuitive Drag-and-Drop Interface, stakeholders could easily select the required columns from the Database and generate Analytics with advanced Visualizations.

Notebook: PolusAI facilitated SQL query writing within a notebook for Data Engineers interested in conducting Analytics.

Outcomes of PolusAI Implementation

The implementation of PolusAI resulted in remarkable achievements for the manufacturing company:

Empowered Stakeholders: Every stakeholder gained control over their Data, enabling them to make quick and informed decisions daily.

Eliminated Delays: The need to wait for weeks or months for daily MIS and Decision-Making reports was completely eradicated. Now, reports were readily available as soon as users accessed their machines.

Excel Files Replacement: The majority of Excel files have been removed from their user’s machines because they are using PolusAI’s AI dashboards and doing Analytics very easily.

Enhanced Efficiency: Through PolusAI, stakeholders could compare year-to-year, month-to-month, and day-to-day Data, facilitating quicker insights in a few seconds.

Reduced Dependency on IT: Previously, Data Analysis relied heavily on the IT team. However, PolusAI empowered users to independently Analyze Data from SAP S4 without any assistance, eliminating bottlenecks and delays.

Conclusion

The successful implementation of PolusAI as a No-Code BI solution in the Manufacturing Industry showcased its potential to transform Data Analytics processes. 

By Democratizing Data and enabling stakeholders to make quick decisions, PolusAI eliminated delays, increased efficiency, and reduced dependence on IT teams. 

The company’s journey exemplifies the power of No-Code BI solutions in transforming Data Analytics, enhancing decision-making, and driving overall organizational success.