Co-create with Ideas2IT










Business teams were often delayed by the complexities of data analysis tools. These users lacked the technical expertise to write complex SQL queries or navigate advanced analytical tools, creating a dependency on IT or data teams for insights. This reliance led to inefficiencies, delays in decision-making, and missed opportunities.Reports and data insights had to be manually created by IT or data teams, which added significant wait times to the decision-making process. This resulted in missed opportunities and inefficiencies across the organization.Non-technical users faced challenges with the complexity of the tools, making it difficult for them to access and understand insights on their own quickly. This led to frustration and a lack of agility in responding to emerging trends or market shifts.
Our shared goal was to develop an intuitive, dynamic platform that would allow non-technical users to easily generate tables, reports, and visualizations based on natural language queries. This solution needed to simplify the data interaction process, allowing users to focus on insights and decision-making without the technical complexities.We aimed to create a seamless, scalable solution that integrated with existing data repositories while also fostering a culture of self-service data analytics within the organization. The solution would empower business users to generate valuable insights without waiting for IT or analytics teams, enabling more agile decision-making across the business.
Our solution leveraged Natural Language Processing (NLP) to convert plain English queries into structured database queries (e.g., SQL), making data retrieval accessible to non-technical users. The platform generated dynamic tables based on user input, presenting detailed data without the need for manual formatting or coding. Key features of the solution included:
The implementation of the dynamic table generation platform transformed the organization’s decision-making process. Business units made decisions 2.5x faster as a result of quicker access to data and insights, leading to more agile responses to market shifts.
The platform’s flexible architecture allowed it to scale as the organization’s data needs grew while also supporting evolving data structures and user requirements. It offered a variety of visualization formats, allowing users to interact with data in the way that best suited their needs.
We'd love to brainstorm your priority tech initiatives and contribute to the best outcomes.
Pharma & Life Sciences
Business teams were often delayed by the complexities of data analysis tools. These users lacked the technical expertise to write complex SQL queries or navigate advanced analytical tools, creating a dependency on IT or data teams for insights. This reliance led to inefficiencies, delays in decision-making, and missed opportunities.Reports and data insights had to be manually created by IT or data teams, which added significant wait times to the decision-making process. This resulted in missed opportunities and inefficiencies across the organization.Non-technical users faced challenges with the complexity of the tools, making it difficult for them to access and understand insights on their own quickly. This led to frustration and a lack of agility in responding to emerging trends or market shifts.
Our shared goal was to develop an intuitive, dynamic platform that would allow non-technical users to easily generate tables, reports, and visualizations based on natural language queries. This solution needed to simplify the data interaction process, allowing users to focus on insights and decision-making without the technical complexities.We aimed to create a seamless, scalable solution that integrated with existing data repositories while also fostering a culture of self-service data analytics within the organization. The solution would empower business users to generate valuable insights without waiting for IT or analytics teams, enabling more agile decision-making across the business.
Our solution leveraged Natural Language Processing (NLP) to convert plain English queries into structured database queries (e.g., SQL), making data retrieval accessible to non-technical users. The platform generated dynamic tables based on user input, presenting detailed data without the need for manual formatting or coding. Key features of the solution included:
The implementation of the dynamic table generation platform transformed the organization’s decision-making process. Business units made decisions 2.5x faster as a result of quicker access to data and insights, leading to more agile responses to market shifts.
The platform’s flexible architecture allowed it to scale as the organization’s data needs grew while also supporting evolving data structures and user requirements. It offered a variety of visualization formats, allowing users to interact with data in the way that best suited their needs.
Pharma & Life Sciences
Business teams were often delayed by the complexities of data analysis tools. These users lacked the technical expertise to write complex SQL queries or navigate advanced analytical tools, creating a dependency on IT or data teams for insights. This reliance led to inefficiencies, delays in decision-making, and missed opportunities.Reports and data insights had to be manually created by IT or data teams, which added significant wait times to the decision-making process. This resulted in missed opportunities and inefficiencies across the organization.Non-technical users faced challenges with the complexity of the tools, making it difficult for them to access and understand insights on their own quickly. This led to frustration and a lack of agility in responding to emerging trends or market shifts.
Our shared goal was to develop an intuitive, dynamic platform that would allow non-technical users to easily generate tables, reports, and visualizations based on natural language queries. This solution needed to simplify the data interaction process, allowing users to focus on insights and decision-making without the technical complexities.We aimed to create a seamless, scalable solution that integrated with existing data repositories while also fostering a culture of self-service data analytics within the organization. The solution would empower business users to generate valuable insights without waiting for IT or analytics teams, enabling more agile decision-making across the business.
Our solution leveraged Natural Language Processing (NLP) to convert plain English queries into structured database queries (e.g., SQL), making data retrieval accessible to non-technical users. The platform generated dynamic tables based on user input, presenting detailed data without the need for manual formatting or coding. Key features of the solution included:
The implementation of the dynamic table generation platform transformed the organization’s decision-making process. Business units made decisions 2.5x faster as a result of quicker access to data and insights, leading to more agile responses to market shifts.
The platform’s flexible architecture allowed it to scale as the organization’s data needs grew while also supporting evolving data structures and user requirements. It offered a variety of visualization formats, allowing users to interact with data in the way that best suited their needs.
We'd love to brainstorm your priority tech initiatives and contribute to the best outcomes.
From SQL Bottlenecks to Self-Service Insights: A Case Study in NLP-Driven Data Access for a Pharma Giant
The client had a vast internal data ecosystem, but business teams struggled to access it.
Users couldn’t write SQL, BI dashboards were rigid, and nearly every data request required IT or analytics support. This created long lead times for even basic questions.
The outcome: delayed decisions, missed opportunities, and underutilized data assets.
The company needed a new interface to its data that is something fast, intuitive, and usable by non-technical roles.
Operational bottlenecks included:
Dashboard access was the difficult are than the actual dashboard creation itself..
Ideas2IT developed a zero-code decision support platform that lets business users ask questions in plain English and receive instant answers, complete with charts and tables, within seconds.
Key Capabilities and Architecture:
The system enabled data access at the speed of conversation without compromising governance or accuracy.
Business teams could now explore data, answer questions, and make decisions—without waiting in dev queues or struggling through complex tools.