AI-ready data platforms can help enterprises reduce manual work, improve forecasting: Report

New Delhi [India], July 14 (ANI): Building AI-ready data platforms can help enterprises reduce manual work, improve forecasting accuracy and enable faster business decisions by bringing together data from multiple business functions into a single trusted system, according to a report by Sonata Software.
The report said many organisations continue to struggle with fragmented data spread across sales, finance, delivery and human resources systems, forcing employees to spend significant time manually reconciling information. Such disconnected systems often lead to delays in decision-making and reduce confidence in revenue and margin forecasts.
According to the report, enterprises can overcome these challenges by creating a unified, AI-ready data foundation that provides a single source of trusted information across departments. This enables business leaders to access near-real-time insights and make quicker decisions.
It stated, "Building a unified AI-ready data foundation on Microsoft Fabric and OneLake, Sonata layered in Copilot and Fabric data agents so every team can query trusted, near real-time data in natural language and get answers in seconds".
Sharing its own experience, Sonata Software said it modernised the way data from delivery, sales and finance systems came together by building a unified AI-ready data platform on Microsoft Fabric and OneLake.
The company also integrated AI-powered Copilot and Fabric data agents to allow employees to access business information through natural language queries.
The report said the initiative helped reduce reconciliation effort by 25-30 per cent, while enabling teams to act on business data 30-40 per cent faster.
It added that automated data pipelines continuously brought information from different business systems into a single platform, replacing outdated data snapshots with near real-time information. Semantic models also helped standardise business calculations, making them more consistent and auditable.
According to the report, the company estimated that around 200 hours of manual effort are saved every month in reconciliation activities. The time saved has been redirected towards forecasting, sales growth and other higher-value work.
The report noted the use of domain-specific AI agents for finance, operations and delivery allows employees to ask business-related questions in plain language and receive answers within seconds without waiting for reports or analyst support.
According to the report, the unified data platform has also improved visibility into revenue forecasting, sales pipelines, employee utilisation and project delivery performance. Leadership teams now have access to near real-time business information, enabling quicker responses to changing business conditions.
The report further said that for a publicly listed company, accurate forecasting is critical as missed revenue and margin guidance can affect market credibility.
The report emphasised that building trusted, AI-ready data foundations can help enterprises improve business predictability, strengthen decision-making and support future growth. (ANI)