Artificial Intelligence (AI) is experiencing tremendous growth and is projected to reach a market size of $190 billion by 2025, with a CAGR (Compound Annual Growth Rate) of over 36% from 2021 to 2025.
However,
A staggering 85% of AI projects fail due to poor data quality or insufficient relevant data.
This all depends on one key element: DATA QUALITY.
Without a solid data foundation, even the smartest AI can’t deliver accurate results. So, make every data point count for AI excellence!
Various industries and businesses of all verticals are adopting AI at lightning speed.
Here are
the impressive growth statistics.
Various industries and businesses of all verticals are adopting AI at lightning speed.
35% of Retail Sectors implementing AI to improve customer experience, optimize inventory, and forecast demand and trends.
45% of Small and Medium Enterprises (SMEs) implementing AI tools for customer service, marketing, and supply chain management.
More than 50% of Financial Institutions deployed AI for personalized banking, risk assessment, and fraud detection.
30% of Manufacturing Industries utilizing AI for process optimization, quality control, and predictive maintenance.
More than 40% of Healthcare Industries incorporated AI for personalized medicine, diagnostics, and drug discovery.
AI relies heavily on data to function effectively. At its core, AI algorithms are designed to recognize patterns, make predictions, and make decisions based on the information provided to them.
So, high-quality data is not just a technical requirement. It’s the backbone of AI’s ability to deliver accuracy, efficiency, and ethical performance.
Imagine AI as a student. Without good study materials (data), it can’t learn or perform well. The more accurate the data, the better the AI’s ability to predict, decide, and innovate.
When these 6 key data quality dimensions align, they create a seamless flow of high-quality data, enabling AI to make reliable decisions and drive innovation.
AI uses data as its fuel to learn, make decisions, and provide valuable insights. The better the quality of the data, the more accurate and reliable the AI's predictions and decisions will be.
AI systems collect data from various sources (such as databases, cloud storage, APIs, sensors, websites, and social media) that can be structured, unstructured, and semi-structured.
Raw data contains duplicates, inconsistencies, or missing values. Before feeding this raw data to an AI model, it should be cleansed, harmonized, and transformed. This step includes removing duplicates, correcting errors, and handling missing values.
Once the data is cleansed, it is used to train AI models. During training, the AI system analyzes the data and learns to identify patterns, trends, and correlations.
The AI learns from historical data and builds a model that can predict outcomes based on new data inputs. The model is adjusted through repeated testing and learning, enabling its ability to make accurate predictions and decisions.
AI systems can predict customer behaviour, detect fraud, or recommend products based on historical data.
The AI model continues to learn and improve over time as more data is collected and fed. This ongoing learning allows the system to adapt to changes and become more accurate in its predictions or decisions.
We don t just manage data, we manage the future of your business.
Don’t let poor data quality hold your business back. Optimize data quality throughout its entire lifecycle with our Intelligence Data Quality Management (iDQM) solution which incorporates robust data governance frameworks that ensure your data is accurate, consistent, up-to-date, actionable, and ready to fuel your AI implementation with confidence.
Lean Data Governance (LDG) ensures data quality by enforcing robust governance principles at every stage. By applying lean principles—simple, swift, and agile—LDG keeps your data clean, compliant, and ready for AI. It ensures data is accurate, complete, and accessible, empowering AI models to deliver optimal performance. Through continuous monitoring and data quality improvement, LDG guarantees AI initiatives are based on trustworthy, actionable data.
AI Lens, the copilot of Lean Data Governance and iMirAI, the copilot in Data Migration solutions, drive AI success by making data more accessible, actionable, and aligned with the demands of AI models. These tools ensure your data is not only of the highest quality but also continuously improving, providing the perfect foundation for AI-driven innovation.
We go beyond technology by offering specialized strategic advisory services to enhance your data and AI capabilities. Our services include:
We assess your data management practices to provide actionable insights that improve data quality, governance, and operational efficiency.
We evaluate your organizations infrastructure, processes, and data to ensure they are prepared for AI implementation.
We optimize your business processes to align with your data and AI goals, ensuring smoother operations and higher efficiency.
