Data Preparation

As information management professionals, we are front and centre of AI transformation, yet many organisations have overlooked a crucial aspect in the race to take…

Prepare your data to empower AI success. EncompaaS helps you organise and de-risk data, ensuring high-quality AI outcomes.

Revolutionizing pharmaceutical rebate management with AI-powered analytics for faster insights and strategic decision-making.

Join us on Wednesday 21st August at 9:00am AEST for our upcoming webinar on Responsible AI in Information Management.

Our expert panel delve into the critical role of data preparation in navigating the generative AI landscape in our latest webinar.

Jesse Todd (CEO, EncompaaS) and Jaimie Tilbrook (CPO, EncompaaS) delve into the critical challenges companies face in managing their vast data landscapes, emphasizing the importance of understanding what data is, where it is located, its context, and its value.

Data plays a crucial role in Generative AI, being a fundamental component for its success. But poor data quality can lead to biased or discriminatory AI systems, perpetuating biases present in the data. Download our infographic to learn why data quality is the linchpin of successful AI implementation.

In the scramble to take advantage of AI’s transformative capabilities, many organisations have overlooked a crucial aspect. The quality and readiness of their data to adequately fuel AI initiatives.

In this video, we’re going to explore how EncompaaS helps you prepare and organize your data with enriched metadata before analyzing it through user-friendly dashboards to leverage it for AI success.

The journey to AI success starts with preparing your data. But as the amount of structured, unstructured, and semi-structured data continues to grow, preparing your data is a significant challenge without the right tools.

High-quality, trustworthy data fuels game-changing benefits like optimised business intelligence, automated decision-making, personalised customer experiences, and innovative AI and machine learning capabilities. 

As transformative as AI’s impact may be, none of it is possible without first establishing a strong foundation of quality data. The reality is that substandard data quality will invariably lead to substandard AI outcomes.