How to get your business data AI-ready
5 essential steps to get your business data AI-ready. Unlock AI's full potential for your business by starting with clean, well-organised data.
5 essential steps to get your business data AI-ready. Unlock AI's full potential for your business by starting with clean, well-organised data.
To get the best AI driven insights from your company data - whether you're using generative AI tools like Caitlyn to answer questions or training predictive models - you need to start with the right foundations. Without clean, well-organised data, AI tools are far more likely to produce poor results and miss valuable opportunities.
The phrase "garbage in, garbage out" perfectly captures the importance of data quality in AI:
As organisations increasingly adopt AI solutions, proper data preparation has become a critical success factor in achieving measurable ROI.
Begin by identifying a specific business problem where AI can provide value:
Example: Foundation for Arable Research (FAR) started with the specific goal of making research findings more accessible to farmers before expanding to broader applications.
Removing inconsistencies and errors is crucial for reliable AI results:
Pro tip: Document your cleaning process so you can replicate it for future datasets.
Different AI applications require different data structures:
Context transforms raw data into valuable insights:
Example: When implementing Caitlyn for agricultural clients, adding a comprehensive glossary of farming terms and regional considerations significantly improved response accuracy.
Leverage specialised tools to streamline your data preparation:
Challenge: Inconsistent data formats across systems.
Solution: Implement standardised data pipelines with clear transformation rules.
Challenge: Incomplete or missing information.
Solution: Use statistical methods to handle missing data or collect additional information.
Challenge: Sensitive or private information.
Solution: Develop clear privacy policies and implement proper data masking or anonymisation.
Challenge: Data silos across departments.
Solution: Create cross-functional data teams and implement unified data platforms.
Implementation is quick and easy. You could be reaping the benefits of AI in just a few weeks.