Best practices

General data preparation

To get the most accurate and useful answers from Kaiya, it's important to prepare your data correctly. This means keeping your datasets clean, naming things clearly, and using the right types of fields.

• Try to keep datasets under 50 columns. Kaiya works better with fewer, more relevant columns. Remove columns that are rarely used or not helpful for analysis.

• Avoid confusing names. If you have both “Product Line” and “Product Type”, Kaiya might not know which one to use if you use "Product" in your search query.

• If there are metrics that users will frequently ask about (like conversion rate, profit margin), add those as calculated columns up front.

• Make sure your data joins neatly. Dimensions and facts should match in granularity to prevent duplicate rows or wrong totals.

• Use full, readable names like Policy Creation Date instead of plc_date.

• Use underscores or spaces — not symbols like brackets, slashes, or emojis.

• Avoid using vague words like “growth” or “total” as column names.

Why?

Kaiya tries to interpret the meaning behind words. If your column is named “Sales Growth” and you ask “What is sales growth?”, Kaiya may return the column instead of calculating growth over time.

• You can teach Kaiya your business language. Use Synonyms to map your company’s terms to the actual columns in your dataset.

• Avoid overlapping synonyms. If two fields share similar terms (like “Expenses” for both “Costs” and “Material Expenses”), Kaiya might get confused.

• Use only essential date columns. Name them clearly and ensure they're in Date format, not Text. Kaiya uses these fields to answer questions like “last month’s revenue” or “YoY growth.”

• Index these:

  • Common filter fields like Region, Product, Drug Name, Channel

  • Fields with few values (low-cardinality) like Segment or Product Category

• Don’t index:

  • Long text or free-text fields like Comments or Descriptions

  • Columns that overlap in meaning (e.g., “Washington” in both City and State)

Kaiya uses indexed fields for auto-suggestions when filtering and selecting values.

Use Kaiya’s clarification prompts when it asks follow-up questions to clear up confusion in your original query.

Use Learnings to teach Kaiya your specific data language over time.

How to ask better questions

By following these best practices, you’ll help Kaiya understand your questions more accurately and return better answers.

• Be specific. Include filters or timeframes.

• Don’t be vague. Instead of “How are things going in the East?”, use “Sales trend in East region over last 6 months”.

• Don’t overload. Break big questions into smaller parts.

• Instead of a casual question“Did people like our service?” → use “Customer satisfaction score in 2024”.

• If Kaiya doesn’t understand your question, rephrase it to be simpler or more specific.

• To ask about change or trends, use this format:

  • “% change in Sales from Jan 2024 to Feb 2024”

  • “What is the change in Revenue this quarter vs last quarter?”

• To start a new topic in the same chat, say “Ignore previous context” or click on the "Clear context" icon to clear conversation history.

• It's better to use new chats for new Business Views. Don’t switch BVs mid-conversation.