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The Agentsql blog.
Plain-language guides to AI data analysts, text-to-SQL, chatting with your database, and getting answers without writing a line of SQL, from the team building the tool.
BigQuery COALESCE: How to Handle NULLs and Set Defaults
COALESCE returns the first value in a list that is not NULL, which is how you set defaults and merge fallback columns in BigQuery. Here are the patterns and the traps.
BigQuery STRING_AGG: How to Combine Grouped Rows Into One String
STRING_AGG concatenates the values from many rows into a single delimited string, one per group. Here is the syntax, ordering, DISTINCT, and the ARRAY_AGG comparison.
BigQuery CASE WHEN: How to Write Conditional Logic in SQL
CASE WHEN is how you write if-then logic in BigQuery SQL: label rows, bucket values, and count conditionally. Here is the syntax and the patterns people use most.
BigQuery PIVOT: How to Turn Rows Into Columns
PIVOT turns row values into columns in BigQuery so a category becomes a set of headers. Here is the syntax, the multiple-column pattern, and the dynamic-columns catch.
BigQuery Date Functions: Format, Add, Subtract, and Group by Date
The BigQuery date functions you actually use: format a date, add and subtract days, measure the gap between two dates, and group a trend by day, week or month.
BigQuery REGEXP_CONTAINS: How to Match Text with Regular Expressions
REGEXP_CONTAINS is how you filter rows by a text pattern in BigQuery when a plain LIKE is not enough. Here is the syntax, the patterns people use most, and the gotchas.
BigQuery ARRAY_AGG: How to Group Values into Arrays
ARRAY_AGG rolls the values in a group into a single array, which is how you build one row per customer, keep the latest value, or pack rich data into a column. Here is how.
BigQuery QUALIFY: How to Filter on Window Functions
QUALIFY is to window functions what WHERE is to columns. It deduplicates rows and picks the top N per group in one clean statement, with no subquery. Here is how to use it.
How Accurate Is Text-to-SQL, Really? What the Benchmarks and Real Use Show in 2026
The honest answer to how accurate text-to-SQL is depends less on the model and more on your schema, your question and whether you can see the SQL. Here is the real picture.
Looker Studio vs Looker: The Difference, the Price Gap, and Which One You Actually Need
They share a name and almost nothing else. One is free and aimed at marketers, the other costs six figures a year. Mixing them up is the most expensive mistake in analytics budgeting.
How to Query BigQuery Without Writing SQL: Plain-English Analysis in 2026
You do not have to learn BigQuery Standard SQL to get answers out of it. Here is how plain-English querying works, what it costs, and how to keep it accurate and cheap.
How Much Does Looker Cost? Real Pricing and the Looker Studio Difference in 2026
Google does not list a Looker price anywhere, and the number people quote for Looker Studio is for a completely different product. Here is what the enterprise platform actually costs.
What Is a Semantic Layer, and Do You Actually Need One?
It is the thing that stops three teams walking into a meeting with three different revenue numbers. It is also easy to buy before you need it.
How Much Does Power BI Cost? Real Pricing for a Small Business in 2026
The licence is $14 a seat. The honest answer to what Power BI costs is bigger than that, and the part nobody quotes you is the one that hurts.
Is Power BI Hard to Learn? What It Actually Takes to Get Productive
The first chart takes an afternoon. Then you meet DAX, and the Excel intuition that got you this far stops helping entirely.
Read Replica vs Production Database: Where Should Analytics Queries Run?
A replica protects the database your customers depend on, at the cost of a few seconds of lag. Here is when that trade is worth making, and when pointing at production is genuinely fine.
Do You Need a Data Warehouse to Use an AI Data Analyst?
A warehouse solves two specific problems: scale and scattered data. If you have neither, an AI data analyst can point at the database you already run today.
BigQuery Cost Control: How to Let People Ask Questions Without a Surprise Bill
BigQuery charges for bytes scanned, so SELECT * on an unpartitioned table costs the same whether you wanted 10 rows or a million. Here are the controls that actually cap it.
Is It Safe to Give an AI Access to Your Production Database?
The risk is not the AI writing a bad query, it is the credentials you hand it. Here is what a read-only, least-privilege connection actually prevents, and the checklist to set one up.
Text-to-SQL vs BI Dashboards: Which Does Your Team Actually Need?
Dashboards and text-to-SQL solve two different problems. One serves the metrics you watch every week; the other answers the question nobody built a report for yet. Here is how to tell which you need.
Can ChatGPT Query My Database? What Actually Works in 2026
Plain ChatGPT has no live connection to your production database, so here are the four real options, what each one can actually see, and which are safe to point at production.
Snowflake natural language query: how business users ask Snowflake questions in plain English
A practical guide to querying Snowflake in plain English: how text-to-SQL works, the least-privilege role to create, what it costs in credits, and where accuracy breaks down.
AI data analyst cost: what teams actually pay in 2026
A straight breakdown of what AI data analyst tools cost, how the pricing models differ, and how the total bill compares to hiring a human analyst.
Best AI SQL Tools in 2026
A practical buyer guide to the best AI SQL tools in 2026, grouped by what they actually do, so you can pick the right category for your team.
How to Query a Database Without Knowing SQL
You do not need to learn SQL to get answers from your database. Here is how to ask in plain English and get a trustworthy result back.
Natural Language to SQL, Explained
A clear, technical walk through how natural language to SQL actually works, from schema grounding to running the query read-only.
AI Data Analyst vs Human Analyst
An honest comparison of AI data analysts and human analysts, where each one wins, and how the best teams use them together.
Text-to-SQL Accuracy and How to Trust Generated SQL
How to trust AI-generated SQL: show the query, verify it, ground it in your schema, and refine until the number is right.
How to Connect AI to Your Database Safely
The safe way to connect an AI tool to your database: read-only, least privilege, never trained on, encrypted, and revocable.
Self-Serve Analytics for Startups
How startups can give the whole team self-serve answers from their data, without hiring an analyst or rolling out a heavy BI stack.
Business Questions to Ask Your Data
A practical list of plain-English business questions to ask your data, and the kind of charted answer an AI data analyst returns for each.
BigQuery Standard SQL vs Legacy SQL: What Is the Difference and Which Should You Use?
BigQuery has two SQL dialects, and one of them is quietly deprecated. Here is the practical difference between Standard SQL and Legacy SQL, and why every new query should use Standard.
BigQuery LIKE ANY: How to Match a Column Against a List of Patterns
BigQuery LIKE ANY lets you test a column against a whole list of patterns in one clean expression instead of a pile of OR conditions. Here is the syntax and when to reach for it.
How to Give Your Team Self-Serve Access to BigQuery Without Losing Control
Opening BigQuery to the whole team sounds risky: runaway costs, accidental damage, people who cannot write SQL. Here is how to give safe, self-serve access without any of that.
BigQuery Window Functions: How to Rank, Run Totals, and Compare Rows
Window functions let you rank rows, run cumulative totals, and compare each row to its group without a GROUP BY that collapses the detail. Here is the syntax and the patterns.
BigQuery Partitioned Tables: How PARTITION BY Cuts Query Cost
Partitioning a BigQuery table by date or integer means a filtered query scans one segment instead of the whole table, which cuts cost and speeds up results. Here is how to set it up.
BigQuery TIMESTAMP vs DATETIME: The Difference and When to Use Each
The difference is time zones: TIMESTAMP is an absolute moment stored in UTC, DATETIME is a wall-clock reading with no zone. Picking the wrong one causes off-by-hours bugs.