Your customer data can do a lot more for you!

Now you have every customer's entire journey, it's time to empower your store's growth with the data. Attribuly allows you to discover the data with Gemini in Bigquery

About Gemini in BigQuery

Gemini in BigQuery provides AI assistance in the following ways:

Explore and understand your data with data insights.

Data insights offers an automated, intuitive way to uncover patterns, assess data quality, and perform statistical analysis by using insightful queries generated from the metadata of your tables. This feature is especially helpful in addressing the cold-start challenges of early data exploration. For more information, see Generate data insights in BigQuery.

Discover, transform, query, and visualize data in a natural language-based data canvas. (Preview)

Using natural language, you can find, join, and query table assets, visualize results, and seamlessly collaborate with others throughout the entire process. For more information, see Analyze with data canvas.

Get assisted SQL and Python data analysis.

You can use Gemini in BigQuery to generate or suggest code in SQL or Python, and to explain an existing SQL query. You can also use natural language queries to begin data analysis. To learn how to generate, complete, and summarize code, see the following documentation:

Optimize your data infrastructure with partitioning, clustering, and materialized view recommendations.

You can let BigQuery monitor your SQL workloads for opportunities to improve performance and reduce costs. For more information, see the following documentation:

Autotune and troubleshoot serverless Apache Spark workloads. (Preview)

Autotuning can automatically optimize Spark jobs by applying configuration settings to a recurring Spark workload based on best practices and an analysis of prior workload runs. Advanced troubleshooting with Gemini can explain and surface job errors, and it can offer actionable recommendations to fix slow or failed jobs. For more information, see Autotuning Spark workloads and Advanced troubleshooting.

Customize your SQL translations with translation rules. (Preview)

Create Gemini-enhanced translation rules to customize your SQL translations when using the interactive SQL translator. You can describe changes to the SQL translation output using natural language prompts or specify SQL patterns to find and replace. For more information, see Create a translation rule.

Use cases

Personalize sign-up emails. Trigger different product recommendations, based on the user's previous events.
Customer segmentation and targeting.

How it works

Attribuly syncs different customer datasets to BigQuery, so you can analyze and take further actions via Gemini in BigQuery. The BigQuery database is owned by you.

The dataset

The initial dataset includes customer, product, and customer events. The datasets have been process to a standardized structure.
The dataset can be updated in a near real-time frequency, so you can use it to personalize customer experience.

What's next?

Welcome to comment your use cases so we can build them for you. :)

Discussion