Find key insights with contribution analysis in BigQuery ML
With growing volumes of data, it becomes increasingly difficult for organizations to understand why their data changes. Organizations struggle to identify the root cause of critical trends and fluctuations, hindering their ability to make informed decisions. For example, a company might be left wondering, “What…
The modern marketer’s strategic advantage: AI-powered data clean rooms
Businesses across all industries crave data to better understand their customers and drive sales. Imagine a major consumer packaged goods brand that primarily sells through a large retailer. This brand could gain valuable insights by understanding the key actions / high-value assets (HVAs) customers take…
BigQuery’s AI-assisted data preparation is now in preview
In today’s data-driven world, the ability to efficiently transform raw data into actionable insights is paramount. However, data preparation and cleaning is often a significant challenge. According to Gartner®1 “Gartner clients now report that 90% or more of their time is spent preparing data (as high…
Building a real-time analytics platform using BigQuery and Bigtable
When developing a real-time architecture, there are two fundamental questions that you need to ask yourself in order to make the right technology choice: Freshness – how fast does the data need to be available? Query latency – how fast do you need to be…
How to integrate Gemini and Sheets with BigQuery
I often find myself in Google Sheets. Some would say too often. Since I use Gemini for all kinds of things too, integrating Gemini into my Sheets workflow just makes sense. I can boost my productivity in Sheets with capabilities like summarizing sheets and creating formulas. Gemini is now…
Build your own generative AI chatbot directly from BigQuery
Organizations today have access to a wealth of data, including customer information, financial records, operational logs, and more, which they aim to leverage for building new generative AI solutions. However, they face a number of challenges: Building and training LLMs requires significant technical expertise and…
Hands on with Gemini models in BigQuery: Decoding sentiment in customer reviews
Sentiment analysis is a powerful tool that uses natural language processing (NLP) to uncover the underlying emotions (positive, negative, neutral) within text such as customer reviews. This analysis can offer valuable insight into how customers perceive your products, services, and brand overall. Furthermore, by utilizing…
Creating marketing campaigns using BigQuery and Gemini models
Creating marketing campaigns is often a complex and time-consuming process. Businesses aim to create real-time campaigns that are highly relevant to customer needs and personalized to maximize sales. Doing so requires real-time data analysis, segmentation, and the ability to rapidly create and execute campaigns. Achieving…
Introducing new ML model monitoring capabilities in BigQuery
Monitoring machine learning (ML) models in production is now as simple as using a function in BigQuery! Today Google introducing a new set of functions that enable model monitoring directly within BigQuery. Now, you can describe data throughout the model workflow by profiling training or…
Introducing multimodal and structured data embedding support in BigQuery
Embeddings represent real-world objects, like entities, text, images, or videos as an array of numbers (a.k.a vectors) that machine learning models can easily process. Embeddings are the building blocks of many ML applications such as semantic search, recommendations, clustering, outlier detection, named entity extraction, and…
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Recent Posts
- Find key insights with contribution analysis in BigQuery ML
- Secure your data ecosystem: a multi-layered approach with Google Cloud
- Gemini for Google Workspace now supports additional languages
- 5 ways small business owners can use Gemini for Workspace to plan for the holiday season and New Year
- Vertex AI grounding: More reliable models, fewer hallucinations
Recent Posts
- Find key insights with contribution analysis in BigQuery ML
- Secure your data ecosystem: a multi-layered approach with Google Cloud
- Gemini for Google Workspace now supports additional languages
- 5 ways small business owners can use Gemini for Workspace to plan for the holiday season and New Year
- Vertex AI grounding: More reliable models, fewer hallucinations
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