Say goodbye to constant “One-Offs” and hello to “Set It and Forget It”

Our customers share why they chose Fivetran to replicate their database data and how their analytics have improved as a result.

Deploying trained models takes models from the lab to live environments and ensures they meet business requirements and drive value. Model deployment can bring great value to organizations, but it is not a simple process, as it involves many phases, stakeholders and different technologies. In this article, we provide recommendations for data professionals who want to improve and streamline their model deployment process.

As we hurtle into a more connected and data-centric future, monitoring the health of our data pipelines and systems is becoming increasingly harder. These days we are managing more data and systems than ever before, and we are monitoring them at a higher scale.

The future of data integration is no-code data integration platforms, and we have the research to prove it.

Lost in the talk about OpenAI is the tremendous amount of compute needed to train and fine-tune LLMs, like GPT, and Generative AI, like ChatGPT. Each iteration requires more compute and the limitation imposed by Moore’s Law quickly moves that task from single compute instances to distributed compute. To accomplish this, OpenAI has employed Ray to power the distributed compute platform to train each release of the GPT models.

In today's data-driven world, product analytics is crucial in understanding user behavior, improving product features, and driving business growth. However, product analytics alone may not provide a complete picture of user interactions and business performance. Integrating product analytics with other data sources and systems is essential to gain deeper insights and make more informed decisions.

When it comes to choosing a business intelligence (BI) solution vendor for your business, there are a variety of factors to consider. One important area of comparison is the natural language query (NLQ) features offered by different BI vendors. NLQ is increasingly becoming a key capability of the modern self-service analytics experience, as it allows users to ask complex questions of their data, and receive insightful answers in the form of a pre-generated, best practice data visualizations.

Practical advice for starting your journey to analytics excellence.