Resources and insights

Discover how self-service analytics tools are empowering non-technical users, enabling data access and insights without coding, streamlining decision-making.

Discover 8 effective ways to build data literacy across business and technical teams, breaking down barriers and enhancing collaboration for data-driven success.

Prophecy and Databricks are redefining how teams build and manage data pipelines on Databricks SQL.

Prophecy and data leaders embrace the GenAI moment at Gartner 2025

Prophecy Introduces Fully Governed Data Preparation for Databricks SQL

Data teams and analysts are inadvertently siloed into different parts of their organizations. These are the 5 data dysfunctions that breed this situation.

Explore best practices and modern examples in data pipeline strategy. Learn to boost business success with scalable and reliable data solutions.

Our new survey shows that data leaders are embracing GenAI and bracing for new challenges

Join the Prophecy team in Orlando to see how genAI is reshaping data teams

The clock strikes noon on Shadow IT

Bringing data teams together for the holidays

Accelerating data transformation with AI to deliver insights

Prophecy team was out in force at one of the data world’s biggest events

Explore alternatives to Alteryx for modern data prep. Explore options and how Prophecy delivers scalability and openness to modernize data preparation.

Discover how Prophecy revolutionizes your data operations.

Prophecy attended the CDOIQ Symposium last week in Boston.

Maximize productivity without the complexity.

Databricks held their annual Data+AI Summit in San Francisco last week at Moscone Center.

Prophecy’s booth will be hopping with book signings, Copilots, and the latest on data and AI

How copilots will change data transformation, and in the process evolve beyond conversational interfaces

Prophecy brings championship winning data, critical healthcare data, and AI for data transformation to DAIS 2024

We’ve written before about the challenge of having too few data engineers. There is another problem. 

Inaugural course addresses the growing data engineering skills gap through agile, self-paced training

Johnson & Johnson takes center stage with Prophecy

Struggling with data transformation? Hiring more data engineers is not the answer. Learn how low-code data transformation unlocks the full potential of your users and your data.

Join us in Orlando to witness the future of data transformation

Join our webinar and see why self-service is the future of data transformation, through unified visual & code technology

Join us in this exciting journey and discover how Prophecy's self-service solutions are revolutionizing the data landscape.

With the release of Prophecy 3.2, we are thrilled to announce two game-changing capabilities: Prophecy Package Builder and Prophecy Package Hub.

Discover how to build generative AI applications leveraging enterprise data. Learn to identify use cases, choose effective models, and navigate challenges with our comprehensive guide.

In this blog, we'll take a look at the differences between prompt engineering and fine-tuning, and provide insights into each approach

Companies can train small, domain-specific language models in a matter of hours or days rather than weeks or months provided they have governed and accurate training inputs. 

Stop getting stuck managing SQL files, start making progress for your business today

Everything you need to know to accelerate ETL modernization

Get an exciting recap from Databricks Data + AI summit including Prophecy’s announcements around low-code data engineering and generative AI app development

Build powerful gen AI applications on private enterprise data in just hours

Unlock the power of generative AI in data engineering with Prophecy’s Data Copilot.

Top 10 reasons to visit Prophecy at Data + AI Summit 2023

Empowering business data users to quickly and easily build scalable data pipelines on the lakehouse

By modernizing the ETL process on Databricks, Prophecy can provide organizations with a more agile, scalable, and cost-effective solution for managing their data.

Learn key steps to follow, how to define the ETL pipeline using Spark APIs and dataframes, and best practices for testing and optimizing pipelines for maximum efficiency

Bringing the power of low-code data engineering to the masses

Learn how the Texas Rangers use Prophecy and Databricks Lakehouse as the foundation of their data mesh architecture to gain a competitive advantage with low-code data engineering.

Leverage Prophecy’s low-code approach and integration with dbt Core to build SQL data pipelines without compromising on engineering best practices

Discover how Prophecy 3.0 arms all data users with low-code SQL, so they can quickly and easily build scalable data pipelines, resulting in highly impactful data products.

Learn essential skills and techniques to empower non-technical data practitioners to build ETL pipelines without relying on data engineering.

A rising number of enterprises are adopting the lakehouse to unite their analytics projects and foster innovation on a shared, cloud-based platform.

Join this webinar to learn how the Texas Rangers are creating a competitive advantage in professional baseball by using data analytics and AI to improve player performance and evaluate new talent.

Let's create a pipeline using Prophecy's visual, low-code interface for Spark.

Let's get started with PySpark using a visual interface to generate open-source Spark code.

In Part 1, we learned an easy way to troubleshoot a data pipeline using historical, read-only metadata. Now, I want to dig in and polish my individual spark data frames.

Let’s take advantage of Spark’s interim metadata to understand our Spark job behavior with low-code tooling.

For enterprises, navigating the cloud transition can be tricky. This describes the two paradigms for ETL in the cloud, and the factors to consider when choosing one.