# Data Shaper and Apache Hop **Data Shaper** is built on **Apache Hop**, the open-source data orchestration and transformation framework. Within the **Data One** suite, this foundation enables a consistent and unified environment for designing, executing, and monitoring data transformations.\ Data Shaper is fully integrated with other **Data One** modules: transformations can be invoked in **Data Mover** mediation contracts and monitored as part of **Data Watcher** dataflows. ### Hop Visual Design and Metadata Apache Hop, short for **H**op **O**rchestration **P**latform, is a data orchestration and data engineering platform that aims to facilitate all aspects of data and metadata orchestration. Hop lets you focus on the problem you’re trying to solve without technology getting in the way. Simple tasks should be easy, complex tasks need to be possible. Hop allows data professionals to work **visually**, using **metadata** to describe how data should be processed. Visual design enables data developers to focus on **what** they want to do instead of **how** that task needs to be done. This focus on the task at hand lets Hop developers be more productive than they would be when writing code. ### Hop Flexible Runtimes Hop developers create **workflows** and **pipelines** in a visual development environment called Hop Gui. These workflows and pipelines can be executed on a variety of engines: workflows and pipelines can run on the native Hop engine, both locally and remotely. Pipelines can also run on Apache Spark, Apache Flink and Google Dataflow through the Apache Beam runtime configurations. In workflows and pipelines, hundreds of operations can be applied on the data: read from and write to a variety of source and target platforms, but also combine, enrich, clean and in many other ways manipulate data. Depending on the engine and selected functionality, your data can be processed in batch, streaming or in a batch/streaming hybrid. ### Hop Core Concepts Before we dive deeper, let’s take a minute to familiarize ourselves with the Hop lingo. **Metadata** is by far the most important concept in all of Hop. Every item we’ll cover below is defined as metadata. All interactions between Hop and other components in your data architecture are done through metadata. *Metadata is at the core of **everything** in Hop*. * **Pipelines** are collections of **transforms**, connected by **hops**. All transforms in a pipeline run in parallel. * **Workflows** are collections of **actions**, connected by **hops**. All actions in a workflow run sequentially by default. * **Projects** are logical collections of hop code and configuration. **Environments** contain the environment-specific (e.g. dev, uat, prd) metadata. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.primeur.com/data-shaper-1.20/getting-started/data-shaper-and-apache-hop.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.