diff --git a/README.rst b/README.rst index 6e2d7c7161..cf6d9eca45 100644 --- a/README.rst +++ b/README.rst @@ -38,23 +38,21 @@ How DVC works We encourage you to read our `Get Started <https://dvc.org/doc/get-started>`_ guide to better understand what DVC is and how it can fit your scenarios. -The easiest (but not perfect!) *analogy* to describe it: DVC is Git (or Git-LFS to be precise) & Makefiles -made right and tailored specifically for ML and Data Science scenarios. +The easiest (but not perfect!) *analogy* to describe it: DVC is Git for data & Makefiles tailored specifically for ML and Data Science scenarios. -#. ``Git/Git-LFS`` part - DVC helps store and share data artifacts and models, connecting them with a Git repository. -#. ``Makefile``\ s part - DVC describes how one data or model artifact was built from other data and code. +#. **Git** part - DVC helps store and share data artifacts (like Git-LFS but without a server) and models, connecting them with a Git repository. +#. **Make** part - DVC describes how data or model artifacts are built from other data and code -- a data pipeline. -DVC usually runs along with Git. Git is used as usual to store and version code (including DVC meta-files). DVC helps -to store data and model files seamlessly out of Git, while preserving almost the same user experience as if they -were stored in Git itself. To store and share the data cache, DVC supports multiple remotes - any cloud (S3, Azure, -Google Cloud, etc) or any on-premise network storage (via SSH, for example). +DVC usually works on top of Git. +Git is used as usual to store and version code (including DVC meta-files). +DVC helps to store data and model files seamlessly out of Git, while preserving almost the same user experience as if they were stored in Git itself. + +To store and share the *data cache*, DVC supports multiple remotes - any cloud (S3, Azure, Google Cloud, etc.) or on-premise network storage (via SSH, for example). |Flowchart| -The DVC pipelines (computational graph) feature connects code and data together. It is possible to explicitly -specify all steps required to produce a model: input dependencies including data, commands to run, -and output information to be saved. See the quick start sections below or -the `Get Started <https://dvc.org/doc/get-started>`_ tutorial to learn more. +DVC pipelines (computational graphs) connect code and data together. +They specify all steps required to produce a model: input dependencies including code, data, commands to run; and output information to be saved. Quick start ===========