Add Hyper-Datasets

docs/hyperdatasets/overview.md

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+---
+title: Hyper Datasets
+---
+
+ClearML's Hyper Datasets are an MLOps-oriented abstraction of your data, which facilitates traceable, reproducible model development
+through parametrized data access and meta-data version control.
+
+The basic premise is that a user-formed query is a full representation of the dataset used by the ML/DL process. 
+
+ClearML Enterprise's hyperdatasets supports rapid prototyping, creating new opportunities such as: 
+* Hyperparameter optimization of the data itself
+* QA/QC pipelining
+* CD/CT (continuous training) during deployment
+* Enabling complex applications like collaborative (federated) learning. 
+
+
+## Hyperdataset Components 
+
+A hyperdataset is composed of the following components:
+
+* [Frames](frames.md)
+    * [SingleFrames](single_frames.md) 
+    * [FrameGroups](frame_groups.md)
+* [Datasets and Dataset Versions](dataset.md)
+* [Dataviews](dataviews.md)
+
+These components interact in a way that enables revising data and tracking and accessing all of its version. 
+
+Frames are the basics units of data in ClearML Enterprise. SingleFrames and FrameGroups make up a Dataset version. 
+Dataset versions can be created, modified, and removed. The different version are recorded and available, 
+so experiments and their data are reproducible and traceable. 
+
+Lastly, Dataviews manage views of the dataset with queries, so the input data to an experiment can be defined from a 
+subset of a Dataset or combinations of Datasets.