Update pm.Data related release notes

Author: michaelosthege

RELEASE-NOTES.md

@@ -113,7 +113,10 @@ This includes API changes we did not warn about since at least `3.11.0` (2021-01
   - Added partial dependence plots and individual conditional expectation plots [5091](https://github.com/pymc-devs/pymc3/pull/5091).
   - Modify how particle weights are computed. This improves accuracy of the modeled function (see [5177](https://github.com/pymc-devs/pymc3/pull/5177)).
   - Improve sampling, increase default number of particles [5229](https://github.com/pymc-devs/pymc3/pull/5229).
-- `pm.Data` now passes additional kwargs to `aesara.shared`. [#5098](https://github.com/pymc-devs/pymc/pull/5098)
+- New features for `pm.Data` containers:
+  - With `pm.Data(..., mutable=True/False)`, or by using `pm.MutableData` vs. `pm.ConstantData` one can now create `TensorConstant` data variables. They can be more performant and compatible in situtations where a variable doesn't need to be changed via `pm.set_data()`. See [#5295](https://github.com/pymc-devs/pymc/pull/5295).
+  - New named dimensions can be introduced to the model via `pm.Data(..., dims=...)`. For mutable data variables (see above) the lengths of these dimensions are symbolic, so they can be re-sized via `pm.set_data()`.
+  - `pm.Data` now passes additional kwargs to `aesara.shared`/`at.as_tensor`. [#5098](https://github.com/pymc-devs/pymc/pull/5098).
 - ...