diff --git a/tensorflow/python/data/ops/dataset_ops.py b/tensorflow/python/data/ops/dataset_ops.py
index 572be83e20a..b23df3672c9 100644
--- a/tensorflow/python/data/ops/dataset_ops.py
+++ b/tensorflow/python/data/ops/dataset_ops.py
@@ -2103,15 +2103,40 @@ class DatasetV1(DatasetV2):
     raise NotImplementedError("Dataset._as_variant_tensor")
 
   @deprecation.deprecated(
-      None, "Use `for ... in dataset:` to iterate over a dataset. If using "
-      "`tf.estimator`, return the `Dataset` object directly from your input "
-      "function. As a last resort, you can use "
-      "`tf.compat.v1.data.make_one_shot_iterator(dataset)`.")
+      None, "This is a deprecated API that should only be used in TF 1 graph "
+      "mode and legacy TF 2 graph mode available through `tf.compat.v1`. In "
+      "all other situations -- namely, eager mode and inside `tf.function` -- "
+      "you can consume dataset elements using `for elem in dataset: ...` or "
+      "by explicitly creating iterator via `iterator = iter(dataset)` and "
+      "fetching its elements via `values = next(iterator)`. Furthermore, "
+      "this API is not available in TF 2. During the transition from TF 1 "
+      "to TF 2 you can use `tf.compat.v1.data.make_one_shot_iterator(dataset)` "
+      "to create a TF 1 graph mode style iterator for a dataset created "
+      "through TF 2 APIs. Note that this should be a transient state of your "
+      "code base as there are in general no guarantees about the "
+      "interoperability of TF 1 and TF 2 code.")
   def make_one_shot_iterator(self):
     """Creates an `Iterator` for enumerating the elements of this dataset.
 
     Note: The returned iterator will be initialized automatically.
-    A "one-shot" iterator does not currently support re-initialization.
+    A "one-shot" iterator does not currently support re-initialization. For
+    that see `make_initializable_iterator`.
+
+    Example:
+
+    ```python
+    # Building graph ...
+    dataset = ...
+    next_value = dataset.make_one_shot_iterator().get_next()
+
+    # ... from within a session ...
+    try:
+      while True:
+        value = sess.run(next_value)
+        ...
+    except tf.errors.OutOfRangeError:
+        pass
+    ```
 
     Returns:
       An `Iterator` over the elements of this dataset.
@@ -2170,10 +2195,19 @@ class DatasetV1(DatasetV2):
         get_legacy_output_classes(self))
 
   @deprecation.deprecated(
-      None, "Use `for ... in dataset:` to iterate over a dataset. If using "
-      "`tf.estimator`, return the `Dataset` object directly from your input "
-      "function. As a last resort, you can use "
-      "`tf.compat.v1.data.make_initializable_iterator(dataset)`.")
+      None, "This is a deprecated API that should only be used in TF 1 graph "
+      "mode and legacy TF 2 graph mode available through `tf.compat.v1`. "
+      "In all other situations -- namely, eager mode and inside `tf.function` "
+      "-- you can consume dataset elements using `for elem in dataset: ...` "
+      "or by explicitly creating iterator via `iterator = iter(dataset)` "
+      "and fetching its elements via `values = next(iterator)`. "
+      "Furthermore, this API is not available in TF 2. During the transition "
+      "from TF 1 to TF 2 you can use "
+      "`tf.compat.v1.data.make_initializable_iterator(dataset)` to create a TF "
+      "1 graph mode style iterator for a dataset created through TF 2 APIs. "
+      "Note that this should be a transient state of your code base as there "
+      "are in general no guarantees about the interoperability of TF 1 and TF "
+      "2 code.")
   def make_initializable_iterator(self, shared_name=None):
     """Creates an `Iterator` for enumerating the elements of this dataset.
 
@@ -2181,10 +2215,19 @@ class DatasetV1(DatasetV2):
     and you must run the `iterator.initializer` operation before using it:
 
     ```python
+    # Building graph ...
     dataset = ...
     iterator = dataset.make_initializable_iterator()
-    # ...
+    next_value = iterator.get_next()  # This is a Tensor.
+
+    # ... from within a session ...
     sess.run(iterator.initializer)
+    try:
+      while True:
+        value = sess.run(next_value)
+        ...
+    except tf.errors.OutOfRangeError:
+        pass
     ```
 
     Args:
@@ -2198,7 +2241,6 @@ class DatasetV1(DatasetV2):
     Raises:
       RuntimeError: If eager execution is enabled.
     """
-
     return self._make_initializable_iterator(shared_name)
 
   def _make_initializable_iterator(self, shared_name=None):  # pylint: disable=missing-docstring