diff --git a/ibis/backends/dask/__init__.py b/ibis/backends/dask/__init__.py
index 7b058b658b72..80aba0be36ad 100644
--- a/ibis/backends/dask/__init__.py
+++ b/ibis/backends/dask/__init__.py
@@ -14,12 +14,14 @@
 import ibis.expr.operations as ops
 import ibis.expr.schema as sch
 import ibis.expr.types as ir
+from ibis import util
 from ibis.backends.dask.core import execute_and_reset
 from ibis.backends.pandas import BasePandasBackend
 from ibis.backends.pandas.core import _apply_schema
 from ibis.formats.pandas import DaskData
 
 if TYPE_CHECKING:
+    import pathlib
     from collections.abc import Mapping, MutableMapping
 
 # Make sure that the pandas backend options have been loaded
@@ -114,6 +116,62 @@ def compile(
 
         return execute_and_reset(query.op(), params=params, **kwargs)
 
+    def read_csv(
+        self, source: str | pathlib.Path, table_name: str | None = None, **kwargs: Any
+    ):
+        """Register a CSV file as a table in the current session.
+
+        Parameters
+        ----------
+        source
+            The data source. Can be a local or remote file, pathlike objects
+            also accepted.
+        table_name
+            An optional name to use for the created table. This defaults to
+            a generated name.
+        **kwargs
+            Additional keyword arguments passed to Pandas loading function.
+            See https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html
+            for more information.
+
+        Returns
+        -------
+        ir.Table
+            The just-registered table
+        """
+        table_name = table_name or util.gen_name("read_csv")
+        df = dd.read_csv(source, **kwargs)
+        self.dictionary[table_name] = df
+        return self.table(table_name)
+
+    def read_parquet(
+        self, source: str | pathlib.Path, table_name: str | None = None, **kwargs: Any
+    ):
+        """Register a parquet file as a table in the current session.
+
+        Parameters
+        ----------
+        source
+            The data source(s). May be a path to a file, an iterable of files,
+            or directory of parquet files.
+        table_name
+            An optional name to use for the created table. This defaults to
+            a generated name.
+        **kwargs
+            Additional keyword arguments passed to Pandas loading function.
+            See https://pandas.pydata.org/docs/reference/api/pandas.read_parquet.html
+            for more information.
+
+        Returns
+        -------
+        ir.Table
+            The just-registered table
+        """
+        table_name = table_name or util.gen_name("read_parquet")
+        df = dd.read_parquet(source, **kwargs)
+        self.dictionary[table_name] = df
+        return self.table(table_name)
+
     def table(self, name: str, schema: sch.Schema | None = None):
         df = self.dictionary[name]
         schema = schema or self.schemas.get(name, None)
diff --git a/ibis/backends/tests/test_register.py b/ibis/backends/tests/test_register.py
index a17c1e8b572a..5bb03c726894 100644
--- a/ibis/backends/tests/test_register.py
+++ b/ibis/backends/tests/test_register.py
@@ -433,7 +433,6 @@ def ft_data(data_dir):
 @pytest.mark.notyet(
     [
         "bigquery",
-        "dask",
         "impala",
         "mssql",
         "mysql",
@@ -462,7 +461,6 @@ def test_read_parquet_glob(con, tmp_path, ft_data):
 @pytest.mark.notyet(
     [
         "bigquery",
-        "dask",
         "impala",
         "mssql",
         "mysql",