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diff --git a/src/mlia/devices/ethosu/data_collection.py b/src/mlia/devices/ethosu/data_collection.py
new file mode 100644
index 0000000..291f1b8
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+++ b/src/mlia/devices/ethosu/data_collection.py
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+# SPDX-FileCopyrightText: Copyright 2022, Arm Limited and/or its affiliates.
+# SPDX-License-Identifier: Apache-2.0
+"""Data collection module for Ethos-U."""
+import logging
+from pathlib import Path
+from typing import List
+from typing import Optional
+
+from mlia.core.context import Context
+from mlia.core.data_collection import ContextAwareDataCollector
+from mlia.core.errors import FunctionalityNotSupportedError
+from mlia.core.performance import estimate_performance
+from mlia.devices.ethosu.config import EthosUConfiguration
+from mlia.devices.ethosu.performance import EthosUPerformanceEstimator
+from mlia.devices.ethosu.performance import OptimizationPerformanceMetrics
+from mlia.devices.ethosu.performance import PerformanceMetrics
+from mlia.nn.tensorflow.config import get_keras_model
+from mlia.nn.tensorflow.config import get_tflite_model
+from mlia.nn.tensorflow.config import KerasModel
+from mlia.nn.tensorflow.optimizations.select import get_optimizer
+from mlia.nn.tensorflow.optimizations.select import OptimizationSettings
+from mlia.nn.tensorflow.utils import save_keras_model
+from mlia.tools.vela_wrapper import Operators
+from mlia.tools.vela_wrapper import supported_operators
+from mlia.utils.types import is_list_of
+
+logger = logging.getLogger(__name__)
+
+
+class EthosUOperatorCompatibility(ContextAwareDataCollector):
+    """Collect operator compatibility information."""
+
+    def __init__(self, model: Path, device: EthosUConfiguration) -> None:
+        """Init operator compatibility data collector."""
+        self.model = model
+        self.device = device
+
+    def collect_data(self) -> Operators:
+        """Collect operator compatibility information."""
+        tflite_model = get_tflite_model(self.model, self.context)
+
+        logger.info("Checking operator compatibility ...")
+        ops = supported_operators(
+            Path(tflite_model.model_path), self.device.compiler_options
+        )
+        logger.info("Done\n")
+        return ops
+
+    @classmethod
+    def name(cls) -> str:
+        """Return name of the collector."""
+        return "ethos_u_operator_compatibility"
+
+
+class EthosUPerformance(ContextAwareDataCollector):
+    """Collect performance metrics."""
+
+    def __init__(
+        self,
+        model: Path,
+        device: EthosUConfiguration,
+        backends: Optional[List[str]] = None,
+    ) -> None:
+        """Init performance data collector."""
+        self.model = model
+        self.device = device
+        self.backends = backends
+
+    def collect_data(self) -> PerformanceMetrics:
+        """Collect model performance metrics."""
+        tflite_model = get_tflite_model(self.model, self.context)
+        estimator = EthosUPerformanceEstimator(
+            self.context,
+            self.device,
+            self.backends,
+        )
+
+        return estimator.estimate(tflite_model)
+
+    @classmethod
+    def name(cls) -> str:
+        """Return name of the collector."""
+        return "ethos_u_performance"
+
+
+class OptimizeModel:
+    """Helper class for model optimization."""
+
+    def __init__(
+        self, context: Context, opt_settings: List[OptimizationSettings]
+    ) -> None:
+        """Init helper."""
+        self.context = context
+        self.opt_settings = opt_settings
+
+    def __call__(self, keras_model: KerasModel) -> KerasModel:
+        """Run optimization."""
+        optimizer = get_optimizer(keras_model, self.opt_settings)
+
+        opts_as_str = ", ".join(str(opt) for opt in self.opt_settings)
+        logger.info("Applying model optimizations - [%s]", opts_as_str)
+        optimizer.apply_optimization()
+
+        model = optimizer.get_model()
+        model_path = self.context.get_model_path("optimized_model.h5")
+        save_keras_model(model, model_path)
+
+        return KerasModel(model_path)
+
+
+class EthosUOptimizationPerformance(ContextAwareDataCollector):
+    """Collect performance metrics for the optimizations."""
+
+    def __init__(
+        self,
+        model: Path,
+        device: EthosUConfiguration,
+        optimizations: List[List[dict]],
+        backends: Optional[List[str]] = None,
+    ) -> None:
+        """Init performance optimizations data collector."""
+        self.model = model
+        self.device = device
+        self.optimizations = optimizations
+        self.backends = backends
+
+    def collect_data(self) -> Optional[OptimizationPerformanceMetrics]:
+        """Collect performance metrics for the optimizations."""
+        logger.info("Estimate performance ...")
+
+        if not self.optimizations:
+            raise FunctionalityNotSupportedError(
+                reason="Unable to estimate model optimizations impact",
+                description="No optimization targets provided",
+            )
+
+        opt_settings = self._parse_optimization_params(self.optimizations)
+
+        try:
+            keras_model = get_keras_model(self.model, self.context)
+        except NotImplementedError as err:
+            raise FunctionalityNotSupportedError(
+                reason="Unable to run model optimizations",
+                description=f"{self.model} is not a Keras model and "
+                "could not be converted to a Keras model",
+            ) from err
+
+        optimizers = [OptimizeModel(self.context, opts) for opts in opt_settings]
+
+        estimator = EthosUPerformanceEstimator(
+            self.context,
+            self.device,
+            self.backends,
+        )
+        original_metrics, *optimized_metrics = estimate_performance(
+            keras_model, estimator, optimizers  # type: ignore
+        )
+
+        result = OptimizationPerformanceMetrics(
+            original_perf_metrics=original_metrics,
+            optimizations_perf_metrics=list(zip(opt_settings, optimized_metrics)),
+        )
+        return result
+
+    @staticmethod
+    def _parse_optimization_params(
+        optimizations: List[List[dict]],
+    ) -> List[List[OptimizationSettings]]:
+        """Parse optimization parameters."""
+        if not is_list_of(optimizations, list):
+            raise Exception("Optimization parameters expected to be a list")
+
+        return [
+            [
+                OptimizationSettings(
+                    item.get("optimization_type"),  # type: ignore
+                    item.get("optimization_target"),  # type: ignore
+                    item.get("layers_to_optimized"),
+                )
+                for item in opt_configuration
+            ]
+            for opt_configuration in optimizations
+        ]
+
+    @classmethod
+    def name(cls) -> str:
+        """Return name of the collector."""
+        return "ethos_u_model_optimizations"