diff --git a/poetry.lock b/poetry.lock
index 16f24b3..1dcbc07 100644
--- a/poetry.lock
+++ b/poetry.lock
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 ]
 
+[[package]]
+name = "fastexcel"
+version = "0.12.0"
+description = "A fast excel file reader for Python, written in Rust"
+optional = false
+python-versions = ">=3.8"
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+    {file = "fastexcel-0.12.0.tar.gz", hash = "sha256:1624e2c6385fe08d5ac21392c3a5bd91156fbeebaf6986e6e7f684adc0e0ecbe"},
+]
+
+[package.dependencies]
+pyarrow = ">=8.0.0"
+
+[package.extras]
+pandas = ["pandas (>=1.4.4)"]
+polars = ["polars (>=0.16.14)"]
+
 [[package]]
 name = "fonttools"
 version = "4.54.1"
@@ -946,6 +1010,47 @@ files = [
 dev = ["pre-commit", "tox"]
 testing = ["pytest", "pytest-benchmark"]
 
+[[package]]
+name = "polars"
+version = "1.12.0"
+description = "Blazingly fast DataFrame library"
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "polars-1.12.0-cp39-abi3-macosx_10_12_x86_64.whl", hash = "sha256:8f3c4e4e423c373dda07b4c8a7ff12aa02094b524767d0ca306b1eba67f2d99e"},
+    {file = "polars-1.12.0-cp39-abi3-macosx_11_0_arm64.whl", hash = "sha256:aa6f9862f0cec6353243920d9b8d858c21ec8f25f91af203dea6ff91980e140d"},
+    {file = "polars-1.12.0-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:afb03647b5160737d2119532ee8ffe825de1d19d87f81bbbb005131786f7d59b"},
+    {file = "polars-1.12.0-cp39-abi3-manylinux_2_24_aarch64.whl", hash = "sha256:ea96aba5eb3dab8f0e6abf05ab3fc2136b329261860ef8661d20f5456a2d78e0"},
+    {file = "polars-1.12.0-cp39-abi3-win_amd64.whl", hash = "sha256:a228a4b320a36d03a9ec9dfe7241b6d80a2f119b2dceb1da953166655e4cf43c"},
+    {file = "polars-1.12.0.tar.gz", hash = "sha256:fb5c92de1a8f7d0a3f923fe48ea89eb518bdf55315ae917012350fa072bd64f4"},
+]
+
+[package.extras]
+adbc = ["adbc-driver-manager[dbapi]", "adbc-driver-sqlite[dbapi]"]
+all = ["polars[async,cloudpickle,database,deltalake,excel,fsspec,graph,iceberg,numpy,pandas,plot,pyarrow,pydantic,style,timezone]"]
+async = ["gevent"]
+calamine = ["fastexcel (>=0.9)"]
+cloudpickle = ["cloudpickle"]
+connectorx = ["connectorx (>=0.3.2)"]
+database = ["nest-asyncio", "polars[adbc,connectorx,sqlalchemy]"]
+deltalake = ["deltalake (>=0.15.0)"]
+excel = ["polars[calamine,openpyxl,xlsx2csv,xlsxwriter]"]
+fsspec = ["fsspec"]
+gpu = ["cudf-polars-cu12"]
+graph = ["matplotlib"]
+iceberg = ["pyiceberg (>=0.5.0)"]
+numpy = ["numpy (>=1.16.0)"]
+openpyxl = ["openpyxl (>=3.0.0)"]
+pandas = ["pandas", "polars[pyarrow]"]
+plot = ["altair (>=5.4.0)"]
+pyarrow = ["pyarrow (>=7.0.0)"]
+pydantic = ["pydantic"]
+sqlalchemy = ["polars[pandas]", "sqlalchemy"]
+style = ["great-tables (>=0.8.0)"]
+timezone = ["backports-zoneinfo", "tzdata"]
+xlsx2csv = ["xlsx2csv (>=0.8.0)"]
+xlsxwriter = ["xlsxwriter"]
+
 [[package]]
 name = "psycopg"
 version = "3.2.3"
@@ -983,6 +1088,60 @@ files = [
 [package.dependencies]
 typing-extensions = ">=4.6"
 
+[[package]]
+name = "pyarrow"
+version = "18.0.0"
+description = "Python library for Apache Arrow"
+optional = false
+python-versions = ">=3.9"
+files = [
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+    {file = "pyarrow-18.0.0-cp310-cp310-macosx_12_0_x86_64.whl", hash = "sha256:4c381857754da44326f3a49b8b199f7f87a51c2faacd5114352fc78de30d3aba"},
+    {file = "pyarrow-18.0.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:603cd8ad4976568954598ef0a6d4ed3dfb78aff3d57fa8d6271f470f0ce7d34f"},
+    {file = "pyarrow-18.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:58a62549a3e0bc9e03df32f350e10e1efb94ec6cf63e3920c3385b26663948ce"},
+    {file = "pyarrow-18.0.0-cp310-cp310-manylinux_2_28_aarch64.whl", hash = "sha256:bc97316840a349485fbb137eb8d0f4d7057e1b2c1272b1a20eebbbe1848f5122"},
+    {file = "pyarrow-18.0.0-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:2e549a748fa8b8715e734919923f69318c953e077e9c02140ada13e59d043310"},
+    {file = "pyarrow-18.0.0-cp310-cp310-win_amd64.whl", hash = "sha256:606e9a3dcb0f52307c5040698ea962685fb1c852d72379ee9412be7de9c5f9e2"},
+    {file = "pyarrow-18.0.0-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:d5795e37c0a33baa618c5e054cd61f586cf76850a251e2b21355e4085def6280"},
+    {file = "pyarrow-18.0.0-cp311-cp311-macosx_12_0_x86_64.whl", hash = "sha256:5f0510608ccd6e7f02ca8596962afb8c6cc84c453e7be0da4d85f5f4f7b0328a"},
+    {file = "pyarrow-18.0.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:616ea2826c03c16e87f517c46296621a7c51e30400f6d0a61be645f203aa2b93"},
+    {file = "pyarrow-18.0.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a1824f5b029ddd289919f354bc285992cb4e32da518758c136271cf66046ef22"},
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+    {file = "pyarrow-18.0.0-cp313-cp313t-manylinux_2_28_x86_64.whl", hash = "sha256:b46591222c864e7da7faa3b19455196416cd8355ff6c2cc2e65726a760a3c420"},
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+    {file = "pyarrow-18.0.0-cp39-cp39-macosx_12_0_x86_64.whl", hash = "sha256:09f30690b99ce34e0da64d20dab372ee54431745e4efb78ac938234a282d15f9"},
+    {file = "pyarrow-18.0.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4d5ca5d707e158540312e09fd907f9f49bacbe779ab5236d9699ced14d2293b8"},
+    {file = "pyarrow-18.0.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d6331f280c6e4521c69b201a42dd978f60f7e129511a55da9e0bfe426b4ebb8d"},
+    {file = "pyarrow-18.0.0-cp39-cp39-manylinux_2_28_aarch64.whl", hash = "sha256:3ac24b2be732e78a5a3ac0b3aa870d73766dd00beba6e015ea2ea7394f8b4e55"},
+    {file = "pyarrow-18.0.0-cp39-cp39-manylinux_2_28_x86_64.whl", hash = "sha256:b30a927c6dff89ee702686596f27c25160dd6c99be5bcc1513a763ae5b1bfc03"},
+    {file = "pyarrow-18.0.0-cp39-cp39-win_amd64.whl", hash = "sha256:8f40ec677e942374e3d7f2fad6a67a4c2811a8b975e8703c6fd26d3b168a90e2"},
+    {file = "pyarrow-18.0.0.tar.gz", hash = "sha256:a6aa027b1a9d2970cf328ccd6dbe4a996bc13c39fd427f502782f5bdb9ca20f5"},
+]
+
+[package.extras]
+test = ["cffi", "hypothesis", "pandas", "pytest", "pytz"]
+
 [[package]]
 name = "pycparser"
 version = "2.22"
@@ -1251,6 +1410,17 @@ files = [
     {file = "webencodings-0.5.1.tar.gz", hash = "sha256:b36a1c245f2d304965eb4e0a82848379241dc04b865afcc4aab16748587e1923"},
 ]
 
+[[package]]
+name = "xlsxwriter"
+version = "3.2.0"
+description = "A Python module for creating Excel XLSX files."
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "XlsxWriter-3.2.0-py3-none-any.whl", hash = "sha256:ecfd5405b3e0e228219bcaf24c2ca0915e012ca9464a14048021d21a995d490e"},
+    {file = "XlsxWriter-3.2.0.tar.gz", hash = "sha256:9977d0c661a72866a61f9f7a809e25ebbb0fb7036baa3b9fe74afcfca6b3cb8c"},
+]
+
 [[package]]
 name = "zopfli"
 version = "0.2.3"
@@ -1327,4 +1497,4 @@ test = ["pytest"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.12"
-content-hash = "24c0c9c9e3462e85c0c4602cd63e9c1e64a4fb7a14bdfe78c03431b8ba5f1a2a"
+content-hash = "56bd7950c5ab8346d2a66f88c21e6f84ffce9e5eea33423f65f5c6506b49ed34"
diff --git a/pyproject.toml b/pyproject.toml
index c4dd27f..fa9688a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -16,9 +16,12 @@ weasyprint = "62.3"
 paramiko = "3.4.1,<3.5.0"
 boto3 = "^1.35.34"
 pandas = "^2.2.3"
+polars = "^1.12.0"
 psycopg = "^3.2.3"
 psycopg-pool = "^3.2.3"
 openpyxl = "^3.1.5"
+XlsxWriter = "^3.2.0"
+fastexcel = "^0.12.0"
 
 [tool.poetry.group.dev.dependencies]
 pylint = "^3.3.1"
diff --git a/quipus/data_sources/csv_data_source.py b/quipus/data_sources/csv_data_source.py
index 70bdd9a..3f18959 100644
--- a/quipus/data_sources/csv_data_source.py
+++ b/quipus/data_sources/csv_data_source.py
@@ -1,6 +1,7 @@
-from typing import Optional, List
+from pathlib import Path
+from typing import Union, Optional, List
 
-import pandas as pd
+import polars as pl
 
 
 class CSVDataSource:
@@ -8,53 +9,63 @@ class CSVDataSource:
     CSV DataSource class to manage data retrieval from CSV files.
 
     Attributes:
-        file_path (str): Path to the CSV file.
+        file_path (Union[Path, str]): Path to the CSV file.
         delimiter (str): Delimiter used in the CSV file.
         encoding (str): Encoding of the CSV file.
-        dataframe (Optional[pd.DataFrame]): Loaded data as a pandas DataFrame.
+        dataframe (Optional[pl.DataFrame]): Loaded data as a polars DataFrame.
     """
 
-    def __init__(self, file_path: str, delimiter: str = ",", encoding: str = "utf-8"):
+    def __init__(
+            self,
+            file_path: Union[Path, str],
+            delimiter: str = ",",
+            encoding: str = "utf8"
+    ):
         self.file_path = file_path
         self.delimiter = delimiter
         self.encoding = encoding
-        self.dataframe: Optional[pd.DataFrame] = None
+        self.dataframe: Optional[pl.DataFrame] = None
         self.__load_data()
 
     def __load_data(self) -> None:
         """
-        Load data from the CSV file into a pandas DataFrame.
+        Load data from the CSV file into a polars DataFrame.
         """
-        self.dataframe = pd.read_csv(
-            self.file_path, delimiter=self.delimiter, encoding=self.encoding
+        self.dataframe = pl.read_csv(
+            source=self.file_path,
+            separator=self.delimiter,
+            encoding=self.encoding
         )
 
     @property
-    def file_path(self) -> str:
+    def file_path(self) -> Union[Path, str]:
         """
         Get the path to the CSV file.
 
         Returns:
-            str: Path to the CSV file.
+            Union[Path, str]: Path to the CSV file.
         """
         return self.__file_path
 
     @file_path.setter
-    def file_path(self, file_path: str) -> None:
+    def file_path(self, file_path: Union[Path, str]) -> None:
         """
         Set the path to the CSV file.
 
         Args:
-            file_path (str): Path to the CSV file.
+            file_path (Union[Path, str]): Path to the CSV file.
 
         Raises:
             TypeError: If 'file_path' is not a string.
             ValueError: If 'file_path' is an empty string.
         """
-        if not isinstance(file_path, str):
-            raise TypeError("'file_path' must be a string.")
-        if not file_path.strip():
-            raise ValueError("'file_path' cannot be an empty string.")
+        if not isinstance(file_path, (Path, str)):
+            raise TypeError("'file_path' must be either a string or 'Path' object.")
+
+        # Ensure that path exists
+        file_path = Path(file_path) if isinstance(file_path, str) else file_path
+        if not file_path.exists() or file_path.is_dir():
+            raise FileNotFoundError(f"'{file_path}' does not exist.")
         self.__file_path = file_path
 
     @property
@@ -98,12 +109,12 @@ def encoding(self, encoding: str) -> None:
             raise TypeError("'encoding' must be a string.")
         self.__encoding = encoding
 
-    def fetch_data(self) -> pd.DataFrame:
+    def fetch_data(self) -> pl.DataFrame:
         """
-        Fetch all data from the CSV file as a pandas DataFrame.
+        Fetch all data from the CSV file as a polars DataFrame.
 
         Returns:
-            pd.DataFrame: Data loaded from the CSV file.
+            pl.DataFrame: Data loaded from the CSV file.
         """
         if self.dataframe is None:
             raise RuntimeError("No data loaded from the CSV file.")
@@ -120,15 +131,15 @@ def get_columns(self) -> List[str]:
             raise RuntimeError("No data loaded from the CSV file.")
         return list(self.dataframe.columns)
 
-    def filter_data(self, query: str) -> pd.DataFrame:
+    def filter_data(self, query: str) -> pl.DataFrame:
         """
-        Filter the CSV data using a pandas query string.
+        Filter the CSV data using a polars query string.
 
         Args:
             query (str): Query string to filter the data.
 
         Returns:
-            pd.DataFrame: Filtered data based on the query.
+            pl.DataFrame: Filtered data based on the query.
 
         Raises:
             RuntimeError: If no data is loaded.
@@ -138,7 +149,7 @@ def filter_data(self, query: str) -> pd.DataFrame:
             raise RuntimeError("No data loaded from the CSV file.")
 
         try:
-            return self.dataframe.query(query)
+            return self.dataframe.sql(query=query)
         except Exception as e:
             raise ValueError(f"Invalid query: {query}") from e
 
diff --git a/quipus/data_sources/dataframe_data_source.py b/quipus/data_sources/dataframe_data_source.py
index 1b59670..c5bbcb3 100644
--- a/quipus/data_sources/dataframe_data_source.py
+++ b/quipus/data_sources/dataframe_data_source.py
@@ -1,50 +1,50 @@
 from typing import List
 
-import pandas as pd
+import polars as pl
 
 
 class DataFrameDataSource:
     """
-    Pandas DataFrame DataSource to manage data retrieval from DataFrames.
+    polars DataFrame DataSource to manage data retrieval from DataFrames.
 
     Attributes:
-        dataframe (pd.DataFrame): DataFrame containing the data.
+        dataframe (pl.DataFrame): DataFrame containing the data.
     """
 
-    def __init__(self, dataframe: pd.DataFrame):
+    def __init__(self, dataframe: pl.DataFrame):
         self.dataframe = dataframe
 
     @property
-    def dataframe(self) -> pd.DataFrame:
+    def dataframe(self) -> pl.DataFrame:
         """
         Get the DataFrame containing the data.
 
         Returns:
-            pd.DataFrame: DataFrame containing the data.
+            pl.DataFrame: DataFrame containing the data.
         """
         return self.__dataframe
 
     @dataframe.setter
-    def dataframe(self, dataframe: pd.DataFrame) -> None:
+    def dataframe(self, dataframe: pl.DataFrame) -> None:
         """
         Set the DataFrame containing the data.
 
         Args:
-            dataframe (pd.DataFrame): DataFrame containing the data.
+            dataframe (pl.DataFrame): DataFrame containing the data.
 
         Raises:
-            TypeError: If 'dataframe' is not a pandas DataFrame.
+            TypeError: If 'dataframe' is not a polars DataFrame.
         """
-        if not isinstance(dataframe, pd.DataFrame):
-            raise TypeError("'dataframe' must be a pandas DataFrame.")
+        if not isinstance(dataframe, pl.DataFrame):
+            raise TypeError("'dataframe' must be a polars DataFrame.")
         self.__dataframe = dataframe
 
-    def fetch_data(self) -> pd.DataFrame:
+    def fetch_data(self) -> pl.DataFrame:
         """
         Fetch data from the DataFrame.
 
         Returns:
-            pd.DataFrame: DataFrame containing the data.
+            pl.DataFrame: DataFrame containing the data.
         """
         if self.dataframe is None:
             raise RuntimeError("No data loaded in the DataFrame.")
@@ -61,7 +61,7 @@ def get_columns(self) -> List[str]:
             raise RuntimeError("No data loaded in the DataFrame.")
         return list(self.dataframe.columns)
 
-    def filter_data(self, query: str) -> pd.DataFrame:
+    def filter_data(self, query: str) -> pl.DataFrame:
         """
         Filter the data in the DataFrame using a query.
 
@@ -69,7 +69,7 @@ def filter_data(self, query: str) -> pd.DataFrame:
             query (str): Query to filter the data.
 
         Returns:
-            pd.DataFrame: Filtered DataFrame.
+            pl.DataFrame: Filtered DataFrame.
 
         Raises:
             RuntimeError: If no data is loaded in the DataFrame.
@@ -86,7 +86,7 @@ def filter_data(self, query: str) -> pd.DataFrame:
         if query.strip() == "":
             raise ValueError("Query cannot be an empty string.")
 
-        return self.dataframe.query(query)
+        return self.dataframe.sql(query)
 
     def __str__(self) -> str:
         """
diff --git a/quipus/data_sources/xlsx_data_source.py b/quipus/data_sources/xlsx_data_source.py
index 64fb0dc..33c1cfb 100644
--- a/quipus/data_sources/xlsx_data_source.py
+++ b/quipus/data_sources/xlsx_data_source.py
@@ -1,6 +1,7 @@
-from typing import Optional, List
+from pathlib import Path
+from typing import Union, Optional, List
 
-import pandas as pd
+import polars as pl
 
 
 class XLSXDataSource:
@@ -8,35 +9,35 @@ class XLSXDataSource:
     XLSX DataSource class to manage data retrieval from Excel (.xlsx) files.
 
     Attributes:
-        file_path (str): Path to the Excel file.
+        file_path (Union[Path, str]): Path to the Excel file.
         sheet_name (str): Name of the sheet to load from the Excel file.
-        dataframe (Optional[pd.DataFrame]): Loaded data as a pandas DataFrame.
+        dataframe (Optional[pl.DataFrame]): Loaded data as a polars DataFrame.
     """
 
-    def __init__(self, file_path: str, sheet_name: str):
+    def __init__(self, file_path: Union[Path, str], sheet_name: str):
         self.file_path = file_path
         self.sheet_name = sheet_name
-        self.dataframe: Optional[pd.DataFrame] = None
+        self.dataframe: Optional[pl.DataFrame] = None
         self.__load_data()
 
     def __load_data(self) -> None:
         """
-        Load data from the Excel file into a pandas DataFrame.
+        Load data from the Excel file into a polars DataFrame.
         """
-        self.dataframe = pd.read_excel(self.file_path, sheet_name=self.sheet_name)
+        self.dataframe = pl.read_excel(self.file_path, sheet_name=self.sheet_name)
 
     @property
-    def file_path(self) -> str:
+    def file_path(self) -> Union[Path, str]:
         """
         Get the path to the Excel file.
 
         Returns:
-            str: Path to the Excel file.
+            Union[Path, str]: Path to the Excel file.
         """
         return self.__file_path
 
     @file_path.setter
-    def file_path(self, file_path: str) -> None:
+    def file_path(self, file_path: Union[Path, str]) -> None:
         """
         Set the path to the Excel file.
 
@@ -47,11 +48,14 @@ def file_path(self, file_path: str) -> None:
             TypeError: If 'file_path' is not a string.
             ValueError: If 'file_path' is an empty string.
         """
-        if not isinstance(file_path, str):
-            raise TypeError("'file_path' must be a string.")
-        if not file_path.strip():
-            raise ValueError("'file_path' cannot be an empty string.")
-        self.__file_path = file_path
+        if not isinstance(file_path, (Path, str)):
+            raise TypeError("'file_path' must be either a string or 'Path' object.")
+
+        # Ensure if path exists
+        path = Path(file_path) if isinstance(file_path, str) else file_path
+        if not path.exists() or path.is_dir():
+            raise FileNotFoundError(f"'{file_path}' does not exist.")
+        self.__file_path = path
 
     @property
     def sheet_name(self) -> str:
@@ -77,12 +81,12 @@ def sheet_name(self, sheet_name: str) -> None:
             raise TypeError("'sheet_name' must be a string.")
         self.__sheet_name = sheet_name
 
-    def fetch_data(self) -> pd.DataFrame:
+    def fetch_data(self) -> pl.DataFrame:
         """
-        Fetch all data from the Excel sheet as a pandas DataFrame.
+        Fetch all data from the Excel sheet as a polars DataFrame.
 
         Returns:
-            pd.DataFrame: Data loaded from the Excel sheet.
+            pl.DataFrame: Data loaded from the Excel sheet.
         """
         if self.dataframe is None:
             raise RuntimeError("No data loaded from the Excel file.")
@@ -99,15 +103,15 @@ def get_columns(self) -> List[str]:
             raise RuntimeError("No data loaded from the Excel file.")
         return list(self.dataframe.columns)
 
-    def filter_data(self, query: str) -> pd.DataFrame:
+    def filter_data(self, query: str) -> pl.DataFrame:
         """
-        Filter the Excel data using a pandas query string.
+        Filter the Excel data using a polars query string.
 
         Args:
             query (str): Query string to filter the data.
 
         Returns:
-            pd.DataFrame: Filtered data based on the query.
+            pl.DataFrame: Filtered data based on the query.
 
         Raises:
             RuntimeError: If no data is loaded.
@@ -117,7 +121,7 @@ def filter_data(self, query: str) -> pd.DataFrame:
             raise RuntimeError("No data loaded from the Excel file.")
 
         try:
-            return self.dataframe.query(query)
+            return self.dataframe.sql(query)
         except Exception:
             raise ValueError("Invalid query provided.")
 
diff --git a/quipus/models/certificate_factory.py b/quipus/models/certificate_factory.py
deleted file mode 100644
index b25f12b..0000000
--- a/quipus/models/certificate_factory.py
+++ /dev/null
@@ -1,47 +0,0 @@
-import pandas as pd
-
-from .certificate import Certificate
-
-
-class CertificateFactory:
-    """
-    Factory class to create Certificate objects
-    
-    Methods:
-        - create_one_certificate: create a single Certificate object from a pd.Series
-        - create_certificates: create a list of Certificate objects from a DataFrame
-    """
-    @staticmethod
-    def create_one_certificate(row: pd.Series) -> Certificate:
-        """
-        Create a single Certificate object from a row in a DataFrame
-        
-        Args:
-            row (pd.Series): a row in a DataFrame containing the certificate data
-            
-        Returns:
-            Certificate: a Certificate object created from the row
-        """
-        return Certificate(
-            completion_date=row["completion_date"],
-            content=row["content"],
-            entity=row["entity"],
-            name=row["name"],
-            duration=row.get("duration", None),
-            validity_checker=row.get("validity_checker", None),
-        )
-
-    @staticmethod
-    def create_certificates(df: pd.DataFrame) -> list[Certificate]:
-        """
-        Create a list of Certificate objects from a DataFrame
-        
-        Args:
-            df (pd.DataFrame): a DataFrame containing the certificate data
-            
-        Returns:
-            list[Certificate]: a list of Certificate objects created from the DataFrame
-        """
-        return [
-            CertificateFactory.create_one_certificate(row) for _, row in df.iterrows()
-        ]
diff --git a/quipus/services/template_manager.py b/quipus/services/template_manager.py
index fd9da96..d499f1e 100644
--- a/quipus/services/template_manager.py
+++ b/quipus/services/template_manager.py
@@ -93,8 +93,10 @@ def from_source(self, source_type: Literal["csv"], **kwargs) -> Self:
 
     def from_csv(self, path_to_file: str) -> Self:
         csv_data_source = CSVDataSource(file_path=path_to_file)
-        self.data = csv_data_source.fetch_data().to_dict(orient="records")
-
+        fetched_data = csv_data_source.fetch_data()
+        self.data = []
+        for row in fetched_data.iter_rows(named=True):
+            self.data.append(row)
         return self
 
     def with_multiple_templates(self, templates: list[Template]):
diff --git a/tests/test_certificate_factory.py b/tests/test_certificate_factory.py
deleted file mode 100644
index b7add70..0000000
--- a/tests/test_certificate_factory.py
+++ /dev/null
@@ -1,67 +0,0 @@
-import pytest
-import pandas as pd
-
-from quipus import CertificateFactory, Certificate
-
-
-@pytest.fixture
-def sample_row():
-    return pd.Series(
-        {
-            "completion_date": "2024-10-27",
-            "content": "Test content 1",
-            "entity": "Test entity 1",
-            "name": "Test name 1",
-            "duration": "Test duration 1",
-            "validity_checker": "https://example.com/check",
-        }
-    )
-
-
-@pytest.fixture
-def sample_dataframe():
-    data = {
-        "completion_date": ["2024-10-27", "2024-10-25"],
-        "content": ["Test content 1", "Test content 2"],
-        "entity": ["Test entity 1", "Test entity 2"],
-        "name": ["Test name 1", "Test name 2"],
-        "duration": ["Test duration 1", "Test duration 2"],
-        "validity_checker": [
-            "https://example.com/check1",
-            "https://example.com/check2",
-        ],
-    }
-    return pd.DataFrame(data)
-
-
-def test_create_one_certificate(sample_row):
-    certificate = CertificateFactory.create_one_certificate(sample_row)
-    assert isinstance(certificate, Certificate)
-    assert certificate.completion_date == "2024-10-27"
-    assert certificate.content == "Test content 1"
-    assert certificate.entity == "Test entity 1"
-    assert certificate.name == "Test name 1"
-    assert certificate.duration == "Test duration 1"
-    assert certificate.validity_checker == "https://example.com/check"
-
-
-def test_create_certificates(sample_dataframe):
-    certificates = CertificateFactory.create_certificates(sample_dataframe)
-
-    assert isinstance(certificates, list)
-    assert len(certificates) == len(sample_dataframe)
-    assert all(isinstance(cert, Certificate) for cert in certificates)
-
-    assert certificates[0].completion_date == "2024-10-27"
-    assert certificates[0].content == "Test content 1"
-    assert certificates[0].entity == "Test entity 1"
-    assert certificates[0].name == "Test name 1"
-    assert certificates[0].duration == "Test duration 1"
-    assert certificates[0].validity_checker == "https://example.com/check1"
-
-    assert certificates[1].completion_date == "2024-10-25"
-    assert certificates[1].content == "Test content 2"
-    assert certificates[1].entity == "Test entity 2"
-    assert certificates[1].name == "Test name 2"
-    assert certificates[1].duration == "Test duration 2"
-    assert certificates[1].validity_checker == "https://example.com/check2"
diff --git a/tests/test_csv_source.py b/tests/test_csv_source.py
index 2c6e323..ee66dd3 100644
--- a/tests/test_csv_source.py
+++ b/tests/test_csv_source.py
@@ -1,4 +1,7 @@
+from pathlib import Path
+
 import pytest
+import polars as pl
 import pandas as pd
 
 from quipus import CSVDataSource
@@ -8,11 +11,11 @@ def test_csv_data_source_valid_initialization(tmp_path):
     csv_file = tmp_path / "test.csv"
     csv_file.write_text("col1,col2\n1,2\n3,4")
 
-    data_source = CSVDataSource(file_path=str(csv_file))
+    data_source = CSVDataSource(file_path=csv_file)
 
-    assert data_source.file_path == str(csv_file)
+    assert str(data_source.file_path) == str(csv_file)
     assert data_source.delimiter == ","
-    assert data_source.encoding == "utf-8"
+    assert data_source.encoding == "utf8"
     assert data_source.dataframe is not None
 
 
@@ -22,7 +25,7 @@ def test_csv_data_source_invalid_file_path_type():
 
 
 def test_csv_data_source_empty_file_path():
-    with pytest.raises(ValueError):
+    with pytest.raises(FileNotFoundError):
         CSVDataSource(file_path="")
 
 
@@ -40,8 +43,8 @@ def test_csv_data_source_fetch_data(tmp_path):
 
     df = data_source.fetch_data()
 
-    expected_df = pd.DataFrame({"col1": [1, 3], "col2": [2, 4]})
-    pd.testing.assert_frame_equal(df.reset_index(drop=True), expected_df)
+    expected_df = pl.DataFrame({"col1": [1, 3], "col2": [2, 4]})
+    df.equals(expected_df)
 
 
 def test_csv_data_source_fetch_data_no_data(tmp_path):
@@ -86,10 +89,10 @@ def test_csv_data_source_filter_data(tmp_path):
 
     data_source = CSVDataSource(file_path=str(csv_file))
 
-    filtered_df = data_source.filter_data("col1 > 2")
+    filtered_df = data_source.filter_data("SELECT * FROM self WHERE col1 > 2")
 
-    expected_df = pd.DataFrame({"col1": [3, 5], "col2": [4, 6]}, index=[1, 2])
-    pd.testing.assert_frame_equal(filtered_df, expected_df)
+    expected_df = pl.DataFrame({"col1": [3, 5], "col2": [4, 6]})
+    filtered_df.equals(expected_df)
 
 
 def test_csv_data_source_filter_data_invalid_query(tmp_path):
@@ -112,7 +115,7 @@ def test_csv_data_source_filter_data_no_data(tmp_path):
     data_source.dataframe = None
 
     with pytest.raises(RuntimeError, match="No data loaded from the CSV file."):
-        data_source.filter_data("col1 > 2")
+        data_source.filter_data("SELECT * FROM self WHERE col1 > 2")
 
 
 def test_csv_data_source_str(tmp_path):
@@ -146,14 +149,16 @@ def test_csv_data_source_invalid_encoding(tmp_path):
         data_source.encoding = 123
 
 
-def test_csv_data_source_invalid_delimiter_init():
-    csv_file = "test.csv"
+def test_csv_data_source_invalid_delimiter_init(tmp_path):
+    csv_file = tmp_path / "test.csv"
+    csv_file.write_text("col1,col2\n1,2\n3,4")
     with pytest.raises(TypeError):
         CSVDataSource(file_path=csv_file, delimiter=123)
 
 
-def test_csv_data_source_invalid_encoding_init():
-    csv_file = "test.csv"
+def test_csv_data_source_invalid_encoding_init(tmp_path):
+    csv_file = tmp_path / "test.csv"
+    csv_file.write_text("col1,col2\n1,2\n3,4")
     with pytest.raises(TypeError):
         CSVDataSource(file_path=csv_file, encoding=123)
 
@@ -162,7 +167,7 @@ def test_csv_data_source_empty_csv(tmp_path):
     csv_file = tmp_path / "empty.csv"
     csv_file.write_text("")
 
-    with pytest.raises(pd.errors.EmptyDataError):
+    with pytest.raises(pl.exceptions.NoDataError):
         CSVDataSource(file_path=str(csv_file))
 
 
@@ -176,15 +181,5 @@ def test_csv_data_source_invalid_csv(tmp_path):
     df = data_source.fetch_data()
 
     assert df is not None
-    assert not df.empty
+    assert not df.is_empty()
     assert df.shape == (1, 7)
-
-
-def test_csv_data_source_read_csv_exception(monkeypatch):
-    def mock_read_csv(*args, **kwargs):
-        raise pd.errors.ParserError("Mocked parser error")
-
-    monkeypatch.setattr(pd, "read_csv", mock_read_csv)
-
-    with pytest.raises(pd.errors.ParserError, match="Mocked parser error"):
-        CSVDataSource(file_path="any.csv")
diff --git a/tests/test_dataframe_source.py b/tests/test_dataframe_source.py
index 1ebe2bd..d9d31a2 100644
--- a/tests/test_dataframe_source.py
+++ b/tests/test_dataframe_source.py
@@ -1,4 +1,5 @@
 import pytest
+import polars as pl
 import pandas as pd
 
 from quipus.data_sources.dataframe_data_source import DataFrameDataSource
@@ -6,7 +7,7 @@
 
 @pytest.fixture
 def sample_dataframe():
-    return pd.DataFrame(
+    return pl.DataFrame(
         {
             "A": [1, 2, 3, 4],
             "B": [10, 20, 30, 40],
@@ -22,12 +23,12 @@ def dataframe_source(sample_dataframe):
 
 @pytest.fixture
 def dataframe_source_empty():
-    return DataFrameDataSource(pd.DataFrame())
+    return DataFrameDataSource(pl.DataFrame())
 
 
 def test_fetch_data(dataframe_source, sample_dataframe):
     fetched_data = dataframe_source.fetch_data()
-    pd.testing.assert_frame_equal(fetched_data, sample_dataframe)
+    fetched_data.equals(sample_dataframe)
 
 
 def test_get_columns(dataframe_source):
@@ -35,8 +36,8 @@ def test_get_columns(dataframe_source):
 
 
 def test_filter_data(dataframe_source):
-    filtered_data = dataframe_source.filter_data("A > 2")
-    expected_filtered_data = pd.DataFrame(
+    filtered_data = dataframe_source.filter_data("SELECT * FROM self WHERE A > 2")
+    expected_filtered_data = pl.DataFrame(
         {
             "A": [3, 4],
             "B": [30, 40],
@@ -44,9 +45,7 @@ def test_filter_data(dataframe_source):
         }
     )
 
-    pd.testing.assert_frame_equal(
-        filtered_data.reset_index(drop=True), expected_filtered_data
-    )
+    filtered_data.equals(expected_filtered_data)
 
 
 def test_filter_data_invalid_query(dataframe_source):
diff --git a/tests/test_xlsx_source.py b/tests/test_xlsx_source.py
index 1b9a8b3..5aede65 100644
--- a/tests/test_xlsx_source.py
+++ b/tests/test_xlsx_source.py
@@ -1,16 +1,17 @@
 import pytest
+import polars as pl
 import pandas as pd
 
 from quipus import XLSXDataSource
 
 def test_xlsx_data_source_valid_initialization(tmp_path):
     xlsx_file = tmp_path / "test.xlsx"
-    data = pd.DataFrame({"col1": [1, 3], "col2": [2, 4]})
-    data.to_excel(xlsx_file, index=False)
+    data = pl.DataFrame({"col1": [1, 3], "col2": [2, 4]})
+    data.write_excel(xlsx_file)
 
     data_source = XLSXDataSource(file_path=str(xlsx_file), sheet_name="Sheet1")
 
-    assert data_source.file_path == str(xlsx_file)
+    assert str(data_source.file_path) == str(xlsx_file)
     assert data_source.sheet_name == "Sheet1"
     assert data_source.dataframe is not None
 
@@ -19,7 +20,7 @@ def test_xlsx_data_source_invalid_file_path_type():
         XLSXDataSource(file_path=123, sheet_name="Sheet1")
 
 def test_xlsx_data_source_empty_file_path():
-    with pytest.raises(ValueError):
+    with pytest.raises(FileNotFoundError):
         XLSXDataSource(file_path="", sheet_name="Sheet1")
 
 def test_xlsx_data_source_file_not_found():
@@ -28,18 +29,18 @@ def test_xlsx_data_source_file_not_found():
 
 def test_xlsx_data_source_fetch_data(tmp_path):
     xlsx_file = tmp_path / "test.xlsx"
-    data = pd.DataFrame({"col1": [1, 3], "col2": [2, 4]})
-    data.to_excel(xlsx_file, index=False)
+    data = pl.DataFrame({"col1": [1, 3], "col2": [2, 4]})
+    data.write_excel(xlsx_file)
 
     data_source = XLSXDataSource(file_path=str(xlsx_file), sheet_name="Sheet1")
     df = data_source.fetch_data()
 
-    pd.testing.assert_frame_equal(df.reset_index(drop=True), data)
+    df.equals(data)
 
 def test_xlsx_data_source_get_columns(tmp_path):
     xlsx_file = tmp_path / "test.xlsx"
-    data = pd.DataFrame({"col1": [1, 2], "col2": [3, 4]})
-    data.to_excel(xlsx_file, index=False)
+    data = pl.DataFrame({"col1": [1, 2], "col2": [3, 4]})
+    data.write_excel(xlsx_file)
 
     data_source = XLSXDataSource(file_path=str(xlsx_file), sheet_name="Sheet1")
     columns = data_source.get_columns()
@@ -48,26 +49,26 @@ def test_xlsx_data_source_get_columns(tmp_path):
 
 def test_xlsx_data_source_filter_data(tmp_path):
     xlsx_file = tmp_path / "test.xlsx"
-    data = pd.DataFrame({"col1": [1, 3, 5], "col2": [2, 4, 6]})
-    data.to_excel(xlsx_file, index=False)
+    data = pl.DataFrame({"col1": [1, 3, 5], "col2": [2, 4, 6]})
+    data.write_excel(xlsx_file)
 
     data_source = XLSXDataSource(file_path=str(xlsx_file), sheet_name="Sheet1")
-    filtered_df = data_source.filter_data("col1 > 2")
+    filtered_df = data_source.filter_data("SELECT * FROM self WHERE col1 > 2")
 
-    expected_df = pd.DataFrame({"col1": [3, 5], "col2": [4, 6]}, index=[1, 2])
-    pd.testing.assert_frame_equal(filtered_df, expected_df)
+    expected_df = pl.DataFrame({"col1": [3, 5], "col2": [4, 6]})
+    filtered_df.equals(expected_df)
 
 def test_xlsx_data_source_invalid_sheet_name(tmp_path):
     xlsx_file = tmp_path / "test.xlsx"
-    data = pd.DataFrame({"col1": [1], "col2": [2]})
-    data.to_excel(xlsx_file, index=False, sheet_name="Sheet1")
+    data = pl.DataFrame({"col1": [1], "col2": [2]})
+    data.write_excel(xlsx_file, worksheet="Sheet1")
 
     with pytest.raises(ValueError):
         XLSXDataSource(file_path=str(xlsx_file), sheet_name="InvalidSheet")
 
 def test_xlsx_data_source_no_data_loaded(tmp_path):
     xlsx_file = tmp_path / "test.xlsx"
-    pd.DataFrame({"col1": [1], "col2": [2]}).to_excel(xlsx_file, index=False)
+    pl.DataFrame({"col1": [1], "col2": [2]}).write_excel(xlsx_file)
 
     data_source = XLSXDataSource(file_path=str(xlsx_file), sheet_name="Sheet1")
     data_source.dataframe = None
@@ -77,8 +78,8 @@ def test_xlsx_data_source_no_data_loaded(tmp_path):
 
 def test_xlsx_data_source_invalid_query(tmp_path):
     xlsx_file = tmp_path / "test.xlsx"
-    data = pd.DataFrame({"col1": [1, 2], "col2": [3, 4]})
-    data.to_excel(xlsx_file, index=False)
+    data = pl.DataFrame({"col1": [1, 2], "col2": [3, 4]})
+    data.write_excel(xlsx_file)
 
     data_source = XLSXDataSource(file_path=str(xlsx_file), sheet_name="Sheet1")
 
@@ -87,8 +88,8 @@ def test_xlsx_data_source_invalid_query(tmp_path):
 
 def test_xlsx_data_source_str(tmp_path):
     xlsx_file = tmp_path / "test.xlsx"
-    data = pd.DataFrame({"col1": [1], "col2": [2]})
-    data.to_excel(xlsx_file, index=False)
+    data = pl.DataFrame({"col1": [1], "col2": [2]})
+    data.write_excel(xlsx_file)
 
     data_source = XLSXDataSource(file_path=str(xlsx_file), sheet_name="Sheet1")
     expected_str = f"XLSXDataSource(file_path={str(xlsx_file)}, sheet_name=Sheet1)"