diff --git a/Dockerfile b/Dockerfile
index 35e64db..b51ef49 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -1,4 +1,4 @@
-FROM apache/airflow:2.8.2-python3.8
+FROM apache/airflow:2.8.2-python3.10
 
 ENV PYTHONBUFFERED=0
 ENV AIRFLOW__LOGGING__LOGGING_LEVEL=INFO
diff --git a/README.md b/README.md
index c5a5bf3..c8e2782 100644
--- a/README.md
+++ b/README.md
@@ -1 +1,88 @@
-# bi-dags
+# BI-DAGs Setup Guide
+
+This README provides a step-by-step guide on setting up your environment for running BI-DAGs with Airflow.
+
+## Prerequisites
+
+Before you begin, ensure you have `pyenv` installed on your system. If you don't have `pyenv` installed, please follow the instructions [here](https://github.com/pyenv/pyenv#installation).
+
+## Installation Steps
+
+### 1. Set Up Python Environment
+
+First, we'll set up a Python environment using `pyenv`.
+
+```sh
+# Define the desired Python version
+export PYTHON_VERSION=3.10.11
+
+# Install the specified Python version using pyenv
+pyenv install $PYTHON_VERSION
+
+# Set the global Python version to the installed one
+pyenv global $PYTHON_VERSION
+
+# Create a virtual environment named 'bi-dags'
+pyenv virtualenv $PYTHON_VERSION bi-dags
+
+# Activate the virtual environment
+pyenv activate bi-dags
+```
+
+### 2. Navigate to Project Directory
+
+Change your current working directory to `bi-dags`.
+
+```sh
+cd bi-dags
+```
+
+### 3. Install Dependencies
+
+With your virtual environment activated, install the necessary dependencies.
+
+```sh
+pip install -r requirements.txt
+```
+
+### 4. Set Airflow Home
+
+Configure the Airflow home environment variable.
+
+```sh
+export AIRFLOW_HOME=$PWD
+```
+
+### 5. Start Airflow
+
+Initialize and start Airflow using the standalone command.
+
+```sh
+airflow standalone
+```
+
+### 6. Start Postgres with Docker Compose
+
+If you're using Docker to manage your Postgres database, start the service.
+
+```sh
+docker-compose start
+```
+
+### 7. Add Airflow Connections via UI
+
+Lastly, add the necessary Airflow connections through the UI.
+
+- Navigate to Admin -> Connections in the Airflow UI.
+- Click on "Add" and fill in the details:
+  - Connection Id: `superset_qa`
+  - Login: `airflow`
+  - Database: `airflow`
+  - Password: `airflow`
+  - Host: `localhost`
+  - Port: `5432`
+  - Connection Type: `postgres`
+
+More information, how to manage db connections can be found [here](https://airflow.apache.org/docs/apache-airflow/2.8.2/howto/connection.html).
+
+After completing these steps, your environment should be set up and ready for running BI-DAGs with Airflow.
diff --git a/dags/migrations/alembic.ini b/dags/migrations/alembic.ini
new file mode 100644
index 0000000..6b83140
--- /dev/null
+++ b/dags/migrations/alembic.ini
@@ -0,0 +1,115 @@
+# A generic, single database configuration.
+
+[alembic]
+# path to migration scripts
+script_location = .
+
+# template used to generate migration file names; The default value is %%(rev)s_%%(slug)s
+# Uncomment the line below if you want the files to be prepended with date and time
+# see https://alembic.sqlalchemy.org/en/latest/tutorial.html#editing-the-ini-file
+# for all available tokens
+# file_template = %%(year)d_%%(month).2d_%%(day).2d_%%(hour).2d%%(minute).2d-%%(rev)s_%%(slug)s
+
+# sys.path path, will be prepended to sys.path if present.
+# defaults to the current working directory.
+prepend_sys_path = .
+
+# timezone to use when rendering the date within the migration file
+# as well as the filename.
+# If specified, requires the python>=3.9 or backports.zoneinfo library.
+# Any required deps can installed by adding `alembic[tz]` to the pip requirements
+# string value is passed to ZoneInfo()
+# leave blank for localtime
+# timezone =
+
+# max length of characters to apply to the
+# "slug" field
+# truncate_slug_length = 40
+
+# set to 'true' to run the environment during
+# the 'revision' command, regardless of autogenerate
+# revision_environment = false
+
+# set to 'true' to allow .pyc and .pyo files without
+# a source .py file to be detected as revisions in the
+# versions/ directory
+# sourceless = false
+
+# version location specification; This defaults
+# to ./versions.  When using multiple version
+# directories, initial revisions must be specified with --version-path.
+# The path separator used here should be the separator specified by "version_path_separator" below.
+# version_locations = %(here)s/bar:%(here)s/bat:./versions
+
+# version path separator; As mentioned above, this is the character used to split
+# version_locations. The default within new alembic.ini files is "os", which uses os.pathsep.
+# If this key is omitted entirely, it falls back to the legacy behavior of splitting on spaces and/or commas.
+# Valid values for version_path_separator are:
+#
+# version_path_separator = :
+# version_path_separator = ;
+# version_path_separator = space
+version_path_separator = os  # Use os.pathsep. Default configuration used for new projects.
+
+# set to 'true' to search source files recursively
+# in each "version_locations" directory
+# new in Alembic version 1.10
+# recursive_version_locations = false
+
+# the output encoding used when revision files
+# are written from script.py.mako
+# output_encoding = utf-8
+
+sqlalchemy.url = driver://user:pass@localhost/dbname
+
+[post_write_hooks]
+# post_write_hooks defines scripts or Python functions that are run
+# on newly generated revision scripts.  See the documentation for further
+# detail and examples
+
+# format using "black" - use the console_scripts runner, against the "black" entrypoint
+# hooks = black
+# black.type = console_scripts
+# black.entrypoint = black
+# black.options = -l 79 REVISION_SCRIPT_FILENAME
+
+# lint with attempts to fix using "ruff" - use the exec runner, execute a binary
+# hooks = ruff
+# ruff.type = exec
+# ruff.executable = %(here)s/.venv/bin/ruff
+# ruff.options = --fix REVISION_SCRIPT_FILENAME
+
+# Logging configuration
+[loggers]
+keys = root,sqlalchemy,alembic
+
+[handlers]
+keys = console
+
+[formatters]
+keys = generic
+
+[logger_root]
+level = WARN
+handlers = console
+qualname =
+
+[logger_sqlalchemy]
+level = WARN
+handlers =
+qualname = sqlalchemy.engine
+
+[logger_alembic]
+level = INFO
+handlers =
+qualname = alembic
+
+[handler_console]
+class = StreamHandler
+args = (sys.stderr,)
+level = NOTSET
+formatter = generic
+
+[formatter_generic]
+format = %(levelname)-5.5s [%(name)s] %(message)s
+datefmt = %H:%M:%S
diff --git a/dags/migrations/env.py b/dags/migrations/env.py
new file mode 100644
index 0000000..9dd6c6c
--- /dev/null
+++ b/dags/migrations/env.py
@@ -0,0 +1,74 @@
+from logging.config import fileConfig
+
+from alembic import context
+from sqlalchemy import engine_from_config, pool
+
+# this is the Alembic Config object, which provides
+# access to the values within the .ini file in use.
+config = context.config
+
+# Interpret the config file for Python logging.
+# This line sets up loggers basically.
+if config.config_file_name is not None:
+    fileConfig(config.config_file_name)
+
+# add your model's MetaData object here
+# for 'autogenerate' support
+# from myapp import mymodel
+# target_metadata = mymodel.Base.metadata
+target_metadata = None
+
+# other values from the config, defined by the needs of env.py,
+# can be acquired:
+# my_important_option = config.get_main_option("my_important_option")
+# ... etc.
+
+
+def run_migrations_offline() -> None:
+    """Run migrations in 'offline' mode.
+
+    This configures the context with just a URL
+    and not an Engine, though an Engine is acceptable
+    here as well.  By skipping the Engine creation
+    we don't even need a DBAPI to be available.
+
+    Calls to context.execute() here emit the given string to the
+    script output.
+
+    """
+    url = config.get_main_option("sqlalchemy.url")
+    context.configure(
+        url=url,
+        target_metadata=target_metadata,
+        literal_binds=True,
+        dialect_opts={"paramstyle": "named"},
+    )
+
+    with context.begin_transaction():
+        context.run_migrations()
+
+
+def run_migrations_online() -> None:
+    """Run migrations in 'online' mode.
+
+    In this scenario we need to create an Engine
+    and associate a connection with the context.
+
+    """
+    connectable = engine_from_config(
+        config.get_section(config.config_ini_section, {}),
+        prefix="sqlalchemy.",
+        poolclass=pool.NullPool,
+    )
+
+    with connectable.connect() as connection:
+        context.configure(connection=connection, target_metadata=target_metadata)
+
+        with context.begin_transaction():
+            context.run_migrations()
+
+
+if context.is_offline_mode():
+    run_migrations_offline()
+else:
+    run_migrations_online()
diff --git a/dags/migrations/migrations.py b/dags/migrations/migrations.py
new file mode 100644
index 0000000..86f3161
--- /dev/null
+++ b/dags/migrations/migrations.py
@@ -0,0 +1,20 @@
+import os
+
+import pendulum
+from airflow.models import DAG
+from airflow.models.param import Param
+from airflow_provider_alembic.operators.alembic import AlembicOperator
+
+with DAG(
+    "migrations",
+    schedule=None,
+    start_date=pendulum.today("UTC").add(days=-1),
+    params={"command": Param("upgrade"), "revision": Param("head")},
+) as dag:
+    AlembicOperator(
+        task_id="alembic_op",
+        conn_id="superset_qa",
+        command="{{ params.command }}",
+        revision="{{ params.revision }}",
+        script_location=f"{os.environ['AIRFLOW_HOME']}/dags/migrations/",
+    )
diff --git a/dags/migrations/script.py.mako b/dags/migrations/script.py.mako
new file mode 100644
index 0000000..fbc4b07
--- /dev/null
+++ b/dags/migrations/script.py.mako
@@ -0,0 +1,26 @@
+"""${message}
+
+Revision ID: ${up_revision}
+Revises: ${down_revision | comma,n}
+Create Date: ${create_date}
+
+"""
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+${imports if imports else ""}
+
+# revision identifiers, used by Alembic.
+revision: str = ${repr(up_revision)}
+down_revision: Union[str, None] = ${repr(down_revision)}
+branch_labels: Union[str, Sequence[str], None] = ${repr(branch_labels)}
+depends_on: Union[str, Sequence[str], None] = ${repr(depends_on)}
+
+
+def upgrade() -> None:
+    ${upgrades if upgrades else "pass"}
+
+
+def downgrade() -> None:
+    ${downgrades if downgrades else "pass"}
diff --git a/dags/migrations/versions/64ac526a078b_my_db_revision.py b/dags/migrations/versions/64ac526a078b_my_db_revision.py
new file mode 100644
index 0000000..9f7be84
--- /dev/null
+++ b/dags/migrations/versions/64ac526a078b_my_db_revision.py
@@ -0,0 +1,50 @@
+"""My DB Revision
+
+Revision ID: 64ac526a078b
+Revises: 4438ef06e0c7
+Create Date: 2024-04-11 16:06:50.691527
+
+"""
+from typing import Sequence, Union
+
+import sqlalchemy as sa
+from alembic import op
+
+# revision identifiers, used by Alembic.
+revision: str = "64ac526a078b"
+down_revision: Union[str, None] = None
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade():
+    op.execute("CREATE SCHEMA IF NOT EXISTS oa")
+    op.create_table(
+        "oa.open_access",
+        sa.Column("year", sa.Integer, primary_key=True),
+        sa.Column("closed_access", sa.Integer, nullable=False),
+        sa.Column("bronze_open_access", sa.Integer, nullable=False),
+        sa.Column("green_open_access", sa.Integer, nullable=False),
+        sa.Column("gold_open_access", sa.Integer, nullable=False),
+        sa.Column("created_at", sa.TIMESTAMP(timezone=True), nullable=False),
+        sa.Column("updated_at", sa.TIMESTAMP(timezone=True), nullable=False),
+        schema="oa",
+    )
+
+    op.create_table(
+        "oa.golden_open_access",
+        sa.Column("year", sa.Integer, primary_key=True),
+        sa.Column("cern_read_and_publish", sa.Integer, nullable=False),
+        sa.Column("cern_individual_apcs", sa.Integer, nullable=False),
+        sa.Column("scoap3", sa.Integer, nullable=False),
+        sa.Column("other", sa.Integer, nullable=False),
+        sa.Column("other_colectives", sa.Integer, nullable=False),
+        sa.Column("created_at", sa.TIMESTAMP(timezone=True), nullable=False),
+        sa.Column("updated_at", sa.TIMESTAMP(timezone=True), nullable=False),
+        schema="oa",
+    )
+
+
+def downgrade():
+    op.drop_table("oa.golden_open_access", schema="oa")
+    op.drop_table("oa.open_access", schema="oa")
diff --git a/docker-compose.yaml b/docker-compose.yaml
new file mode 100644
index 0000000..6e923ab
--- /dev/null
+++ b/docker-compose.yaml
@@ -0,0 +1,22 @@
+services:
+  postgres:
+    image: docker.io/library/postgres:13
+    environment:
+      POSTGRES_USER: airflow
+      POSTGRES_PASSWORD: airflow
+      POSTGRES_DB: airflow
+    volumes:
+      - postgres-db-volume:/var/lib/postgresql/data
+    expose:
+      - 5432
+    ports:
+      - 5432:5432
+    healthcheck:
+      test: ["CMD", "pg_isready", "-U", "airflow"]
+      interval: 10s
+      retries: 5
+      start_period: 5s
+    restart: always
+
+volumes:
+  postgres-db-volume:
diff --git a/requirements-test.txt b/requirements-test.txt
index a3a4d9b..bb8c5df 100644
--- a/requirements-test.txt
+++ b/requirements-test.txt
@@ -1,4 +1,4 @@
-pre-commit==3.5.0
+pre-commit==3.6.0
 pytest==7.4.4
 coverage==7.4.0
 pytest-cov==4.1.0
diff --git a/requirements.txt b/requirements.txt
index ade786d..2f0a994 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,2 +1,4 @@
--c https://raw.githubusercontent.com/apache/airflow/constraints-2.8.1/constraints-3.8.txt
-apache-airflow[celery, postgres]==2.8.1
+-c https://raw.githubusercontent.com/apache/airflow/constraints-2.8.1/constraints-3.10.txt
+apache-airflow[celery, postgres, redis]==2.8.1
+alembic==1.13.1
+airflow-provider-alembic==1.0.0
diff --git a/tests/README.md b/tests/README.md
new file mode 100644
index 0000000..457b46c
--- /dev/null
+++ b/tests/README.md
@@ -0,0 +1,102 @@
+# BI-DAGs Setup Guide
+
+This README provides a step-by-step guide on setting up your environment for running BI-DAGs with Airflow.
+
+## Prerequisites
+
+Before you begin, ensure you have `pyenv` installed on your system. If you don't have `pyenv` installed, please follow the instructions [here](https://github.com/pyenv/pyenv#installation).
+
+## Installation Steps
+
+### 1. Set Up Python Environment
+
+First, we'll set up a Python environment using `pyenv`.
+
+\```sh
+
+# Define the desired Python version
+
+export PYTHON_VERSION=3.10.11
+
+# Install the specified Python version using pyenv
+
+pyenv install $PYTHON_VERSION
+
+# Set the global Python version to the installed one
+
+pyenv global $PYTHON_VERSION
+
+# Create a virtual environment named 'bi-dags'
+
+pyenv virtualenv $PYTHON_VERSION bi-dags
+
+# Activate the virtual environment
+
+pyenv activate bi-dags
+\```
+
+### 2. Install Dependencies
+
+With your virtual environment activated, install the necessary dependencies.
+
+\```sh
+pip install -r requirements.txt
+\```
+
+### 3. Navigate to Project Directory
+
+Change your current working directory to `bi-dags`.
+
+\```sh
+cd bi-dags
+\```
+
+### 4. Set Airflow Home
+
+Configure the Airflow home environment variable.
+
+\```sh
+export AIRFLOW_HOME=$PWD
+\```
+
+### 5. Configure Database Connection
+
+Export the database connection environment variable.
+
+\```sh
+
+# Replace 'your_db_connection_string' with your actual database connection string
+
+export AIRFLOW**CORE**SQL_ALCHEMY_CONN=your_db_connection_string
+\```
+
+### 6. Start Airflow
+
+Initialize and start Airflow using the standalone command.
+
+\```sh
+airflow standalone
+\```
+
+### 7. Start Postgres with Docker Compose
+
+If you're using Docker to manage your Postgres database, start the service.
+
+\```sh
+docker-compose start
+\```
+
+### 8. Add Airflow Connections via UI
+
+Lastly, add the necessary Airflow connections through the UI.
+
+- Navigate to Admin -> Connections in the Airflow UI.
+- Click on "Add" and fill in the details:
+  - Name: `SUPERSET_QA`
+  - Login: `airflow`
+  - Database: `airflow`
+  - Password: `airflow`
+  - Host: `localhost`
+  - Port: `5432`
+
+After completing these steps, your environment should be set up and ready for running BI-DAGs with Airflow.