turbaszek commented on a change in pull request #272:
URL: https://github.com/apache/airflow-site/pull/272#discussion_r453817450
##########
File path: landing-pages/site/content/en/blog/apache-airflow-for-new-comers.md
##########
@@ -0,0 +1,51 @@
+---
+title: "Apache Airflow For New Comers"
+linkTitle: "Apache Airflow For New Comers"
+author: "Ephraim Anierobi"
+twitter: "@ephraimbuddy"
+github: "@ephraimbuddy"
+description: "Description"
+tags: []
+date: "2020-07-12"
+draft: true
+---
+
+Apache Airflow is a platform to programmatically author, schedule and monitor
workflows.
+A workflow is a sequence of tasks that processes a set of data. You can think
of workflow
+as the path that describes how tasks go from being undone to done.
+Scheduling, on the other hand, is the process of planning, controlling and
optimizing when
+a particular task should be done.
+
+### Authoring Workflow in Apache Airflow.
+Apache Airflow makes it super easy to author workflows using python scripts in
a DAG file. An
+acronym for Directed Acyclic Graph. The DAG houses a collection of tasks in a
way that
+shows each task's relationships and dependencies. You can have as many DAGs as
you want, and
+Airflow will execute them respecting their relationships and dependencies.
+If a task B depends on successful execution of another task A, it means
airflow will run task
+A and only run task B after task A. This dependency is very easy to express in
Airflow.
+For example, the above scenario is expressed in DAG as:
+
+```task_A >> task_B```
+
+Also equivalent to
+
+```task_A.set_downstream(task_B)```
+
+That helps airflow to know that it need to execute task A before task B.
+
+There are many inbuilt operators that makes task creation very easy. Remember,
a task could just
Review comment:
```suggestion
There are many builtin operators that makes task creation very easy.
Remember, a task could just
```
##########
File path: landing-pages/site/content/en/blog/apache-airflow-for-new-comers.md
##########
@@ -0,0 +1,51 @@
+---
+title: "Apache Airflow For New Comers"
+linkTitle: "Apache Airflow For New Comers"
+author: "Ephraim Anierobi"
+twitter: "@ephraimbuddy"
+github: "@ephraimbuddy"
+description: "Description"
+tags: []
+date: "2020-07-12"
+draft: true
+---
+
+Apache Airflow is a platform to programmatically author, schedule and monitor
workflows.
+A workflow is a sequence of tasks that processes a set of data. You can think
of workflow
+as the path that describes how tasks go from being undone to done.
+Scheduling, on the other hand, is the process of planning, controlling and
optimizing when
+a particular task should be done.
+
+### Authoring Workflow in Apache Airflow.
+Apache Airflow makes it super easy to author workflows using python scripts in
a DAG file. An
+acronym for Directed Acyclic Graph. The DAG houses a collection of tasks in a
way that
+shows each task's relationships and dependencies. You can have as many DAGs as
you want, and
+Airflow will execute them respecting their relationships and dependencies.
+If a task B depends on successful execution of another task A, it means
airflow will run task
+A and only run task B after task A. This dependency is very easy to express in
Airflow.
+For example, the above scenario is expressed in DAG as:
+
+```task_A >> task_B```
+
+Also equivalent to
+
+```task_A.set_downstream(task_B)```
Review comment:
```suggestion
```python
task_A.set_downstream(task_B)
```
```
##########
File path: landing-pages/site/content/en/blog/apache-airflow-for-new-comers.md
##########
@@ -0,0 +1,51 @@
+---
+title: "Apache Airflow For New Comers"
+linkTitle: "Apache Airflow For New Comers"
Review comment:
```suggestion
title: "Apache Airflow For Newcomers"
linkTitle: "Apache Airflow For Newcomers"
```
##########
File path: landing-pages/site/content/en/blog/apache-airflow-for-new-comers.md
##########
@@ -0,0 +1,51 @@
+---
+title: "Apache Airflow For New Comers"
+linkTitle: "Apache Airflow For New Comers"
+author: "Ephraim Anierobi"
+twitter: "@ephraimbuddy"
+github: "@ephraimbuddy"
+description: "Description"
+tags: []
+date: "2020-07-12"
+draft: true
+---
+
+Apache Airflow is a platform to programmatically author, schedule and monitor
workflows.
+A workflow is a sequence of tasks that processes a set of data. You can think
of workflow
+as the path that describes how tasks go from being undone to done.
+Scheduling, on the other hand, is the process of planning, controlling and
optimizing when
+a particular task should be done.
+
+### Authoring Workflow in Apache Airflow.
+Apache Airflow makes it super easy to author workflows using python scripts in
a DAG file. An
+acronym for Directed Acyclic Graph. The DAG houses a collection of tasks in a
way that
+shows each task's relationships and dependencies. You can have as many DAGs as
you want, and
+Airflow will execute them respecting their relationships and dependencies.
+If a task B depends on successful execution of another task A, it means
airflow will run task
+A and only run task B after task A. This dependency is very easy to express in
Airflow.
+For example, the above scenario is expressed in DAG as:
+
+```task_A >> task_B```
Review comment:
```suggestion
```python
task_A >> task_B
```
```
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