azure services

Apache Airflow: Monitor and manage the data pipelines and complex workflows
Ali Mohsin
| December 3, 2022

Data Science Dojo is offering Apache Airflow for FREE on Azure Marketplace packaged with a pre-configured web environment of Airflow with various data analytics features.  

  

Introduction:  

In this era of tighter data restrictions, it is more important than ever to understand, analyze, and manage your data throughout its lifecycle. It is harder than ever as data volumes rise, and data pipelines get more complicated. A solution is needed Organizations or Individuals must have a complete, scalable, easy-to-analyze platform to manage and monitor the complex workflows and support several integrations. 

 

What is Apache Airflow?  

Apache Airflow, a powerful open-source tool for authoring, scheduling, and monitoring data and computational workflows. It provides a method that makes it easier to manage, schedule, and coordinate complicated data pipelines from several sources. 

 

What is DAG? 

A DAG, or Directed Acyclic Graph, in Airflow is a list of all the jobs you wish to execute, arranged to reflect their connections and dependencies. A Python script that expresses the DAG’s structure as code defines a DAG. Researchers’ priori ideas about the connections between and among variables in causal structures are encoded using DAGs. It contains directed edges (arrows), linking nodes (variables), and their paths. Hence A workflow is represented as a DAG, which consists of discrete units of work called Tasks that are ordered considering relationships and data flows. 

 

Apache Airflow Architecture: 

This powerful and scalable workflow scheduling software is made up of four key parts: 

  • Scheduler: The scheduler keeps track of all DAGs and the jobs they are connected to. To start, it frequently checks the list of open tasks. 
  • Web server: The user interface for Airflow is the web server (The default port Apache Airflow listens to is 8080). It displays the status of the jobs, gives the user access to the databases, and lets them read log files from other remote file stores like Microsoft Azure blobs. 
  • Database: To make sure the schedule retains metadata information, the state of the DAGs and the tasks they are connected to, are saved in the database. The scheduler scans each DAG and records essential data, including schedule intervals, run-by-run statistics, and task instances. 
  • Executors: There are various kinds of executors for different use cases. Few examples of Executors are  SequentialExecutor, LocalExecutor, CeleryExecutor, and KubernetesExecutor 

  

(With SequentialExecutor, just one task may be carried out at once. No parallel processing is possible. It is useful when testing or debugging. LocalExecutor supports hyperthreading and parallelism. It is excellent for using Airflow on a single node or a local workstation. CeleryExecutor is usually used for managing a distributed Airflow cluster. While using the Kubernetes API, the KubernetesExecutor creates temporary pods for each of the task instances to run in.) 

 

Key features Apache Airflow provides: 

  • Dynamic Pipelines can be constructed by Airflow dynamic, also as it is constructed in the form of code which gives an edge to dynamic behavior. 
  • Apache Airflow has a rich User Interface that helps the user to manage their workflow easily 
  • It gives a separate code view pallet that enables users to view their DAGs code as well.  
  • Allows users to visualize their DAGs in different forms like Gantt chart, Tree, and Graph. 
  • With ready to use operators in airflow, users can work with various cloud platforms like Microsoft Azure, AWS (Amazon Web Services) etc. 
  • Allows role-based user management to maintain Security and Accessibility.

 

Apache Airflow with Azure services: 

Apache Airflow leverages the power of Azure services to make the procedure of monitoring and managing complex workflows intuitively. Also with Azure, Airflow made it a more scalable data warehousing platform. Airflow enables users to work in a scalable environment. 

 

Conclusion:  

Other open-source Data Engineering solutions put intense competition on Apache Airflow. But it is one of the most robust platforms used by Data Engineers for orchestrating workflows or pipelines. Users can easily visualize your data pipelines’ dependencies, progress, logs, code, trigger tasks, and success status all in a single package.  

At Data Science Dojo, we deliver data science education, consulting, and technical services to increase the power of data. We therefore know the importance of data and the encapsulated insights. Through this offer, we are confident that you can analyze, visualize, and query your data in a collaborative environment with greater ease. 

Install the Apache Airflow offer now from the Azure Marketplace by Data Science Dojo, your ideal companion in your journey to learn data science! 

Click on the button below to head over to the Azure Marketplace and deploy Apache Airflow for FREE by clicking on “Try now.”  

 

CTA - Try now

 

Note: You’ll have to sign up to Azure, for free, if you do not have an existing account. 

Ali Mohsin
| July 6, 2022

Data Science Dojo has launched one of the most in-demand data analytics software, Redash as a virtual machine offer on the Azure Marketplace.

Introduction

With the rising complexity of the data, organizations must have complete control over their data. Sometimes there is a hindrance for the analysts in the specific use cases. Especially when working internally with a dedicated team that requires unlimited access to information. A solution is needed to perform the data-driven tasks efficiently and extract actionable insights.

What is Redash?

Redash, a data analytics tool, assists organizations to become more data-driven by providing tools to democratize data access. It simplifies the creation of dashboards and makes visualizations of your data by connecting to any data source. 

Data analysis with Redash

As a Business Intelligence tool, it has more powerful integration capabilities than other Data Analytics platforms, making it a favorite among businesses that have implemented a variety of apps to manage their business processes. Similarly, according to the reviewer’s point-of-view, they found it to be more user-friendly, manageable, and business-friendly in comparison with other platforms.

PRO TIP: Join our Data Science Bootcamp to learn more about data analytics.

analytics graphs
Data Analytics with Redash

Key features of Redash

  • It offers a user-friendly graphical user interface to carry out complex tasks with a few clicks.
  • Allows users to deal with small as well as big data, it supports many SQL and NoSQL databases.
  • The Query Editor allows users to query the database by utilizing the Schema Browser and autocomplete features.
  • Users can utilize the drag-and-drop feature to build visualizations (like charts, boxplot, cohort, counter, etc.) and then merge them into a single dashboard.
  • Enables peer evaluation of reports and searches and makes it simple for users to share visualizations and the queries that go with them.
  • Allows charts and dashboards to be updated automatically at defined time intervals.

Redash with Azure Services

It leverages the power of Azure services to make the procedure of integration with data sources quickly. Write SQL queries to pull subsets of data for visualizations and plot different charts and share dashboards within the organization with greater ease.

Conclusion

Other open-source business intelligence solutions put strong competition on Redash. Deciding to invest in business intelligence and data analysis tool can be challenging because all corporate departments, including product, finance, marketing, and others, now use multiple platforms to carry out day-to-day operations and carry out analytics tasks to strengthen their control over data.

At Data Science Dojo, we deliver data science education, consulting, and technical services to increase the power of data. We, therefore, know the importance of data and encapsulated insights. Through this offer, we are confident that you can analyze, visualize, and query your data in a collaborative environment with greater easeInstall the Redash offer now from the Azure Marketplace by Data Science Dojo, your ideal companion in your journey to learn data science!

Try Redash!

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