Frustrated with handling data type conversion issues in python? Then this post is for you. In this post, we go over a reusable data type conversion pattern using Pydantic. We will also go over the caveats involved in using this library.
Frustrated that hiring managers are not reading your Github projects? then this post is for you. In this post, we discuss a way to impress hiring managers by hosting a live dashboard with near real-time data. We will also go over coding best practices such as project structure, automated formatting, and testing to make your code professional. By the end of this post, you will have deployed a live dashboard that you can link to your resume and LinkedIn.
Unable to find practical examples of idempotent data pipelines? Then, this post is for you. In this post, we go over a technique that you can use to make your data pipelines professional and data reprocessing a breeze.
Working with a dataset that is too large to fit in memory? Then this post is for you. In this post, we will write memory efficient data pipelines using python generators. We also cover the common generator patterns you will need for your data pipelines.
If you are overwhelmed with re-engineering a legacy data pipeline, then this post is for you. In this post, we go over 6 key principles to help you figure out the most impactful data features for your end user and how to deliver them.
Wondering how to execute a spark job on an AWS EMR cluster, based on a file upload event on S3? Then this post if for you. In this post we go over how to trigger spark jobs on an AWS EMR cluster, using AWS Lambda. The lambda function will execute in response to an S3 upload event. We will go over this event driven pattern with code snippets and set up a fully functioning pipeline.
Setting up an ELT data-ops workflow with multiple environments for developers is often extremely time consuming. What if there was a way to speed up this process, so that you could concentrate on modeling your data and delivering value to your end users? The good news is that there is a way. You can leverage dbt cloud to setup an ELT data-ops workflow in a very short time. In this post, we cover how to setup a data-ops workflow for an ELT system. We will go over how to setup dbt, snowflake, CI and schedule jobs. This data-ops workflow can be easily modified and built upon as your data team's needs evolve.
Spending hundreds of thousands of dollars on vendor BI tools ? Looking for a clean open source alternative ? Then this post is for you. In this post we go over Apache Superset, which is one of the most popular open source visualization tools. We will go over its architecture and build charts and dashboards to visualize data. We will end with a list of pros and cons with using an open source visualization tool like Apache Superset.
Wondering how to store a dimension table's history over time and how to join these historical dimension tables with fact tables for analytical querying ? Then this post is for you. In this post, we will go over a popular dimension modeling technique called SCD2, which preserves historical changes. We will also see how to join a fact table with an SCD2 table to get accurate point in time information.
Whenever updating a few records in an OLTP table we just use the update command. But what if we have to update millions of records in an OLTP table? If you run a large update, your database will lock those records and other transactions may fail. In this post we look at how a large update can cause lock timeout error and how running batches of smaller updates can eliminate this issue.