![Advanced analytics with SQL PIVOT](https://note.datengineer.dev/posts/pivot-and-dynamic-pivot-in-sql-advanced-sql-for-analytics/images/data-engineer-advanced-sql-pivot-and-dynamic-pivot.png)
PIVOT and Dynamic PIVOT in SQL - Advanced SQL for analytics
As a data engineer, a typical working day for me, apart from meetings, is full of SELECT, FROM and WHERE. But these basic statements are not enough, especially for the complex ad hoc analysis that is increasingly common nowadays. SQL is a powerful language. It is a declarative language where we define what we want and the engine finds a way to achieve it. The language is evolving to adapt to the increasing variety of analysis needs....
How to create Azure DevOps Pull Requests reporting with Power BI
As a developer, I have always emphasized the importance of code quality and efficient development processes. Modern Git workflows are typically about writing code, commits, pull requests, code reviews, and merges. To gain deeper insight into these processes, I decided to create a Power BI report to track them. My goal is to identify bottlenecks, areas for improvement, and opportunities to streamline our workflow. Pre-requisites Before we dive into building the Power BI report, you must have Power BI Desktop of course....
How to start a successful Data Warehouse project
Any organization aiming to leverage the power of data-driven decision-making stands to benefit greatly from a successful Data Warehouse project. A well-designed Data Warehouse not only centralizes your data but also guarantees that it is reliable, scalable, maintainable, and usable by stakeholders. Over the past few months, my team and I have launched a new Data Warehouse project in production. The opportunity to start from scratch is always a valuable chance to gain new insights and expertise....
Understand Row-Oriented vs Column-Oriented Storage
The way we access and analyze data has changed a lot lately. Row-oriented storage, which has been the standard for data storage for a long time, is having trouble keeping up with the demands of modern data analysis. In this article, I will introduce you to column-oriented storage and how it can help analytical queries run faster. OLAP In my previous post, we discussed the differences between Online Analytical Processing (OLAP) and Online Transaction Processing (OLTP)....
![OLTP vs OLAP Differences](https://note.datengineer.dev/posts/oltp-olap-why-we-need-data-warehouse/images/oltp-vs-olap-cover.png)
OLTP & OLAP - Why we need Data Warehouse
Today, I was advising a team on building their data warehouse solution. I realized that even 40 years after the term “data warehouse” was first introduced, there are still questions about why we need a data warehouse and why we don’t get all of the data from application databases, especially by executives. I write this post to answer these questions by clarifying the terms OLTP and OLAP, which are frequently used in discussions about data warehouse database architecture....
Recursive CTEs and CONNECT BY in SQL to query Hierarchical data
In database design, the idea of hierarchical data represents relationships between entities as a tree-like structure. This type of data model is widely used in many domains, such as file systems, organizational structure, etc. When dealing with hierarchical data, it is crucial to efficiently query and extract information about the relationships between entities. In this post, we will explore two powerful SQL tools for querying hierarchical data: recursive Common Table Expressions (CTEs) and the CONNECT BY clause....