Geek Logbook

Tech sea log book

Recent Posts

Categories

#50projectsIn50days Airflow Amazon Web Services Apache Iceberg AWS Azure bash Batch CAP Coders At Work Data data lakes Data Warehouse Docker Edsger W. Dijkstra Excel Git Hadoop HDFS Hellerstein Hive Javascript Networking NoSql Postman Power Bi Powershell Pyspark Python Redash S3 Social Skills Software Developer Spark Spark: The Definitive Guide SQL SSH terraform Testing The Elements of Programming Style Traversy Media Understanding Distributed Systems Virtual Box whale-alert Yaml

Archives

Creating a Running Total in SQL Server with Window Functions

Introduction Calculating a running total is a common requirement in many data analysis tasks, such as tracking cumulative sales, computing cumulative scores, or keeping track of inventory levels. In SQL Server, window functions provide an efficient and straightforward way to calculate running totals. In this post, we’ll explore how to use window functions, particularly the
Read More

Using the OVER() Clause with Window Functions in SQL Server

Introduction SQL window functions have become an indispensable tool for data analysts and developers. They allow for advanced calculations that go beyond simple aggregates, enabling analysis over a set of table rows related to the current row. The OVER() clause is fundamental in defining how these window functions operate, allowing you to partition data, order
Read More

Splitting Strings and Accessing Elements in Azure Data Factory

Introduction Azure Data Factory (ADF) is a powerful cloud-based data integration service that allows you to create data-driven workflows for orchestrating and automating data movement and data transformation. When working with data, it’s common to encounter situations where you need to manipulate strings, such as splitting a string by a delimiter and accessing specific elements.
Read More

Extracting Year, Month, and Day from Dates in Azure Data Factory

In Azure Data Factory (ADF), working with dates is a common task, especially when dealing with data transformations and scheduling tasks. ADF allows you to handle dates in different formats, such as timestamps and strings. This blog post will guide you on how to extract the year, month, and day from two types of dates:
Read More

Understanding Window Functions in SQL: A Deep Dive

Introduction When working with databases, you’ll often need to perform calculations across a set of rows related to the current row in your query. Whether you’re calculating a running total, ranking rows, or performing other complex aggregations, window functions in SQL provide a powerful way to achieve these tasks without resorting to more complicated subqueries
Read More

Extracting the Header from a CSV File in Python

When working with CSV files in Python, it’s often necessary to extract the header (the first row of the file) to understand the structure of the data or to perform specific operations on the remaining rows. In this post, we’ll explore how to extract the header using Python’s csv module. Using csv.reader to Extract the
Read More

How to Check if Two Tables Have the Same Columns in SQL

When working with databases, it’s sometimes necessary to compare two tables to ensure they have the same structure. Specifically, you might need to verify that two tables have the same columns before performing operations like data migrations or comparisons. This post will guide you through the process of checking if two tables have identical columns
Read More

Identifying Duplicate Records in SQL Based on Specific Fields

In database management, identifying and handling duplicate records is crucial to ensure data integrity. This post will guide you through a SQL query designed to find duplicates based on a specific field. For this example, we’ll work with a table containing raw data and extract relevant information to identify duplicates. Understanding the Query Let’s say
Read More