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Day: May 14, 2024

Data Quality Issues in Python-Based Time Series Analysis

Published 2024-05-14 by Kevin Feasel

Hadi Fadlallah checks out the data:

Time-series data analysis is one of the most important analysis methods because it provides great insights into how situations change with time, which helps in understanding trends and making the right choices. However, there is a high dependence on its quality.

Data quality mistakes in time series data sets have implications that extend over a large area, such as the accuracy and trustworthiness of analyses, as well as their interpretation. For instance, mistakes can be caused by modes of data collection, storage, and processing. Specialists working on these data sets must acknowledge these data quality obstacles.

Read on for several examples of data quality issues you might run into in a time series dataset, as well as their fixes.

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Checking if a Column Exists in an R Data Frame

Published 2024-05-14 by Kevin Feasel

Steven Sanderson takes a peek:

When working with data frames in R, it’s common to need to check whether a specific column exists. This is particularly useful in data cleaning and preprocessing, to ensure your scripts don’t throw errors if a column is missing. Today, we’ll explore several methods to perform this check efficiently in R, and I encourage you to try these methods out with your own data sets.

Read on for four ways to do this.

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Including a SQL Query in an Expression in SSRS

Published 2024-05-14 by Kevin Feasel

Slava Murygin shares a tip:

Why: Most of the time, when you want a flexibility of your SQL query you can use parameterization. However there might be a situation when you’d need to build a dynamic query. In my case I used SQL query within an expression to feed it to multiple data sources targeting different servers with the exact same query.

Read on to see what Slava has fought with in the past.

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Optimized Column Order for Indexes

Published 2024-05-14 by Kevin Feasel

Eitan Blumin talks indexing:

SQL Server performance optimization is not a simple topic, and index design plays a pivotal role in it, determining the efficiency of database queries.

One key aspect that often influences performance is the order of columns in an index.

In this guide, I’ll use my real-world experience from our consulting jobs to examine the thinking process behind selecting the best column sequence for an index, the logic behind the decisions, and offer some practical insights for optimal database performance.

Read on to learn more about indexing strategy. And this is probably a good time to remind people that the missing index DMV’s column order has as its sole basis the column’s ordinal value. You can, and often will, do better than the missing index DMV recommendation by going through Eitan’s exercise.

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Optimized Locking in Azure SQL Database

Published 2024-05-14 by Kevin Feasel

Bob Pusateri locks the door:

One of the newer features introduced in Azure SQL Database is “Optimized Locking”. But what does that mean, and how does it compare to the apparently “un-optimized” locking the SQL relational engine has been using up to this point? Let’s dive in and take a look.

Read on to learn more about optimized locking and how it compares to the traditional form of locking available in SQL Server today.

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