Fine-grained Access Control for Stored Procedures

Fine-grained access control for stored procedures using a programmable database proxy

Power BI Treemap Chart Step-by-Step Tutorial

Microsoft Power BI Desktop provides a wide variety of visuals to its users. Sometimes, one wants to conduct a comparative analysis, a simple way to explore the relationship between the data categories within a set hierarchy. Hence, when a decision revolves around understanding the relationship of each element, this visual can provide an insightful analysis. This article will highlight all the steps to create a treemap chart in Power BI Desktop.

Memory Grant Feedback Persistence in SQL Server 2022

By using input from real memory consumption during query execution, Memory Grant input Persistence in SQL Server 2022 is a potent feature that helps optimize query performance. In order to improve the accuracy of memory grant calculations for subsequent executions of the same or comparable queries, SQL Server gathers and stores this information.

On Being an "Expert"

I had the opportunity last week to present a session at DataSaturdays Stockholm. I can't say enough nice things about the event and the organizers. I presented on Query Store in SQL Server. In my mind, it's an entry-level to middle tier presentation. Most of the room was already working with Query Store, some quite […]

Adding Hints with Query Store

Enhancing Web Application Performance through Database Optimization: A Comprehensive Study

In the contemporary digital landscape, web applications play a pivotal role in delivering services and facilitating interactions between users and businesses. However, the performance of these applications heavily relies on the efficiency of underlying databases. This comprehensive study aims to explore the intricate relationship between database optimization techniques and web application performance enhancement. The study begins by delineating the significance of web application performance and its correlation with database operations. It examines various factors affecting performance, including data retrieval, storage, and processing. Furthermore, it identifies common challenges such as latency, scalability issues, and inefficient query execution. Through an extensive review of the literature, this study evaluates state-of-the-art database optimization methodologies and their applicability to web applications. Techniques such as indexing, query optimization, denormalization, caching mechanisms, and data partitioning are scrutinized, highlighting their potential to mitigate performance bottlenecks. Moreover, the study investigates emerging trends and technologies in database management systems (DBMS), such as NoSQL databases, in-memory databases, and cloud-based solutions. It assesses their suitability for enhancing web application performance, considering factors like data volume, query complexity, and real-time processing requirements.

Multiple Query Trace Flags

How Big Data Supports Gen AI

This article includes an overview of how big data and Artificial Intelligence (AI) models work together.

Combining Silver Tables into a Model – Data Engineering with Fabric

This next article in the series creates objects at the gold layer for consumption by combining tables from the silver layer of the lake house.

Using Machine Learning Pipeline Execution Activity in Azure Data Factory

This article shows how one can run a machine learning activity in an Azure Data Factory (ADF) pipeline.