Press "Enter" to skip to content

Author: Kevin Feasel

Creating a Generic SSRS Report

Published 2022-04-04 by Kevin Feasel

Tim Mitchell breaks out the black print on white cardboard:

When a simple presentation of data is needed, SQL Server Reporting Services (SSRS) is a common tool of choice. Creating simple tabular, row-and-column type reports can be done relatively quickly and easily in SSRS. But what happens if you need a lot of these reports? If you need to present dozens or even hundreds of reports to end users, building even a simple report for each one can take time. Unfortunately there’s no Biml-like automation tool for SSRS, so this work must typically be done by hand.

However, it is possible to create a generic report in SSRS that can dynamically present information from tables or views. In this post, I’ll share my implementation of this.

Looking at Tim’s solution, I’d be a bit concerned about longer-term maintenance. In particular, my worry would be that what you gain in ease of development, you give away in making troubleshooting and report maintenance harder.

Comments closed

Emphasizing One Data Point in Excel

Published 2022-04-04 by Kevin Feasel

Elizabeth Ricks makes a point:

Today’s post is a tactical one: how to highlight a data point in Excel. 

When we craft visualizations for explanatory purposes—that is, when there’s a specific finding or recommendation that we want to communicate to someone specific—our goal is to drive action. In those cases,  our visuals should emphasize what’s interesting in the data and what requires attention. Highlighting key points in our graph is an important step in creating successful explanatory communications.

Read on for examples as well as how to do this.

Comments closed

PRECEDING and FOLLOWING in Window Functions

Published 2022-04-04 by Kevin Feasel

Reitse Eskens looks at a couple of useful window operators:

I was teaching a class today on more advanced SQL queries and we were discussing if you could use preceding and following in a single windowing function.

Windowing Functions

If you’re not familiar with windowing functions, they’re really cool. You can perform all kinds of trickery and magic with them. Let’s start with a simple example.
The dataset I’m using has flight data from the early 2000’s.

Read on for the example and for the answer to Reitse’s question.

Comments closed

Monitoring Kubernetes in Production

Published 2022-04-04 by Kevin Feasel

Samir Behara provides some guidance:

Kubernetes is an open-source container orchestration system for automating the deployment and management of containerized applications. Kubernetes provides capabilities like service discovery, horizontal autoscaling, and load balancing, while ensuring that application configurations are declarative and that systems are self-healing.

In this article, I will explain how to monitor your Kubernetes cluster and implement automated health checks, and discuss the various monitoring tools available.

Read on for some thoughts. In addition to Samir’s links and ideas, I’d also throw in some tools like Rancher to make management a little easier.

Comments closed

Synonyms in SQL Server

Published 2022-04-04 by Kevin Feasel

Chad Callihan looks at synonyms in SQL Server:

Are you familiar with synonyms as they relate to SQL Server? I haven’t seen them used too much out in the wild but understand they can have benefits. Let’s take a look at what synonyms are in SQL Server and some common reasons for implementing them.

My recollection is that synonyms have some limitations which make them not as useful as they’d first appear. But the bigger reason I think we don’t see synonyms used very often is that they obscure information and make it tougher to understand what’s really happening. In that respect, it’s a bit similar to a trigger: useful but sometimes painful to debug because it obscures relevant information.

Comments closed

An Overview of Azure IoT Central

Published 2022-04-04 by Kevin Feasel

James Serra looks at IoT Central:

This is a short blog to give you a high-level overview on a product called Azure IoT Central. I saw this fairly new Azure product (GA Sept 2018) in use for the first time at a large manufacturing company who was using it at their manufacturing facility (see Grupo Bimbo takes a bite out of production costs with Azure IoT throughout factories). They have thousands of sensors that are collecting data for all the machines used in producing their products. In short, think of it as an “Application Platform as a Service (aPaas)” for quickly building IoT solutions. It’s boxing up IoT hub, Device Provisioning Service (DPS), Stream Analytics, Data Explorer, SQL Database, Time Series Intelligence and Cosmos DB to make it easy to quickly build a solution and get value out of the IoT data. To get an idea of the what this solution would look like, check out the IoT Central sample for calculating Overall Equipment Effectiveness (OEE) of industrial equipment.

I haven’t seen much use of this service, as generally any use case I’ve seen around IoT quickly turns into using IoT Hub and IoT Edge to develop custom code.

Comments closed

An Overview of the Microsoft Defender Ecosystem

Published 2022-04-01 by Kevin Feasel

Alan La Pietra looks at all the Defenders you can get your hands on:

Microsoft Defender Antivirus is available in Windows 10 and Windows 11, and in versions of Windows Server

Microsoft Defender Antivirus is a major component of your next-generation protection in Microsoft “Defender for Endpoint”

Microsoft Defender Antivirus is built into Windows, and it works with Microsoft Defender for Endpoint to provide protection on your device and in the cloud

I see the hand of marketing in this. Which means they’ll probably all have different names nine months from now.

Comments closed

An Overview of Automatic Text Summarization

Published 2022-04-01 by Kevin Feasel

Kevin Jacobs looks at the state of the art with respect to automatic text summarization:

Automatic text summarization comes in two flavours: extractive summarization and abstractive summarization. Extractive summarization models take exact phrases from the reference documents and use them as a summary. One of the very first research papers on (extractive) text summarization is the work of Luhn [1]. TextRank [2] (based on the concepts used by the PageRank algorithm) is another widely used extractive summarization model.

In the era of deep learning, abstractive summarization became a reality. With abstractive summarization, a model generates a text instead of using literal phrases of the reference documents. One of the more recent works on abstractive summarization is PEGASUS [3] (a demo is available at HuggingFace).

Click through for a couple contemporary examples as well as a few pain points you can experience when using the current set of libraries and algorithms.

Comments closed

Lists in Power Query

Published 2022-04-01 by Kevin Feasel

Ed Hansberry makes a list and checks it twice:

Lists in Power Query are something many people know nothing about. Power Query uses them all the time even though you may not realize it, so if you add some List knowledge to your quiver, you’ll be able to kick your Power Query skills up a notch.

In my work, I often see the need for counting words, especially today with so much online data. Perhaps you want to ensure your Amazon product listings have a maximum number of words in the descriptions or you want to count the words in a podcast. The method I’m going to show you will count anything in your data, so you can apply this pattern to any of your datasets.

Also known as map and reduce (but not quite MapReduce).

Comments closed