Technical Analysis’ Post

It's rarely discussed, but the multi-class problem often exists in the business problem. A multi-class classification problem is a classification task that aims to classify the input into one of three or more distinct classes. It's different from binary classification, where there are only two possible outcomes (e.g., spam or ham). Multi-class classification involves selecting from more than two classes. There are two common strategies to approach multi-class classification: One-vs-All or One-vs-One. What are the differences? And what are the considerations for using them? Let's get into the detail. 👇👇👇 https://lnkd.in/gGbamHWU

Master Data Management to achieve a Single Source of Truth - Substack: Data Enrichment. Just buy a data enrichment tool and you're done right? · Data Normalization · Data Sources and Sync Intervals · Resolving Data Quality ...

Current status: experimenting with “foundational requirements” instead of “non-functional requirements”. If your system is slow, or down, or breached, or loses all your customers’ data, it doesn’t matter how wonderful its features are.

I just published my first article on Medium where I explore the challenges related to data-intensive applications.

Study says real-time log analysis reduces downtime by 40% A McKinsey study (https://lnkd.in/dq7DR9i9) suggests that real-time log and data analytics can reduce downtime by 40% (up to 50% in some cases). For software engineers across all verticals and industries, tools like Parseable help solve the problem of delays by identifying where the issue began. Benefits of Parseable’s real-time log analysis: ✔️Reduced Footprint: Parseable efficiently runs with low memory and CPU usage. ✔️Increased Speed: Parseable ingests and queries logs at high speed with minimal latency. ✔️Schema-Free Simplicity: Parseable ingests any log format without complex configuration. ✔️Future-Proof Storage: Parseable leverages Parquet for scalable log data storage and analysis. We’re building Parseable to ensure businesses can quickly respond to anomalies, optimize system performance, and significantly reduce downtime. As the digital landscape becomes increasingly complex, the need for powerful, flexible log management solutions grows. Parseable provides a simple yet powerful platform to streamline log analysis and reduce operational disruptions. Get started with Parseable in just a single command: https://lnkd.in/d_bvmUt8

The Index Overload: A Story of Tuning Success Problem Statement: ❌Faced a challenge with slow DML operations (insert, delete, update) on a 24.5GB table with millions of records. ❌Processes were dragging on endlessly, causing system locks, crashes, and frustration for the business. Root Cause Analysis: ➝In the RCA, I discovered the table had 12 columns with 110 indexes ➝Too many indexes planned for efficient Retrieval-processing. ➝Excessive indexes were causing overhead, slowing down DML on table After discussing with the stakeholders, and linking processes: ✔I trimmed down the indexes, removing those that were not needed. ✔Ended up with only 4-5 critical indexes, finely tuned for the key queries The result? A night and day difference! ✔The operations that were once taking forever now completed in just a few seconds! The Business Value: ➝Faster DML operations = Improved overall system efficiency. ➝Reduced system crashes and locks, ensuring smoother workflows. ➝Increased productivity, allowing the business to focus on growth, not troubleshooting. Lesson learned: Indexes are good, only when used wisely. If you don’t need them, drop them. This was a tough battle, but winning it brought immense satisfaction, knowing we’d restored performance and unlocked real business value. #DatabaseTuning #PerformanceOptimization #IndexManagement

Adding custom data to your payload has some great advantages: 🛠️ 1. Understand the root cause of an error more easily 2. Better understand the business impact of an error 3. Make an automated response decision Learn how to apply these here

"As days and weeks pass, the POC remains operational and an internal IT team is tasked with its production management. Then, the unexpected occurs. The POC’s stability falters, its performance falls short of expectations, or its integration with other systems becomes a struggle. With each passing day, more members of the IT team are required to invest time in managing and enhancing the POC. However, due to the novelty of the technology, they often lack the expertise needed to effectively optimize it. Compounding the issue, the vendor’s inadequate support model exacerbates the situation, failing to address the ongoing challenges." Read “Once You POC, You (Can’t) Stop!“ by janmeskens on Medium:

Why Memory<T> Matters 🚀Boost Performance with Memory<T> When working with large datasets, optimizing performance is crucial. In such cases, using Memory<T> can make a significant impact. Why Use Memory<T>? ● Performance: Avoids unnecessary copying of data, making operations more efficient. ● Flexibility: Unlike Span<T>, Memory<T> can be passed to asynchronous methods, making it ideal for async processing pipelines. Difference Between Span<T> and Memory<T> ● Span<T>: ▪ Stored on the stack. ▪ Designed for synchronous modification of an array segment. ● Memory<T>: ▪ Stored on the managed heap. ▪ Suitable for asynchronous processing. Both are powerful wrappers over buffers of structured data, making them indispensable in performance-critical pipelines. By using Span<T> and Memory<T>, you can reduce memory allocations significantly and enhance your application’s performance.

Reliability at Your Fingertips: Affordable Solutions for Independent Professionals! As an independent professional, you deserve the best tools to ensure product reliability without breaking the bank. With Reliability4All, we offer a Basic Reliability Suite starting at just $12.99/month. The Basic Reliability Suite includes: ✔️ Life Data Analysis (LDA) ✔️ Reliability Growth Analysis (RGA) ✔️ Degradation Analysis (DA) ✔️ Reliability Test Design (RTD) Elevate your work with advanced features designed to meet the needs of solo engineers, researchers, and small teams. Why pay for expensive enterprise solutions when you can access high-quality reliability tools for less? #ReliabilityAtAffordablePrices #ProductTesting #IndependentProfessionals #LifeDataAnalysis #SmallBusinessSolutions #ReliabilityGrowth #TechToolsForEveryone #AffordableSolutions