Hacker Combat™’s Post

Threat intelligence

Day 12 of #30DaysWebChallenge: Foreign Keys in databases! They're like the secret agents linking tables, making sure your data communicates smoothly. Think of it as a guide, helping your tables understand each other better. #ForeignKey #CodingJourney

Structured data is a standardized format for providing information about a webpage and classifying its content.

How does OpenSearch work? How does opensearch work? OpenSearch is an open-source search and analytics suite. Developers build solutions for search and more! Read mode on following blog post!

Looking for ways to make relational databases of #disinformation actors more effective? Check out these tips and tricks from our partner Ontotext! 👉 https://bit.ly/3LkEkM5

Every year, the U.S. government directs billions of dollars into priority technology areas. For example, the FY2025 budget includes $3B+ for “Artificial Intelligence.” As disparate USG stakeholders prepare to direct billions of dollars into a given technology area, like #AI, it is essential that they have transparent information about how much federal funding has flowed into that domain historically; what USG stakeholders have directed those investments; and what external entities (companies, universities, research institutions, nonprofits, etc.) have received those funds, at the prime and sub-award levels.  SHELDON’s Federal Spend Reports (FSRs) are designed to do just that. Here is an executive summary version of our AI-focused FSR, updated last month: (password: sheldon; use the spacebar to advance the slides) https://lnkd.in/dtmWPQ2e Whereas the FSR provides a macro-level view of the data, we generate other custom outputs (like Ryan Hafen's amazing #Trelliscope) to allow partners to interact with the data directly/extract more specific insights. Be in touch to learn more: abresler@pwcommunications.com Background  SHELDON leverages open source data and open source tools to enable USG stakeholders of all technical skills to make data-driven decisions in areas related to market research, supplier sourcing, resource allocation, benchmarking/portfolio management, technology development and transition, and more. Development for SHELDON was funded by the United States Air Force, US Navy, and Defense Technical Information Center Technical Background for SHELDON FSRs The process for generating an FSR involves developing a set of terms to describe the topic of interest alongside SMEs, feeding these terms into the DTIC thesaurus to identify related terms, and refining as needed. We then identify direct incidences of these terms across the SHELDON dataset and populate our templated report (designed in partnership with the Air Force). SHELDON’s master dataset joins salient government and government-adjacent data sources related to historic and future USG investment; the entities that work with the USG; USG solicitations, and more.  When it comes to the information contained in our FSRs, it’s important to note that we have all of the underlying data– so in the case of AI, for the $43.6B+ in federal funding we identified, we have all of the underlying data related to the thousands of “awardees” that received these monies, and the thousands of awarding offices that made these awards.

🌟 Curious about how DataForge measures up? 🌟 We're excited to share our new Product Comparison Guide, crafted to provide an in-depth look at how DataForge stands alongside leading code frameworks like dbt and SQLMesh, as well as ELT tools like Coalesce and Matillion. This guide offers a clear, side-by-side evaluation, helping you quickly identify the unique strengths of each tool and understand how they fit into today’s evolving data landscape. Explore the guide on our website to see how DataForge can help reimagine your data transformation workflows. And we’d love to hear from you—which tools or platforms should we add next? We worked hard to make this as factual as possible, but we may have missed something—let us know! https://lnkd.in/g4Nq75rz #DataForge #DataTransformation #ProductGuide #DataEngineering #ELT #ModernDataStack

Optimizing date range queries is a critical yet challenging aspect of database performance. In this 3-part series, I explore effective strategies, including: ✅ Standard approaches and their limitations ✅ Dynamic Range Segmentation (simplified and advanced) ✅ Custom domain indexing for ultimate efficiency 📖 Read the full series here: https://lnkd.in/exqQuSxK Whether you're tackling performance bottlenecks or seeking innovative indexing techniques, this series has something for everyone! Let me know your thoughts or share your own tips in the comments. 💬 #DatabaseOptimization #SQLPerformance #IntervalSearch #DynamicRangeSegmentation

Partnering for Web Scraping with webscrapingexpert.com offers a reliable and effective solution for your ongoing data needs. Our commitment to excellence ensures that your business has access to precise, up-to-date data, tailored to your specific requirements. From real-time market analysis to comprehensive competitor insights, our dedicated team uses cutting-edge technology to provide you with actionable information. This partnership is designed to support your objectives, fuel your strategies, and drive your business forward. Let’s collaborate to transform data into your most valuable asset. Contact us at info@webscrapingexpert.com for a partnership that empowers your business. #DataScraping #WebScrapingServices #BigData #BusinessIntelligence #webscrapingexpert

Pyiceberg: Polaris, DuckDB, Daft We often don't need to rely on expensive cluster-based engines to query tables. PyIceberg, DuckDB, and Daft provide efficient alternatives for many use cases that significantly reduce costs. These tools allow us to handle data management and querying effectively, avoiding the high expense of cluster resources. Comments?