Level19

Welcome to the seventh installment of our Legacy Migration Series on modernizing payment systems through microservices! As we shift our focus to the cultural transformation necessary for maximizing the benefits of a microservice platform, it's crucial to recognize that this transition is not just a technical change—it's a profound organizational shift. It requires updates to processes and mindsets across all departments, emphasizing integration and collaboration. In this blog, Brett Westgarth explores key topics such as the myth of independence in Agile teams, the critical role of leadership in guiding this change, and the benefits of structured versus continuous deployment strategies. He also highlights the importance of ongoing training and development to equip teams for a successful transition. Join us in navigating this cultural shift and unlocking the full potential of microservices! #Microservices #LegacyMigration #CulturalTransformation #Level19 #ITStrategy #Payments

Whenever I get a phishing SMS or email, I like to test my kids by sending it their way and asking, “Is this real or not?” It’s my way of training the next generation to spot things! Stay sharp out there, folks! #CyberSecurity #Phishing #FamilyLessons See below from Security Trybe which i also shared with my kids.

Part 2: Tools and Techniques for Synthetic Data Generation In synthetic data generation, GenAI enables the creation of data that maintains the chemical composition of real-world data. Here’s a closer look at the techniques that make this possible: 1. Generative Adversarial Networks (GANs) - How it works: GANs use two neural networks that compete with each other—a generator creates synthetic data while a discriminator evaluates it for authenticity. The feedback loop helps the generator improve, producing more realistic data over time. - Use case: Useful for generating synthetic financial transactions or behavioral data for training machine learning models, testing, or simulating large-scale behaviors. 2. Variational Autoencoders (VAEs) - How it works: VAEs compress data into a smaller latent space (a simpler representation) and then reconstruct it into a synthetic version. This process ensures the output maintains key characteristics of the original data while allowing flexibility in generating new instances. - Use case: VAEs are effective for creating synthetic logs or customer interaction data, helping businesses simulate user engagement for analytics. 3. Reinforcement Learning for Synthetic Data - How it works: Reinforcement learning models generate data by interacting with an environment and learning from feedback. The model receives rewards or penalties based on its actions, refining its output to generate more accurate data that reflects real-world behaviors. - Use case: Commonly used for simulating financial market dynamics or optimizing business processes by running scenario-based simulations to predict outcomes. Key Considerations: - Bias: Care must be taken to ensure synthetic data doesn’t reflect biases from the original datasets. - Balancing Privacy and Realism: It’s essential to strike the right balance between protecting data privacy and generating realistic, usable data. In the next part, I’ll explore some future aspects of synthetic data and its implications. #SyntheticData #GenAI #MachineLearning #AI #GANs #VAEs #ReinforcementLearning #TechTrends #aibrains

Short 3 part introduction to synthetic data generation Something I’ve been thinking about for a while now - here is a quick 3 part mini series introduction to the concept. I might do another series that dives into some specific examples ive been building/toying around with. Stay tuned! Part 1: Introduction to Synthetic Data and GenAI In today’s AI-driven world, synthetic data is becoming a key tool for organizations that need realistic datasets without the risks tied to real-world data. But what sets synthetic data apart is its ability to replicate the chemical composition of real production data—mimicking its properties and patterns while safeguarding privacy. What is Synthetic Data? Synthetic data is artificially generated data that mimics the structure and behavior of real data. Unlike anonymized data, it is not based on real records but created from scratch, replicating the “chemical composition” of production data to ensure it behaves similarly to real-world datasets. Why is Synthetic Data Important? Synthetic data helps solve two major problems: protecting privacy and filling in data gaps. Regulatory challenges, like PIPEDA, limit the use of real data, but synthetic data offers a solution by mimicking the statistical properties of actual data, without exposing sensitive information. It’s also scalable, enabling companies to generate vast datasets to train their AI systems. For example, maybe you have 90% of your customers with a small number of accounts and the remaining 10% of the customer base has orders of magnitude more accounts - I seldom see performance testing setups taking even those basic facts into account. Key Benefits: - Data Privacy: With no actual user data, it complies with regulations while maintaining the essence of production data. It can take into account both direct and quasi identifiers. - Scalability: Synthetic data can be generated endlessly, simulating everything from common cases to rare, hard-to-find scenarios. - Filling Data Gaps: It replicates the “chemical composition” of missing or incomplete real-world data, ensuring AI models are robust and well-trained. In the next part, I’ll explore the tools and techniques used for synthetic data generation, including how GenAI enhances this process to create highly realistic and usable datasets. #SyntheticData #GenAI #DataPrivacy #AI #MachineLearning #TechTrends #DataScience #ArtificialIntelligence #aibrains

In today's dynamic tech landscape, cyber threats are evolving rapidly. Adopting a proactive approach to safeguarding your data is paramount.  Data breaches bring immense financial, reputational, and regulatory challenges. Nimesh Nair writes about how our comprehensive approach identifies vulnerabilities before they can be exploited, ensuring robust protection for your critical assets. From meticulous planning to clear communication and detailed reporting, we offer the insights and strategies needed to fortify your IT infrastructure. Join us as we explore the critical elements for a successful penetration test, from careful planning to collaboration and clear objectives. Continue to follow Level19 or visit our website for more insights and updates! #Cybersecurity #PenetrationTesting #DataProtection #NetworkSecurity #Compliance #RiskManagement #Level19

📊 #FridayInCharts - Analyzing the Trends in Job Postings 📈 This chart from #Indeed highlights job postings in Canada from just before the pandemic until now for Banking/Finance and Software Development. Wild to see in a chart what our industry experienced over 4 years. For a #developer, looks like we are closer to the pandemic low than we are to pre-pandemic levels for job postings. #JobMarket #TechTrends #BankingAndFinance #SoftwareDevelopment #JobPostings #CareerTrends #Economy #Workforce #EmploymentData #MarketAnalysis

The Internet is Not Down ... When the kids say the internet is down at home (it's usually my fault!) I explained to them how devices connect to the internet via wifi versus cellular and I drew the following to explain it. If only my cabling was as clean as the lines in the diagram below! Don't let your kids get away with saying the internet is down! 😉 By the way, did you know you can use ChatGPT to generate diagrams like this? It's a bit of a hack – you ask it to generate mermaid script, which you can import to draw.io. I literally just verbally told ChatGPT what I needed, iterated a couple times, and voila! Might have to do a post on this alone as it is a time saver for diagraming. #InternetIssues #ChatGPT #TechHacks

Understanding VPN Protection Ever wondered how a VPN protects your data? Here's a simple visual breakdown: - With VPN: Your data travels through a secure VPN client to a VPN server before reaching the internet. This setup encrypts your information, ensuring privacy from your Internet Service Provider (ISP) and potential threats. - Without VPN: Your data goes directly through the ISP to the internet, leaving it vulnerable to interception. Protect your data and stay secure online! #VPN #CyberSecurity #DataProtection #Privacy

Reminder to protect your URLs with basic cross-site scripting (XSS) attack defenses. Not having something like this puts your data at risk. Check out my older post on XSS to learn more about safeguarding your applications. #CyberSecurity #XSS #DataProtection #WebSecurity #AppSecurity #CrossSiteScripting #InfoSec #WebDevelopment #SecureCoding #DataPrivacy #TechTips #SecurityAwareness #SafeBrowsing https://lnkd.in/gHAVA7k9

GUID vs ULID #GUID (Globally Unique Identifier) and #ULID (Universal Unique Lexicographically Sortable Identifier) are both used to create unique identifiers, but they have distinct differences and use cases. GUIDs are 128-bit numbers, commonly represented as 32 hexadecimal characters, ensuring uniqueness across systems. They are excellent for distributed systems but lack inherent ordering, making database indexing less efficient. ULIDs, on the other hand, are 128-bit identifiers designed for better performance in databases. They combine a timestamp with random data, providing both uniqueness and lexicographical order, which enhances performance in sequential storage systems. In summary, GUIDs are ideal for ensuring global uniqueness, while ULIDs offer the added benefit of efficient ordering and performance in databases. Choosing between them depends on your specific needs for uniqueness and data retrieval efficiency. The best visual explanation I've seen is from Milan Jovanović on X that I snagged below. #TechInsights #DataManagement #database #performance