The Synergy Between Agile Coaching and Product Management
When Agile coaches and product managers work together, they create a powerful synergy that drives innovation and business succes
Here's a breakdown of the terms CIF Sanction Screening , AML Watch Screening , and Risk Profiling in the context of financial institutions, specifically in relation to compliance and anti-money laundering (AML) efforts: 1. CIF Sanction Screening CIF (Customer Information File) Sanction Screening involves checking customer information (such as names, addresses, and other identifiers) against lists of sanctioned individuals or entities. Sanctioned lists typically come from global regulatory bodies, such as the United Nations , EU , or OFAC (Office of Foreign Assets Control) . The aim is to ensure that the bank or financial institution does not engage in any transactions or provide services to individuals or entities that are on these sanctioned lists (due to reasons such as terrorism, criminal activities, or economic sanctions). Example : If a customer’s name matches one on the OFAC list , the institution will block transactions and report it for further investigation....
Future Strategy: Fast, Safe Mobile Releases with CI/CD & Feature Flags To meet growing demands for faster updates and reliable mobile experiences, we’re transforming how we deliver mobile apps. Our new approach emphasizes automation, flexibility, and control through CI/CD pipelines, feature toggles, and regular release cycles. 1️⃣ Separating Code Deployment from Feature Launch By using feature flags , we decouple code deployment from feature activation . This means we can ship code early but only make it visible to users when we’re ready. text Copy Edit Code Merged → CI/CD → Staging/UAT ↘ → Production (Feature OFF) → Enable in Production (Feature ON) 💡 Benefits : Release features silently (aka “dark launch”) Gradually roll out new functionality Instantly turn off features without pushing a new build 2️⃣ Environment-Based Versioning Each environment follows a structured version for...
https://www.youtube.com/watch?v=q8d9uuO1Cf4 Data Science Stack: A Quick Overview In data science, we use various tools and techniques to work with data. Here's a breakdown: Hardware: Storage: We store data in data warehouses (structured) or data lakes (unstructured). Processing: We use GPUs (graphic processing units) to process data. Software: Programming Languages: Python is the most popular language, followed by JavaScript for simpler applications. Rust and Mojo are newer options. Libraries: Python has many libraries like Pandas, NumPy, scikit-learn, TensorFlow, PyTorch, Keras, and Matplotlib to help with data analysis, machine learning, and visualization. Development Environments: We use IDEs like Jupyter Notebook and PyCharm to write and run code. Version Control: We use tools like GitHub to manage different versions of our code. Data Exchange: We use JSON format to exchange data between systems. Deployment: Centralized: Model is hosted on a server and acces...
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