Fast Track PM Success with Project Online
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Project Online provides a flexible online solution for project and portfolio management built for the cloud on SharePoint. It allows users to quickly get started with schedule development, maintain organizational standards, and engage stakeholders. When implemented successfully, Project Online can deliver compliance, executive visibility, internal/external collaboration, and line of business integration.
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3) In relation to agile, the group discussed how practices like reducing handoffs, co-located teams, continuous improvement through retrospectives, and embracing experimentation can help speed up delivery of working software.
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Agile101 Small Batches
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Review and discuss the basic agile practices in the context of two games. The first game will illustrate why small batches are important and how they can help you address project risks sooner. The second game will illustrate how small batches can help give you better information about your project sooner and will demonstrate some of the basic agile practices at work like iterations, continuous flow, manage to done, velocity, retrospectives, etc.
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Att bryta ner kravbilden på rätt sätt är nyckeln till att leverera rätt sak snabbt. Andra faktorer som utvecklingsmetoden eller kapacitet hos medarbetaren spelar roll, men utan en meningsfull uppdelning av kraven är det svårt att lyckas.
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This document summarizes various tools for collaborative working without hosting your own servers. It discusses tools for creating start pages, top links, searches, and doing more with weblogs like Google gadgets and Widgetbox. Other tools covered include Zimbio for creating portals, wikis for comparisons, Google Documents for document sharing, bookmark collaboration with Furl and Delicious, and miscellaneous tools like Cl!p for sharing data.
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Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
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Gursev Pirge, PhD
Senior Data Scientist - JohnSnowLabs
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Dmitrii Kamaev, PhD
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This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-Efficiency
Freshworks creates AI-boosted business software that helps employees work more efficiently and effectively. Managing data across multiple RDBMS and NoSQL databases was already a challenge at their current scale. To prepare for 10X growth, they knew it was time to rethink their database strategy. Learn how they architected a solution that would simplify scaling while keeping costs under control.
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Programming Foundation Models with DSPy - Meetup Slides
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GraphRAG for LifeSciences Hands-On with the Clinical Knowledge Graph
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Graph ML and GenAI Expert - Neo4j
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