This document provides an overview of loading data into Azure SQL DW (Synapse Analytics). It discusses extracting source data into text files, landing the data into Azure Data Lake Store Gen2, preparing the data for loading into staging tables using PolyBase or COPY commands, transforming the data, and inserting it into production tables. It also compares ETL vs ELT approaches and SSIS vs Azure Data Factory for data integration. The presenter then demonstrates loading data in Synapse SQL pool and invites any questions.
Azure Databricks - An Introduction (by Kris Bock)Daniel Toomey
Azure Databricks is a fast, easy to use, and collaborative Apache Spark-based analytics platform optimized for Azure. It allows for interactive collaboration through a unified workspace, enables sharing of insights through integration with Power BI, and provides native integration with other Azure services. It also offers enterprise-grade security through integration with Azure Active Directory and compliance features.
Big Data Day LA 2016/ NoSQL track - Architecting Real Life IoT Architecture, ...Data Con LA
Learn how to benefit from IoT (internet of things) to reduce costs and spur transformation for your company and clients. Attendees will learn about building blocks to create an IoT solution, and walk through real life architectural decisions in building a solution.
Analytics in a Day Ft. Synapse Virtual WorkshopCCG
Say goodbye to data silos! Analytics in a Day will simplify and accelerate your journey towards the modern data warehouse. Join CCG and Microsoft for a half-day virtual workshop, hosted by James McAuliffe.
Azure Data Lake Store is a hyper-scale repository for big data analytics workloads that allows storing petabytes of data in its native format with unlimited storage. Azure Data Lake Analytics is an on-demand analytics job service that runs massively parallel data processing programs and integrates with Visual Studio, charging only for jobs run. U-SQL is a query language that allows querying multiple Azure data sources and includes cognitive capabilities like image tagging and sentiment analysis.
Big Data and Data Warehousing Together with Azure Synapse Analytics (SQLBits ...Michael Rys
SQLBits 2020 presentation on how you can build solutions based on the modern data warehouse pattern with Azure Synapse Spark and SQL including demos of Azure Synapse.
Perth Microsoft Data & Analytics User Group - Building Solutions with Azure D...Sergio Zenatti Filho
This document introduces Sergio Zenatti Filho, a Cloud Solution Architect for Data Platforms at Microsoft. He has over 18 years of experience designing and delivering data and analytics solutions internationally. He enjoys learning new technologies and helping customers define the best solutions for their business needs. Sergio has extensive expertise with Microsoft's data and analytics platforms in both the cloud and on-premises.
Machine learning allows us to build predictive analytics solutions of tomorrow - these solutions allow us to better diagnose and treat patients, correctly recommend interesting books or movies, and even make the self-driving car a reality. Microsoft Azure Machine Learning (Azure ML) is a fully-managed Platform-as-a-Service (PaaS) for building these predictive analytics solutions. It is very easy to build solutions with it, helping to overcome the challenges most businesses have in deploying and using machine learning. In this presentation, we will take a look at how to create ML models with Azure ML Studio and deploy those models to production in minutes.
Privacy has become one of the most important critical topics in data today. It is more than how do we ingest and consume data but the important factors about how you protect your customer’s rights while balancing the business need. In our session, we will bring CTO, Privacera, Don Bosco Durai together with Northwestern Mutual to detail an important use case in privacy and then show how to scale Privacy with a focus on the business needs. We will make the ability to scale effortless.
Azure Days 2019: Grösser und Komplexer ist nicht immer besser (Meinrad Weiss)Trivadis
«Moderne» Data Warehouse/Data Lake Architekturen strotzen oft nur von Layern und Services. Mit solchen Systemen lassen sich Petabytes von Daten verwalten und analysieren. Das Ganze hat aber auch seinen Preis (Komplexität, Latenzzeit, Stabilität) und nicht jedes Projekt wird mit diesem Ansatz glücklich.
Der Vortrag zeigt die Reise von einer technologieverliebten Lösung zu einer auf die Anwender Bedürfnisse abgestimmten Umgebung. Er zeigt die Sonnen- und Schattenseiten von massiv parallelen Systemen und soll die Sinne auf das Aufnehmen der realen Kundenanforderungen sensibilisieren.
Big data requires service that can orchestrate and operationalize processes to refine the enormous stores of raw data into actionable business insights. Azure Data Factory is a managed cloud service that's built for these complex hybrid extract-transform-load (ETL), extract-load-transform (ELT), and data integration projects.
DataOps for the Modern Data Warehouse on Microsoft Azure @ NDCOslo 2020 - Lac...Lace Lofranco
Talk Description:
The Modern Data Warehouse architecture is a response to the emergence of Big Data, Machine Learning and Advanced Analytics. DevOps is a key aspect of successfully operationalising a multi-source Modern Data Warehouse.
While there are many examples of how to build CI/CD pipelines for traditional applications, applying these concepts to Big Data Analytical Pipelines is a relatively new and emerging area. In this demo heavy session, we will see how to apply DevOps principles to an end-to-end Data Pipeline built on the Microsoft Azure Data Platform with technologies such as Data Factory, Databricks, Data Lake Gen2, Azure Synapse, and AzureDevOps.
Resources: https://aka.ms/mdw-dataops
This document summarizes various Azure data and analytics services that could be used to build an "ImagineCare" solution, including Azure Data Factory for data automation, Azure Data Catalog for indexing data sources, Azure Event Hubs for ingesting IoT data, Azure Data Lake for petabyte-scale data storage, Azure SQL Data Warehouse for relational data warehousing, Azure Machine Learning for predictive analytics, HD Insight for Hadoop distribution, Azure Streaming Analytics for streaming jobs, Power BI for dashboards and visualizations, Cortana Desktop Assistant for voice processing, and the Azure Machine Learning gallery for published web services. A demo was shown of vehicle telemetry data visualized in dashboards using data both "in motion" and "at rest
Azure Days 2019: Keynote Azure Switzerland – Status Quo und Ausblick (Primo A...Trivadis
Die Azure Cloud ist in der Schweiz angekommen. In dieser Session beleuchtet Primo Amrein, Cloud Lead bei Microsoft Schweiz, die Einführung der Azure Cloud in der Schweiz, berichtet über die Erfolgsgeschichten und die Lessons Learned. Die Session wird mit einem Ausblick auf die Roadmap abgerundet.
Big data requires service that can orchestrate and operationalize processes to refine the enormous stores of raw data into actionable business insights. Azure Data Factory is a managed cloud service that's built for these complex hybrid extract-transform-load (ETL), extract-load-transform (ELT), and data integration projects.
Big data requires service that can orchestrate and operationalize processes to refine the enormous stores of raw data into actionable business insights. Azure Data Factory is a managed cloud service that's built for these complex hybrid extract-transform-load (ETL), extract-load-transform (ELT), and data integration projects.
The breath and depth of Azure products that fall under the AI and ML umbrella can be difficult to follow. In this presentation I’ll first define exactly what AI, ML, and deep learning is, and then go over the various Microsoft AI and ML products and their use cases.
Leveraging Azure Analysis Services Tabular Data Models with Power BI by Tim M...KTL Solutions
We will take a look at an introduction and overview of Azure Analysis Services: Microsoft‘s cloud-based analytical engine and Platform as a Service (PaaS) offerings and how to leverage SQL Server Data Tools to build and deploy a tabular data model to Azure Analysis Services.
We will then connect with Power BI Desktop and the Power BI portal to build visualizations. We will discuss Azure Analysis Services features and capabilities, use cases, provisioning and deployment, managing and monitoring, tools, and report creation. Azure Analysis Service became Globally Available in April 2017, and Power
BI has released several major updates as well.
This document introduces Cortana Intelligence Solutions, which provides intelligent, interactive dashboards and proven solution architectures to help organizations transform data into insights. It highlights the business potential of big data and analytics, then demonstrates a Twitter time series analysis using Azure Time Series Insights. The document provides information on Cortana Intelligence Solutions and links to learn more, try sample solutions, deploy solutions, customize deployments, and give feedback.
Analytics in a Day Ft. Synapse Virtual WorkshopCCG
Say goodbye to data silos! Analytics in a Day will simplify and accelerate your journey towards the modern data warehouse. Join CCG and Microsoft for a half-day virtual workshop, hosted by James McAuliffe.
Session6-SharePoint and Azure- steve fox-windows-and_azure_spfsMithun T. Dhar
SharePoint can be integrated with Windows Azure in various ways to leverage reach, resources, and reusability. Examples presented included a crime statistics dashboard, external lists to access Azure SQL data from SharePoint, and an image file manager leveraging Azure storage. The document recommends downloading virtual machines for SharePoint and the Azure Developer Center, and provides references for code samples and training on integrating SharePoint and Azure.
SQLArgentina - Data Platform Summit BA - KeynoteMariano Kovo
The document announces an upcoming Data Summit in Buenos Aires on May 27, 2019 featuring keynotes on transforming business with a modern data estate and data modernization choices. It also promotes the PASS Summit 2019 conference from June 24-28, 2019 with a discount for SQLArgentina members and lists upcoming webinars from the PASS virtual groups on various data platform topics.
Sergio Zenatti Filho is a Cloud Solution Architect at Microsoft with over 18 years of experience designing and delivering data and analytics solutions. He will discuss Azure SQL Database, including an overview of the different database services, how to provision and monitor an Azure SQL Database, and security and performance features like auditing and transparent data encryption. Resources for further reading are provided.
This document provides an agenda for a presentation on SharePoint given by Chris McNulty and Michelle Caldwell. It includes brief biographies of the presenters, an outline of topics to be covered such as SharePoint 2016 deep dives and demonstrations, and information on accessing related resources and contacting the presenters. Next steps mentioned include discussions of topics being out of scope and leaving time for questions.
SBA Security Meetup - Deploying and managing azure sentinel as code by Bojan ...SBA Research
Deploying and Managing Azure Sentinel as Code
In this Meetup, Bojan Magusic will explore and demonstrate how to detect threats and respond smarter and faster and eliminate security risks using Azure Sentinel as Code. The talk will cover specifically:
- Security challenges that SOC teams are facing
- How can the public cloud help us manage those challenges
- What is a cloud-native next-generation SIEM
- Glimpse into a cloud native next-gen SIEM that is Azure Sentinel
- Using Infrastructure as Code to manage Azure Sentinel
Speaker:
Bojan Magusic (Cloud Solution Architect - Security & Compliance - Microsoft)
Talk language: English
About the Speaker:
*********************
Bojan Magusic is a Cloud Solution Architect - Security & Compliance, One Commercial Partner, Microsoft Ireland. He will explore and demonstrate how to detect threats and respond smarter and faster and eliminate security risk using Azure Sentinel as Code. Bojan acts as a technology expert for Microsoft partners in Western Europe, who are looking to build new solutions based on Microsoft’s Azure cloud platform technologies. He has a strong passion for cybersecurity, advancing women in tech, and professional development. He is very interested in building partnerships with other companies to learn how they support, advance, and retain their cyber talent. In addition to various technical certifications, he also has received certifications from INSEAD and Kellogg School of Management. Bojan resides in Dublin (Ireland), from where he is living the dream!
Hadoop et bases de données relationnelles ultra performantes : le meilleur de...Microsoft Décideurs IT
Le modèle traditionnel de traitement des données dans un système décisionnel est arrivé à maturité et atteint ses limites quant au traitement de nouveaux types de données issues des objets connectés, capteurs, données de réseaux sociaux,… Hadoop constitue une des pierres angulaires pour intégrer ces données diverses. Afin de simplifier la transition vers ces nouvelles perspectives, APS et les technologies de virtualisation tels que Polybase permettent de moderniser l’existant en toute simplicité. Dans cette session, nous allons détailler les différents scénarii d’architectures et de cas d’usages possibles pour la modernisation du système décisionnel avec l’utilisation de Polybase via des démonstrations pour répondre aux questions de type : 1. En quoi l’utilisation d’Hadoop permet de répondre aux défis d’alimentation, de collecte des données (ETL) et d’archivage à moindre coût ? 2. Qu’apporte Polybase dans APS avec Hadoop par rapport à un système traditionnel dans un monde où les volumes de données continuent à croitre et à se complexifier et où la consommation des données tend à être en temps réel?
Hadoop et bases de données relationnelles ultra performantes : le meilleur de...Microsoft Technet France
The document discusses Microsoft's Analytics Platform System and how it provides an integrated platform for data ingestion, storage, processing, analytics and visualization. It can handle both structured and unstructured data from various sources and formats. The platform allows users to easily create external tables in Azure SQL Database linked to data stored in Hadoop on Azure HDInsight or on-premises with Hortonworks. It also discusses using the platform for scenarios like customer analytics, fraud detection, predictive maintenance and more.
David J. Rosenthal gave a presentation about Microsoft's Azure cloud platform. He discussed how Azure can help companies with digital transformation by engaging customers, empowering employees, and optimizing operations. He provided examples of how companies are using Azure services like AI, IoT, analytics and more to modernize applications, gain insights from data, and improve productivity. Rosenthal emphasized that Azure offers a secure, flexible cloud platform that businesses can use to innovate, grow and transform both today and in the future.
The document summarizes upcoming presentations for the Brisbane Azure User Group in September 2016 and beyond. It includes:
- An upcoming presentation in September 2016 on Azure Functions by Dan Dekel from Patient Zero.
- Information on Microsoft Azure updates in September 2016 including the general availability of Azure SQL Data Warehouse in additional regions, a new P15 performance level for Azure SQL Database Premium, and JSON support in Azure SQL Database.
- Details about upcoming Microsoft events like Innovation Days in Sydney in September and Ignite conferences in the US and New Zealand.
- Announcements for Azure certification study groups in Brisbane to help participants study for the 70-532 Developing Microsoft Azure Solutions exam.
The document discusses how organizations can leverage cloud, data, and AI to gain competitive advantages. It notes that 80% of organizations now adopt cloud-first strategies, AI investment increased 300% in 2017, and data is expected to grow dramatically. The document promotes Microsoft's cloud-based analytics services for harnessing data at scale from various sources and types. It provides examples of how companies have used these services to improve customer experience, reduce costs, speed up insights, and gain operational efficiencies.
.Net development with Azure Machine Learning (AzureML) Nov 2014Mark Tabladillo
Azure Machine Learning provides enterprise-class machine learning and data mining to the cloud. This presenter will cover 1) what AzureML is, 2) technical overview of AzureML for application development, 3) a reminder to consider SQL Server Data Mining, and 4) a recommend path for resources and next steps.
Advanced Analytics and Artificial Intelligence - Transforming Your Business T...David J Rosenthal
Recent advances in AI have incredible potential and they are already fundamentally changing our lives in ways we couldn’t have imagined even five years ago. And yet, AI is also probably one of the least understood technological breakthroughs in modern times. Come to this event to learn about breakthrough advances in AI and the power of the cloud, and how Microsoft provides a flexible platform for you to infuse intelligence into your own products and services. Microsoft empowers you to transform your business, uniquely combining AI innovation with a proven Enterprise platform, deriving intelligence from a wide range of data relevant to your business no matter where it lives.
Microsoft Azure and Microsoft 365 - How Will They Help YouSuhail Jamaldeen
Induction Program Faculty of Arts - Uni. of Colombo (21.01.2020)
Spoke on Microsoft 365 and Cloud Computing among the students of University of Colombo Faculty of Arts students on 21st January 2020
This document provides an overview of using Polybase for data virtualization in SQL Server. It discusses installing and configuring Polybase, connecting external data sources like Azure Blob Storage and SQL Server, using Polybase DMVs for monitoring and troubleshooting, and techniques for optimizing performance like predicate pushdown and creating statistics on external tables. The presentation aims to explain how Polybase can be leveraged to virtually access and query external data using T-SQL without needing to know the physical data locations or move the data.
Antonios Chatzipavlis presented on SQL Server backup and restore. The presentation covered database architecture basics including data files, transaction log files, and the buffer cache. It also discussed backup types like full, differential, transaction log, copy only and partial backups. Backup strategies and restore processes were explained, including restoring to a point in time and restoring system databases. The internals of how SQL Server performs backups using buffers and I/O threads was also summarized.
Antonios Chatzipavlis presented on migrating SQL workloads to Azure. He discussed modernizing data platforms by discovering, assessing, planning, transforming, optimizing, testing and remediating. Key migration considerations include remaining, rehosting, refactoring, rearchitecting, rebuilding or replacing workloads. Tools for migrating data include Microsoft Assessment and Planning Toolkit, Data Migration Assistant, Database Experimentation Assistant, SQL Server Migration Assistant, and Azure Database Migration Service. Workloads can be migrated to Azure VMs, Azure SQL Databases or Azure SQL Managed Instances.
This document summarizes a webinar presentation about workload management in SQL Server 2019. It discusses how SQL Server's Resource Governor feature can be used to provide multitenancy, predictable performance, and isolation for multiple workloads running on a single SQL Server instance. Key concepts covered include resource pools, workload groups, and classification functions to assign sessions to different pools and groups. The presentation also reviews best practices for using lookup tables in classification functions and shows some DMVs for monitoring Resource Governor configuration and statistics.
The document provides an overview of the DAX language. It discusses that DAX is the programming language used in Power BI, Power Pivot, and Analysis Services for data modeling, reporting, and analytics. It describes the basic components of a DAX data model including tables, columns, relationships, measures, and hierarchies. It also covers DAX syntax, functions, operators, and how context and filter context work in DAX calculations and queries.
The document introduces Diagnostic Management Views (DMVs) and Dynamic Management Functions (DMFs) in SQL Server. It discusses that DMVs and DMFs return server state information and can be used to monitor server health, diagnose problems, and tune performance. It provides examples of common DMVs and DMFs used for query execution and the query plan cache. Finally, it notes that the presentation will demonstrate troubleshooting with DMVs and DMFs.
This document summarizes common T-SQL anti-patterns that can negatively impact query performance, including using SELECT *, functions in predicates, OR operators, implicit conversions, unnecessary sorts, correlated subqueries, and dynamic SQL execution. The presentation provides explanations of why each anti-pattern hurts performance and recommendations for more optimized alternatives such as using indexes, temporary tables, parameterization, and execution plan analysis.
This document discusses designing a modern data warehouse in Azure. It provides an overview of traditional vs. self-service data warehouses and their limitations. It also outlines challenges with current data warehouses around timeliness, flexibility, quality and findability. The document then discusses why organizations need a modern data warehouse based on criteria like customer experience, quality assurance and operational efficiency. It covers various approaches to ingesting, storing, preparing and modeling data in Azure. Finally, it discusses architectures like the lambda architecture and common data models.
Modernizing Your Database with SQL Server 2019 discusses SQL Server 2019 features that can help modernize a database, including:
- The Hybrid Buffer Pool which supports persistent memory to improve performance on read-heavy workloads.
- Memory-Optimized TempDB Metadata which stores TempDB metadata in memory-optimized tables to avoid certain blocking issues.
- Intelligent Query Processing features like Adaptive Query Processing, Batch Mode processing on rowstores, and Scalar UDF Inlining which improve query performance.
- Approximate Count Distinct, a new function that provides an estimated count of distinct values in a column faster than a precise count.
- Lightweight profiling, enabled by default, which provides query plan
This document discusses designing a modern data warehouse in Azure. It provides an overview of traditional vs. self-service data warehouses and their limitations. It also outlines challenges with current data warehouses around timeliness, flexibility, quality and findability. The document then discusses why organizations need a modern data warehouse based on criteria like customer experience, quality assurance and operational efficiency. It covers various approaches to ingesting, storing, preparing, modeling and serving data on Azure. Finally, it discusses architectures like the lambda architecture and common data models.
The document provides details about an SQL expert's background and certifications. It summarizes the expert's career starting in 1982 working with computers and 1988 starting in the computer industry. In 1996, they started working with SQL Server 6.0 and have since earned multiple Microsoft certifications. The expert now provides training and consultation services, and created an online school called SQL School Greece to teach SQL Server.
Azure SQL Database for the SQL Server DBA - Azure Bootcamp Athens 2018 Antonios Chatzipavlis
Azure SQL Database is a managed database service hosted in Microsoft's Azure cloud. Some key differences from SQL Server include: the service is paid by the hour based on the selected service tier; users can dynamically scale resources up or down; backups and high availability are managed by the service provider; and common administration tasks are handled by the provider rather than the user. The service offers automatic backups, point-in-time restore, and geo-restore capabilities along with built-in high availability through replication across three copies in the primary region.
The document discusses technologies within the Microsoft SQL family and Azure SQL that can help organizations address requirements of the General Data Protection Regulation (GDPR). It covers features for discovering and classifying personal data, managing access and controlling how data is used, and protecting data through encryption, auditing and other security controls. Built-in technologies like dynamic data masking, row-level security, authentication options, and transparent data encryption are described as ways SQL Server and Azure SQL Database can help organizations comply with GDPR.
The document provides biographical information about Antonios Chatzipavlis, a SQL Server expert and evangelist. It then summarizes his presentation on statistics and index internals in SQL Server, which covers topics like cardinality estimation, inspecting and updating statistics, index structure and types, and identifying missing indexes. The presentation includes demonstrations of analyzing cardinality estimation and picking the right index key.
This document provides an introduction and overview of Azure Data Lake. It describes Azure Data Lake as a single store of all data ranging from raw to processed that can be used for reporting, analytics and machine learning. It discusses key Azure Data Lake components like Data Lake Store, Data Lake Analytics, HDInsight and the U-SQL language. It compares Data Lakes to data warehouses and explains how Azure Data Lake Store, Analytics and U-SQL process and transform data at scale.
This document provides an overview of Azure SQL Data Warehouse. It discusses what Azure SQL Data Warehouse is, how it is provisioned and scaled, best practices for designing tables in Azure SQL DW including distribution keys and data types, and methods for loading and querying data including PolyBase and labeling queries for monitoring. The presentation also covers tuning aspects like statistics, indexing, and resource classes.
This document provides an introduction and overview of Azure DocumentDB. It discusses how DocumentDB is a fully managed NoSQL database service that provides fast and predictable performance for JSON data through SQL querying capabilities. It also describes how DocumentDB offers features like elastic scaling, high availability, global distribution and ease of development. The document then provides information on starting with DocumentDB, writing queries, and programming capabilities within DocumentDB like stored procedures and triggers.
This document provides an introduction and overview of machine learning concepts and Azure Machine Learning. It defines machine learning as finding patterns in data and using those patterns to predict the future. It outlines the machine learning workflow and lifecycle, including preparing data, applying algorithms to find patterns, iterating to create the best model, and deploying the final model. It also describes machine learning concepts like supervised and unsupervised learning, and different problem types like regression, classification, and clustering. Finally, it discusses options for using Azure Machine Learning, including free and full-featured paid accounts, and demonstrates its use.
Welcome to Cyberbiosecurity. Because regular cybersecurity wasn't complicated...Snarky Security
How wonderful it is that in our modern age, every bit of our biological data can be digitized, stored, and potentially pilfered by cyber thieves! Isn't it just splendid to think that while scientists are busy pushing the boundaries of biotechnology, hackers could be plotting the next big bio-data heist? This delightful scenario is brought to you by the ever-expanding digital landscape of biology and biotechnology, where the integration of computer science, engineering, and data science transforms our understanding and manipulation of biological systems.
While the fusion of technology and biology offers immense benefits, it also necessitates a careful consideration of the ethical, security, and associated social implications. But let's be honest, in the grand scheme of things, what's a little risk compared to potential scientific achievements? After all, progress in biotechnology waits for no one, and we're just along for the ride in this thrilling, slightly terrifying, adventure.
So, as we continue to navigate this complex landscape, let's not forget the importance of robust data protection measures and collaborative international efforts to safeguard sensitive biological information. After all, what could possibly go wrong?
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This document provides a comprehensive analysis of the security implications biological data use. The analysis explores various aspects of biological data security, including the vulnerabilities associated with data access, the potential for misuse by state and non-state actors, and the implications for national and transnational security. Key aspects considered include the impact of technological advancements on data security, the role of international policies in data governance, and the strategies for mitigating risks associated with unauthorized data access.
This view offers valuable insights for security professionals, policymakers, and industry leaders across various sectors, highlighting the importance of robust data protection measures and collaborative international efforts to safeguard sensitive biological information. The analysis serves as a crucial resource for understanding the complex dynamics at the intersection of biotechnology and security, providing actionable recommendations to enhance biosecurity in an digital and interconnected world.
The evolving landscape of biology and biotechnology, significantly influenced by advancements in computer science, engineering, and data science, is reshaping our understanding and manipulation of biological systems. The integration of these disciplines has led to the development of fields such as computational biology and synthetic biology, which utilize computational power and engineering principles to solve complex biological problems and innovate new biotechnological applications. This interdisciplinary approach has not only accelerated research and development but also introduced new capabilities such as gene editing and biomanufact
How UiPath Discovery Suite supports identification of Agentic Process Automat...DianaGray10
📚 Understand the basics of the newly persona-based LLM-powered Agentic Process Automation and discover how existing UiPath Discovery Suite products like Communication Mining, Process Mining, and Task Mining can be leveraged to identify APA candidates.
Topics Covered:
💡 Idea Behind APA: Explore the innovative concept of Agentic Process Automation and its significance in modern workflows.
🔄 How APA is Different from RPA: Learn the key differences between Agentic Process Automation and Robotic Process Automation.
🚀 Discover the Advantages of APA: Uncover the unique benefits of implementing APA in your organization.
🔍 Identifying APA Candidates with UiPath Discovery Products: See how UiPath's Communication Mining, Process Mining, and Task Mining tools can help pinpoint potential APA candidates.
🔮 Discussion on Expected Future Impacts: Engage in a discussion on the potential future impacts of APA on various industries and business processes.
Enhance your knowledge on the forefront of automation technology and stay ahead with Agentic Process Automation. 🧠💼✨
Speakers:
Arun Kumar Asokan, Delivery Director (US) @ qBotica and UiPath MVP
Naveen Chatlapalli, Solution Architect @ Ashling Partners and UiPath MVP
Increase Quality with User Access Policies - July 2024Peter Caitens
⭐️ Increase Quality with User Access Policies ⭐️, presented by Peter Caitens and Adam Best of Salesforce. View the slides from this session to hear all about “User Access Policies” and how they can help you onboard users faster with greater quality.
"Building Future-Ready Apps with .NET 8 and Azure Serverless Ecosystem", Stan...Fwdays
.NET 8 brought a lot of improvements for developers and maturity to the Azure serverless container ecosystem. So, this talk will cover these changes and explain how you can apply them to your projects. Another reason for this talk is the re-invention of Serverless from a DevOps perspective as a Platform Engineering trend with Backstage and the recent Radius project from Microsoft. So now is the perfect time to look at developer productivity tooling and serverless apps from Microsoft's perspective.
Cracking AI Black Box - Strategies for Customer-centric Enterprise ExcellenceQuentin Reul
The democratization of Generative AI is ushering in a new era of innovation for enterprises. Discover how you can harness this powerful technology to deliver unparalleled customer value and securing a formidable competitive advantage in today's competitive market. In this session, you will learn how to:
- Identify high-impact customer needs with precision
- Harness the power of large language models to address specific customer needs effectively
- Implement AI responsibly to build trust and foster strong customer relationships
Whether you're at the early stages of your AI journey or looking to optimize existing initiatives, this session will provide you with actionable insights and strategies needed to leverage AI as a powerful catalyst for customer-driven enterprise success.
Keynote : AI & Future Of Offensive SecurityPriyanka Aash
In the presentation, the focus is on the transformative impact of artificial intelligence (AI) in cybersecurity, particularly in the context of malware generation and adversarial attacks. AI promises to revolutionize the field by enabling scalable solutions to historically challenging problems such as continuous threat simulation, autonomous attack path generation, and the creation of sophisticated attack payloads. The discussions underscore how AI-powered tools like AI-based penetration testing can outpace traditional methods, enhancing security posture by efficiently identifying and mitigating vulnerabilities across complex attack surfaces. The use of AI in red teaming further amplifies these capabilities, allowing organizations to validate security controls effectively against diverse adversarial scenarios. These advancements not only streamline testing processes but also bolster defense strategies, ensuring readiness against evolving cyber threats.
Choosing the Best Outlook OST to PST Converter: Key Features and Considerationswebbyacad software
When looking for a good software utility to convert Outlook OST files to PST format, it is important to find one that is easy to use and has useful features. WebbyAcad OST to PST Converter Tool is a great choice because it is simple to use for anyone, whether you are tech-savvy or not. It can smoothly change your files to PST while keeping all your data safe and secure. Plus, it can handle large amounts of data and convert multiple files at once, which can save you a lot of time. It even comes with 24*7 technical support assistance and a free trial, so you can try it out before making a decision. Whether you need to recover, move, or back up your data, Webbyacad OST to PST Converter is a reliable option that gives you all the support you need to manage your Outlook data effectively.
Top 12 AI Technology Trends For 2024.pdfMarrie Morris
Technology has become an irreplaceable component of our daily lives. The role of AI in technology revolutionizes our lives for the betterment of the future. In this article, we will learn about the top 12 AI technology trends for 2024.
This PDF delves into the aspects of information security from a forensic perspective, focusing on privacy leaks. It provides insights into the methods and tools used in forensic investigations to uncover and mitigate privacy breaches in mobile and cloud environments.
"Hands-on development experience using wasm Blazor", Furdak Vladyslav.pptxFwdays
I will share my personal experience of full-time development on wasm Blazor
What difficulties our team faced: life hacks with Blazor app routing, whether it is necessary to write JavaScript, which technology stack and architectural patterns we chose
What conclusions we made and what mistakes we committed
TrustArc Webinar - Innovating with TRUSTe Responsible AI CertificationTrustArc
In a landmark year marked by significant AI advancements, it’s vital to prioritize transparency, accountability, and respect for privacy rights with your AI innovation.
Learn how to navigate the shifting AI landscape with our innovative solution TRUSTe Responsible AI Certification, the first AI certification designed for data protection and privacy. Crafted by a team with 10,000+ privacy certifications issued, this framework integrated industry standards and laws for responsible AI governance.
This webinar will review:
- How compliance can play a role in the development and deployment of AI systems
- How to model trust and transparency across products and services
- How to save time and work smarter in understanding regulatory obligations, including AI
- How to operationalize and deploy AI governance best practices in your organization
5. Antonios Chatzipavlis
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9. Azure Synapse Analytics
Limitless analytics service with unmatched time to insight
Platform
Azure
Data Lake Storage
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Optimized for Analytics
METASTORE
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MONITORING
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11. • Extract the source data into text files.
• Land the data into Azure Data Lake Store Gen2.
• Prepare the data for loading.
• Load the data into staging tables with PolyBase or the COPY command.
• Transform the data.
• Insert the data into production tables.
Data loading strategy for Synapse SQL pool
The fastest and most scalable way to load data