Azure Synapse Analytics is Microsoft's analytical engine that brings together data integration, enterprise data warehousing and big data analytics. It uses a holistic approach which means that different user personas will use Azure Synapse.
• How do you deal with these different user personas and the different roles within Azure Synapse Analytics? For example, what is a Data Scientist or Data Engineer allowed to do and what not?
• What roles do we need to store the code in DevOps, to debug a pipeline or to execute a Notebook?
I would like to take you through some practical examples on how you can best set up these roles for your Azure Synapse environment.
Azure Key Vault, Azure Dev Ops and Azure Synapse - how these services work pe...Erwin de Kreuk
Can we store our Connectionstrings or BlobStorageKeys or other Secretvalues somewhere else then in Azure Synapse Pipelines? Yes you can! You can store these valuable secrets in Azure Key Vault(AKV).
• But how can we achieve this in Azure Synapse Analytics?
• How do we deploy our Synapse Pipelines in Azure Dev Ops to Test, Acceptance and Production environments with these Secrets ?
• Can this be setup dynamically?
During this session I will give answers on all these questions. You will learn how to setup your Azure Key Vault, connect these secrets in Azure Synapse Analytics and finally deploy these secrets dynamically in Azure Dev Ops. As you can see a lot to talk about during this session.
Azure Synapse Analytics is Azure SQL Data Warehouse evolved: a limitless analytics service, that brings together enterprise data warehousing and Big Data analytics into a single service. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs. This is a huge deck with lots of screenshots so you can see exactly how it works.
Organizations are grappling to manually classify and create an inventory for distributed and heterogeneous data assets to deliver value. However, the new Azure service for enterprises – Azure Synapse Analytics is poised to help organizations and fill the gap between data warehouses and data lakes.
Azure Key Vault, Azure Dev Ops and Azure Synapse - how these services work pe...Erwin de Kreuk
Can we store our Connectionstrings or BlobStorageKeys or other Secretvalues somewhere else then in Azure Synapse Pipelines? Yes you can! You can store these valuable secrets in Azure Key Vault(AKV).
• But how can we achieve this in Azure Synapse Analytics?
• How do we deploy our Synapse Pipelines in Azure Dev Ops to Test, Acceptance and Production environments with these Secrets ?
• Can this be setup dynamically?
During this session I will give answers on all these questions. You will learn how to setup your Azure Key Vault, connect these secrets in Azure Synapse Analytics and finally deploy these secrets dynamically in Azure Dev Ops. As you can see a lot to talk about during this session.
Azure Synapse Analytics is Azure SQL Data Warehouse evolved: a limitless analytics service, that brings together enterprise data warehousing and Big Data analytics into a single service. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs. This is a huge deck with lots of screenshots so you can see exactly how it works.
Organizations are grappling to manually classify and create an inventory for distributed and heterogeneous data assets to deliver value. However, the new Azure service for enterprises – Azure Synapse Analytics is poised to help organizations and fill the gap between data warehouses and data lakes.
Databricks is a Software-as-a-Service-like experience (or Spark-as-a-service) that is a tool for curating and processing massive amounts of data and developing, training and deploying models on that data, and managing the whole workflow process throughout the project. It is for those who are comfortable with Apache Spark as it is 100% based on Spark and is extensible with support for Scala, Java, R, and Python alongside Spark SQL, GraphX, Streaming and Machine Learning Library (Mllib). It has built-in integration with many data sources, has a workflow scheduler, allows for real-time workspace collaboration, and has performance improvements over traditional Apache Spark.
Novell ZENworks Patch Management Best PracticesNovell
Since the first virus arrived on the IT scene, patching software has been a costly and time-consuming IT focus. In fact, “Patch Tuesdays” have come to symbolize the drain software patches place on organizations of every description. Attend this session to find out how Novell ZENworks Patch Management—working hand-in-hand with Novell ZENworks Configuration Management—can make Patch Tuesdays a thing of the past. You'll learn about the benefits of integrated patch and configuration management. You'll also receive tips, tricks and inside information to successfully deploy and troubleshoot Novell ZENworks 10 Patch Management and realize its true potential.
Microsoft Azure is the only hybrid cloud to help you migrate your apps, data, and infrastructure with cost-effective and flexible paths. At this event you’ll learn how thousands of customers have migrated to Azure, at their own pace and with high confidence by using a reliable methodology, flexible and powerful tools, and proven partner expertise. Come to this event to learn how Azure can help you save—before, during, and after migration, and how it offers unmatched value during every stage of your cloud migration journey. Learn about assessments, migration offers, and cost management tools to help you migrate with confidence.
Applying DevOps to Databricks can be a daunting task. In this talk this will be broken down into bite size chunks. Common DevOps subject areas will be covered, including CI/CD (Continuous Integration/Continuous Deployment), IAC (Infrastructure as Code) and Build Agents.
We will explore how to apply DevOps to Databricks (in Azure), primarily using Azure DevOps tooling. As a lot of Spark/Databricks users are Python users, will will focus on the Databricks Rest API (using Python) to perform our tasks.
Azure Synapse Analytics is Azure SQL Data Warehouse evolved: a limitless analytics service, that brings together enterprise data warehousing and Big Data analytics into a single service. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs. This is a huge deck with lots of screenshots so you can see exactly how it works.
Windows Azure Active Directory presentation will show you how to set up your Azure AD account and how to connect existing ASP.NET MVC Web Application with Azure Active Directory to provide Single-Sign-On
By using a Data Lake, you no longer need to worry about structuring or transforming data before storing it. A Data Lake on AWS enables your organization to more rapidly analyze data, helping you quickly discover new business insights. Join us for our webinar to learn about the benefits of building a Data Lake on AWS and how your organization can begin reaping their rewards. In this webinar, select APN Partners will share their specific methodology for implementing a Data Lake on AWS and best practices for getting the most from your Data Lake.
Azure Data Factory | Moving On-Premise Data to Azure Cloud | Microsoft Azure ...Edureka!
** Microsoft Azure Certification Training : https://www.edureka.co/microsoft-azure-training **
This Edureka "Azure Data Factory” tutorial will give you a thorough and insightful overview of Microsoft Azure Data Factory and help you understand other related terms like Data Lakes and Data Warehousing.
Following are the offering of this tutorial:
1. Why Azure Data Factory?
2. What Is Azure Data Factory?
3. Data Factory Concepts
4. What is Azure Data Lake?
5. Data Lake Concepts
6. Data Lake Vs Data Warehouse
7. Demo- Moving On-Premise Data To Cloud
Check out our Playlists: https://goo.gl/A1CJjM
here's where Microsoft has invested, across these areas: identity and access management, apps and data security, network security, threat protection, and security management.
We’ve put a tremendous amount of investment into these areas and the way it shows up is across a pretty broad array of product areas and features.
Our Identity and Access Management tools enable you to take an identity-based approach to security, and establish truly conditional access policies
Our App and Data Security help you protect your apps and your data as it moves around—both inside and outside your organization
Azure includes a robust networking infrastructure with built-in security controls for your application and service connectivity.
Our Threat Protection capabilities are built in and fully integrated, so you can strengthen both pre-breach protection with deep capabilities across e-mail, collaboration services, and end points including hardware based protection; and post-breach detection that includes memory and kernel based protection and response with automation.
And our Security Management tools give you the visibility and more importantly the guidance to manage policy centrally
SQL KONFERENZ 2020 Azure Key Vault, Azure Dev Ops and Azure Data Factory how...Erwin de Kreuk
Can we store our Connectionstrings or BlobStorageKeys or other Secretvalues somewhere else then in Azure Data Factory(ADF)? Yes you can! You can store these valuable secrets in Azure Key Vault(AKV).
But how can we achieve this in ADF? And finally how do we deploy our DataFactories in Azure Dev Ops to Test, Acceptance and Production environments with these Secrets ? Can this be setup dynamically?
During this session I will give answers on all of these questions. You will learn how to setup your Azure Key Vault, connect these secrets in ADF and finally deploy these secrets dynamically in Azure Dev Ops. As you can see a lot to talk about during this session.
Lake Database Database Template Map Data in Azure Synapse AnalyticsErwin de Kreuk
Database templates in Synapse Analytics are blueprints which can be used by organizations to plan, architect and design solutions.
How can we use these Database Templates in a day-to-day business, in order to speed up to automate this process?
Map data tool can help us with that
Databricks is a Software-as-a-Service-like experience (or Spark-as-a-service) that is a tool for curating and processing massive amounts of data and developing, training and deploying models on that data, and managing the whole workflow process throughout the project. It is for those who are comfortable with Apache Spark as it is 100% based on Spark and is extensible with support for Scala, Java, R, and Python alongside Spark SQL, GraphX, Streaming and Machine Learning Library (Mllib). It has built-in integration with many data sources, has a workflow scheduler, allows for real-time workspace collaboration, and has performance improvements over traditional Apache Spark.
Novell ZENworks Patch Management Best PracticesNovell
Since the first virus arrived on the IT scene, patching software has been a costly and time-consuming IT focus. In fact, “Patch Tuesdays” have come to symbolize the drain software patches place on organizations of every description. Attend this session to find out how Novell ZENworks Patch Management—working hand-in-hand with Novell ZENworks Configuration Management—can make Patch Tuesdays a thing of the past. You'll learn about the benefits of integrated patch and configuration management. You'll also receive tips, tricks and inside information to successfully deploy and troubleshoot Novell ZENworks 10 Patch Management and realize its true potential.
Microsoft Azure is the only hybrid cloud to help you migrate your apps, data, and infrastructure with cost-effective and flexible paths. At this event you’ll learn how thousands of customers have migrated to Azure, at their own pace and with high confidence by using a reliable methodology, flexible and powerful tools, and proven partner expertise. Come to this event to learn how Azure can help you save—before, during, and after migration, and how it offers unmatched value during every stage of your cloud migration journey. Learn about assessments, migration offers, and cost management tools to help you migrate with confidence.
Applying DevOps to Databricks can be a daunting task. In this talk this will be broken down into bite size chunks. Common DevOps subject areas will be covered, including CI/CD (Continuous Integration/Continuous Deployment), IAC (Infrastructure as Code) and Build Agents.
We will explore how to apply DevOps to Databricks (in Azure), primarily using Azure DevOps tooling. As a lot of Spark/Databricks users are Python users, will will focus on the Databricks Rest API (using Python) to perform our tasks.
Azure Synapse Analytics is Azure SQL Data Warehouse evolved: a limitless analytics service, that brings together enterprise data warehousing and Big Data analytics into a single service. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs. This is a huge deck with lots of screenshots so you can see exactly how it works.
Windows Azure Active Directory presentation will show you how to set up your Azure AD account and how to connect existing ASP.NET MVC Web Application with Azure Active Directory to provide Single-Sign-On
By using a Data Lake, you no longer need to worry about structuring or transforming data before storing it. A Data Lake on AWS enables your organization to more rapidly analyze data, helping you quickly discover new business insights. Join us for our webinar to learn about the benefits of building a Data Lake on AWS and how your organization can begin reaping their rewards. In this webinar, select APN Partners will share their specific methodology for implementing a Data Lake on AWS and best practices for getting the most from your Data Lake.
Azure Data Factory | Moving On-Premise Data to Azure Cloud | Microsoft Azure ...Edureka!
** Microsoft Azure Certification Training : https://www.edureka.co/microsoft-azure-training **
This Edureka "Azure Data Factory” tutorial will give you a thorough and insightful overview of Microsoft Azure Data Factory and help you understand other related terms like Data Lakes and Data Warehousing.
Following are the offering of this tutorial:
1. Why Azure Data Factory?
2. What Is Azure Data Factory?
3. Data Factory Concepts
4. What is Azure Data Lake?
5. Data Lake Concepts
6. Data Lake Vs Data Warehouse
7. Demo- Moving On-Premise Data To Cloud
Check out our Playlists: https://goo.gl/A1CJjM
here's where Microsoft has invested, across these areas: identity and access management, apps and data security, network security, threat protection, and security management.
We’ve put a tremendous amount of investment into these areas and the way it shows up is across a pretty broad array of product areas and features.
Our Identity and Access Management tools enable you to take an identity-based approach to security, and establish truly conditional access policies
Our App and Data Security help you protect your apps and your data as it moves around—both inside and outside your organization
Azure includes a robust networking infrastructure with built-in security controls for your application and service connectivity.
Our Threat Protection capabilities are built in and fully integrated, so you can strengthen both pre-breach protection with deep capabilities across e-mail, collaboration services, and end points including hardware based protection; and post-breach detection that includes memory and kernel based protection and response with automation.
And our Security Management tools give you the visibility and more importantly the guidance to manage policy centrally
SQL KONFERENZ 2020 Azure Key Vault, Azure Dev Ops and Azure Data Factory how...Erwin de Kreuk
Can we store our Connectionstrings or BlobStorageKeys or other Secretvalues somewhere else then in Azure Data Factory(ADF)? Yes you can! You can store these valuable secrets in Azure Key Vault(AKV).
But how can we achieve this in ADF? And finally how do we deploy our DataFactories in Azure Dev Ops to Test, Acceptance and Production environments with these Secrets ? Can this be setup dynamically?
During this session I will give answers on all of these questions. You will learn how to setup your Azure Key Vault, connect these secrets in ADF and finally deploy these secrets dynamically in Azure Dev Ops. As you can see a lot to talk about during this session.
Lake Database Database Template Map Data in Azure Synapse AnalyticsErwin de Kreuk
Database templates in Synapse Analytics are blueprints which can be used by organizations to plan, architect and design solutions.
How can we use these Database Templates in a day-to-day business, in order to speed up to automate this process?
Map data tool can help us with that
Integrating Jira Software Cloud With the AWS Code SuiteAtlassian
In this talk, Jay Yeras, Partner Solutions Architect at Amazon Web Services, will demonstrate how to customize, build, and host your Connect app on AWS.
Learn best practices on how to containerize the application and store a custom container image in Amazon ECR. Jay will share sample code based on AWS CloudFormation to quickly provision a highly scalable and fully managed container orchestration service running on AWS Fargate. Build a CI/CD pipeline using AWS CodePipeline, AWS CodeCommit and AWS CodeBuild for automated deployments. Lastly, deploy the solution as an Atlassian Marketplace app.
This solution provides customers using the AWS Code Suite of services with the ability to report on build state and other relevant data through AWS Lambda based integrations that leverage the Jira REST APIs to push relevant details about the status of the pipeline in near real-time to Jira Software Cloud.
DataSaturdayNL 2019 Azure Key Vault, Azure Dev Ops and Azure Data Factory h...Erwin de Kreuk
Can we store our Connectionstrings or BlobStorageKeys or other Secretvalues somewhere else then in Azure Data Factory(ADF)? Yes you can! You can store these valuable secrets in Azure Key Vault(AKV). But how can we achieve this in ADF? And finally how do we deploy our DataFactories in Azure Dev Ops to Test, Acceptance and Production environments with these Secrets ? Can this be setup dynamically? During this session I will give answers on all of these questions. You will learn how to setup your Azure Key Vault, connect these secrets in ADF and finally deploy these secrets dynamically in Azure Dev Ops. As you can see a lot to talk about during this session.
DatamindsConnect2019 Azure Key Vault, Azure Dev Ops and Azure Data Factory ho...Erwin de Kreuk
Can we store our Connectionstrings or BlobStorageKeys or other Secretvalues somewhere else then in Azure Data Factory(ADF)? Yes you can! You can store these valuable secrets in Azure Key Vault(AKV).
But how can we achieve this in ADF? And finally how do we deploy our DataFactories in Azure Dev Ops to Test, Acceptance and Production environments with these Secrets ? Can this be setup dynamically?
During this session I will give answers on all of these questions. You will learn how to setup your Azure Key Vault, connect these secrets in ADF and finally deploy these secrets dynamically in Azure Dev Ops. As you can see a lot to talk about during this session.
Continuous Integration and Deployment Best Practices on AWS (ARC307) | AWS re...Amazon Web Services
With AWS, companies now have the ability to develop and run their applications with speed and flexibility like never before. Working with an infrastructure that can be 100 percent API driven enables businesses to use lean methodologies and realize these benefits. This in turn leads to greater success for those who make use of these practices. In this session, we talk about some key concepts and design patterns for continuous deployment and continuous integration, two elements of lean development of applications and infrastructures.
Azure Resource Manager templates: Improve deployment time and reusabilityStephane Lapointe
Azure Resource Manager is the future of Azure and his templating features are a big improvement and simplification of how you provision resources on Azure. See how you can create ARM template in Visual Studio to create complex, multiple resources templates and how they can be combined and reused. Learn the different template functions available and how they can help you build more advanced template.
In this session, you learn how to set up a crawler to automatically discover your data and build your AWS Glue Data Catalog. You then auto-generate an AWS Glue ETL script, download it, and interactively edit it using a Zeppelin notebook, connected to an AWS Glue development endpoint. After that, you upload this script to Amazon S3, reuse it across multiple jobs, and add trigger conditions to run the jobs. The resulting datasets automatically get registered in the AWS Glue Data Catalog and you can then query these new datasets from Amazon EMR and Amazon Athena. Prerequisites: Knowledge of Python and familiarity with big data applications is preferred but not required. Attendees must bring their own laptops.
In this session, you learn how to set up a crawler to automatically discover your data and build your AWS Glue Data Catalog. You then auto-generate an AWS Glue ETL script, download it, and interactively edit it using a Zeppelin notebook, connected to an AWS Glue development endpoint. After that, you upload this script to Amazon S3, reuse it across multiple jobs, and add trigger conditions to run the jobs. The resulting datasets automatically get registered in the AWS Glue Data Catalog and you can then query these new datasets from Amazon EMR and Amazon Athena. Prerequisites: Knowledge of Python and familiarity with big data applications is preferred but not required. Attendees must bring their own laptops.
Making sense of Microsoft Identities in a Hybrid worldJason Himmelstein
Are you struggling to making heads or tails of the identity options for Office 365, Azure & onPrem installations? Does the seemingly ever changing landscape give you hives just thinking about the security implications? What are the recommended topologies & how in the world would you get started? If you have asked yourself any of these questions, you are not alone!
In this session we will walk through the concepts behind the new world of Identity Management, teach you about Azure Active Directory Connect, and explain some of the troubleshooting that you will likely need to do along the way. At the end of this session you will understand how to get your onPrem Identities synced to Azure & be on your way to enjoying all of the benefits of the Microsoft Cloud.
a talk about azure synapse aimed to help people who are not data experts understand what synapse is and how you can integrate it with other technologies
Apache Ambari at the Apache Big Data Conference in Miami on May 18, 2017
presented by Alejandro Fernandez
Using Apache Ambari for enterprises with Blueprints, Custom Services, Stack Advisor, Kerberos, Large Scale, Rolling/Express Upgrades, Alerts, Metrics, and Log Search.
Machine learning services with SQL Server 2017Mark Tabladillo
SQL Server 2017 introduces Machine Learning Services with two independent technologies: R and Python. The purpose of this presentation is 1) to describe major features of this technology for technology managers; 2) to outline use cases for architects; and 3) to provide demos for developers and data scientists.
Building data pipelines for modern data warehouse with Apache® Spark™ and .NE...Michael Rys
This presentation shows how you can build solutions that follow the modern data warehouse architecture and introduces the .NET for Apache Spark support (https://dot.net/spark, https://github.com/dotnet/spark)
Is there a way that we can build our Azure Synapse Pipelines all with paramet...Erwin de Kreuk
Is there a way that we can build our Synapse Data Pipelines all with parameters all based on MetaData? Yes there's and I will show you how to. During this session I will show how you can load Incremental or Full datasets from your sql database to your Azure Data Lake. The next step is that we want to track our history from these extracted tables. We will do using Delta Lake. The last step that we want, is to make this data available in Azure SQL Database or Azure Synapse Analytics. Oh and we want to have some logging as well from our processes A lot to talk and to demo about during this session.
Is there a way that we can build our Azure Data Factory all with parameters b...Erwin de Kreuk
Is there a way that we can build our Data Factory all with parameters all based on MetaData? Yes there's and I will show you how to. During this session I will show how you can load Incremental or Full datasets from your sql database to your Azure Data Lake. The next step is that we want to track our history from these extracted tables. We will do this with Azure Databricks using Delta Lake. The last step that we want, is to make this data available in Azure SQL Database or Azure Synapse Analytics. Oh and we want to have some logging as well from our processes A lot to talk and to demo about during this session.
Help, I need to migrate my On Premise Database to Azure, which Database Tier ...Erwin de Kreuk
During this session we will walk you through all the different Tiers in Azure, DTU, Vcore, Serverless and Managed Instance and will provide examples when to use which Tier.
We will also show you the Microsoft Data Migration Assesment (DMA). This tool will help you to decide which tier you should choose. So if you need help or just interested in the different Azure Database Tiers then visit our session
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
StarCompliance is a leading firm specializing in the recovery of stolen cryptocurrency. Our comprehensive services are designed to assist individuals and organizations in navigating the complex process of fraud reporting, investigation, and fund recovery. We combine cutting-edge technology with expert legal support to provide a robust solution for victims of crypto theft.
Our Services Include:
Reporting to Tracking Authorities:
We immediately notify all relevant centralized exchanges (CEX), decentralized exchanges (DEX), and wallet providers about the stolen cryptocurrency. This ensures that the stolen assets are flagged as scam transactions, making it impossible for the thief to use them.
Assistance with Filing Police Reports:
We guide you through the process of filing a valid police report. Our support team provides detailed instructions on which police department to contact and helps you complete the necessary paperwork within the critical 72-hour window.
Launching the Refund Process:
Our team of experienced lawyers can initiate lawsuits on your behalf and represent you in various jurisdictions around the world. They work diligently to recover your stolen funds and ensure that justice is served.
At StarCompliance, we understand the urgency and stress involved in dealing with cryptocurrency theft. Our dedicated team works quickly and efficiently to provide you with the support and expertise needed to recover your assets. Trust us to be your partner in navigating the complexities of the crypto world and safeguarding your investments.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
5. InSpark
Azure Synapse Studio
Integration Management Monitoring Security
Analytics runtimes
Azure Data Lake Storage
Azure Synapse Analytics
Resource Group Development Resource Group Production
Integration runtimes Integration runtimes
Workspace
Workspace Item
Apache Spark Pool Integration
Runtime
Linked Services Credentials
Data Engineers
Data Scientists
Azure Synapse Studio
Integration Management Monitoring Security
Analytics runtimes
Azure Data Lake Storage
Azure Synapse Analytics
Integration runtimes
Workspace
Workspace Item
Apache Spark Pool Integration
Runtime
Linked Services Credentials
6. InSpark
Azure Synapse Studio
Integration Management Monitoring Security
Analytics runtimes
Azure Data Lake Storage
Azure Synapse Analytics
Resource Group Development
Integration runtimes
Workspace
Workspace Item
Apache Spark Pool Integration
Runtime
Linked Services Credentials
7. InSpark
Azure Synapse Analytics
Resource Group Development
Azure Owner or Contributor
Resource Group
Create Synapse Workspace
Manage Synapse Workspace
Synapse Resource
Manage Synapse Workspace
Azure Contributor
Resource Group
ARM templates for automated deployment
Resource Management
Azure Roles
8. InSpark
Azure Synapse Analytics
Resource Group Development
Azure Storage Blob Data Contributor
User and workspace MSI
Reader
Resource Group or Synapse Workspace
Access Management
Azure Roles
Azure Data Lake Storage
10. InSpark
Azure Synapse Analytics
Resource Group Development
Roles:
Synapse Administrator
Synapse SQL Administrator
Synapse Apache Spark Administrator
SQL Active Directory Admin
Administrators
Synapse Roles
Azure Data Lake Storage
Analytics runtimes Integration runtimes
11. InSpark
Activities:
Can read and write artifacts
Can do all actions on Spark activities.
Can view Spark pool logs
Can view saved notebook and pipeline output
Can use the secrets stored by linked services or credentials
Can assign and revoke Synapse RBAC roles at current scope
Synapse Administrator
Synapse Roles
12. InSpark
Activities:
Can do all actions on Spark artifacts
Can do all actions on Spark activities
Synapse Apache Spark Administrator
Synapse Roles
13. InSpark
Activities:
Can do all actions on SQL scripts
Can connect to SQL serverless endpoints with SQL db_datareader,
db_datawriter, connect, and grant permissions
Synapse SQL Administrator
Synapse Roles
18. InSpark
Item:
Linked Service
Apache Spark Pool
Integration Runtime
Credentials
Workspace Item
Synapse Roles
Azure Synapse Studio
Integration Management Monitoring Security
Analytics runtimes
Azure Data Lake Storage
Azure Synapse Analytics
Resource Group Development
Integration runtimes
Workspace
Workspace Item
Apache Spark Pool Integration
Runtime
Linked Services Credentials
19. InSpark
Role assignment on Workspace or Workspace Item
Needs to be Synapse Administrator
Can also be a guest user
No Synapse Administrator
Contributor or Owner on the Workspace
Advice! => create role assignments based on
Security Groups
Changes in assignments will take up 2-5 minutes
Changes in SG can take 10-15 minutes
Role Assignment
Synapse Roles
20. InSpark
No access message in Azure Portal
https://web.azuresynapse.net
Tips and Tricks
Synapse Roles
21. InSpark
No access message in Azure Portal
https://web.azuresynapse
Power BI
Access is defined on Power BI workspace level
Tips and Tricks
Synapse Roles
22. InSpark
No access message in Azure Portal
https://web.azuresynapse
Power BI
Access is defined on Power BI workspace level
Publish Error
Tips and Tricks
Synapse Roles
26. InSpark
Synapse Administrator:
db_owner (DBO) permissions on the ‘Built-In’
serverless SQL pool
Synapse SQL Administrator:
Can do all actions on SQL scripts
Can connect to SQL serverless endpoints with SQL
db_datareader, db_datawriter, connect, and grant
permissions
Serverless SQL Pool
SQL
Serverless
27. InSpark
Synapse Administrator:
Full access to data in dedicated SQL pools
Grant access to other users
Perform configuration and maintenance activities
Can't drop dedicated SQL pools
Synapse SQL Administrator:
No access by default
Active Directory Admin:
Full access
Dedicated SQL Pool
SQL
Dedicated
28. InSpark
Serverless SQL pool:
Dedicated SQL pool:
SQL Pools
SQL
Dedicated
Serverless
use master
go
CREATE LOGIN [erwin.de.kreuk@demo.com] FROM EXTERNAL PROVIDER;
go
use yourdb -- Use your database name
go
CREATE USER demouser FROM LOGIN [erwin.de.kreuk@demo.com];
use yourdb -- Use your database name
go
alter role db_owner Add member demouser
--Create user in the database
CREATE USER [erwin.dekreuk@gmail.com] FROM EXTERNAL PROVIDER;
--Grant role to the user in the database
EXEC sp_addrolemember 'db_owner', 'erwin.dekreuk@gmail.com';
30. InSpark
Azure Dev Ops:
Basic user settings
Azure Artifact Publisher
Azure Contributor (Azure RBAC) or higher role on
the Synapse workspace
Dev Ops Service Connection:
Azure Contributor (Azure RBAC) or higher role on
the Resource Group
Azure Synapse Administrator
Azure Dev Ops
GIT Integration
31. InSpark
Azure Synapse Studio
Integration Management Monitoring Security
Analytics runtimes
Azure Data Lake Storage
Azure Synapse Analytics
Azure Synapse Studio
Integration Management Monitoring Security
Azure Data Lake Storage
Azure Synapse Analytics
Resource Group Development Resource Group Production
Integration runtimes Analytics runtimes Integration runtimes
Workspace
Workspace Item
Apache Spark Pool Integration
Runtime
Linked Services Credentials
Workspace Item
Apache Spark Pool Integration
Runtime
Linked Services Credentials
Workspace
Data Engineers
Data Scientists
32. InSpark
Data Engineers
Needs to access SQL Serverless
Publish or edit Code
Debug pipelines
Data Scientist:
Needs to access SQL Serverless
Needs access to a specified Spark Pool
Publish or edit Code
Submit Spark Jobs
Security Groups
Azure Synapse Studio
Integration Management Monitoring Security
Analytics runtimes
Azure Data Lake Storage
Azure Synapse Analytics
Resource Group Development
Integration runtimes
Workspace
Workspace Item
Apache Spark Pool Integration
Runtime
Linked Services Credentials
Data Engineers
Data Scientists
