- The document discusses real-time options in Power BI including push, streaming, and PubNub data. It describes the characteristics of each option including refresh rates, visual capabilities, and advantages/limitations.
- A case study is presented on creating a dashboard to monitor warehouse workload in real-time using a hybrid dataset with data pushed from SQL Server and SAP HANA via REST APIs into Power BI. PowerApps is also suggested for creating mobile apps connected to the real-time data.
- Additional resources are provided on real-time streaming documentation, tutorials for IoT dashboards and connecting Azure Stream Analytics, and using PubNub streams in Power BI.
Marco Pozzan
Power BI consultant & Trainer
Scenario di utilizzo del real-time di Power BI. In questa sessione verrà introdotta la teoria sul real-time dashboarding offerto da Power BI. Poi ci si focalizzerà sun un caso pratico di real-time dataset in modalità ibrida per la realizzazione di una dashboard di controllo con la possibilità di effettuare il write back e permettere all’utente di effettuare analisi what-if.
Explore Your Data Using Amazon QuickSight and Build Your First Machine Learni...Amazon Web Services
In this session we will demonstrate how non-experts in machine learning, can easily analyze their data with QuickSight and build scalable and production-ready predictive models with Amazon machine learning. After the session you will have a good understanding how to define problems from your business, in terms of data and predictive models, and you will be able to apply analytics and machine learning concepts as a competitive advantage.
Modern business is fast and needs to take decisions immediatly. It cannot wait that a traditional BI task that works on data snapshots at some time. Social data, Internet of Things, Just in Time don't undestand "snapshot" and needs working on streaming, live data. Microsoft offers a PaaS solution to satisfy this need with Azure Stream Analytics. Let's see how it works.
Event: Passcamp, 07.12.2017
Speaker: Stefan Kirner
Mehr Tech-Vorträge: https://www.inovex.de/de/content-pool/vortraege/
Mehr Tech-Artikel: https://www.inovex.de/blog
Azure Data Factory is one of the newer data services in Microsoft Azure and is part of the Cortana Analyics Suite, providing data orchestration and movement capabilities.
This session will describe the key components of Azure Data Factory and take a look at how you create data transformation and movement activities using the online tooling. Additionally, the new tooling that shipped with the recently updated Azure SDK 2.8 will be shown in order to provide a quickstart for your cloud ETL projects.
Marco Pozzan
Power BI consultant & Trainer
Scenario di utilizzo del real-time di Power BI. In questa sessione verrà introdotta la teoria sul real-time dashboarding offerto da Power BI. Poi ci si focalizzerà sun un caso pratico di real-time dataset in modalità ibrida per la realizzazione di una dashboard di controllo con la possibilità di effettuare il write back e permettere all’utente di effettuare analisi what-if.
Explore Your Data Using Amazon QuickSight and Build Your First Machine Learni...Amazon Web Services
In this session we will demonstrate how non-experts in machine learning, can easily analyze their data with QuickSight and build scalable and production-ready predictive models with Amazon machine learning. After the session you will have a good understanding how to define problems from your business, in terms of data and predictive models, and you will be able to apply analytics and machine learning concepts as a competitive advantage.
Modern business is fast and needs to take decisions immediatly. It cannot wait that a traditional BI task that works on data snapshots at some time. Social data, Internet of Things, Just in Time don't undestand "snapshot" and needs working on streaming, live data. Microsoft offers a PaaS solution to satisfy this need with Azure Stream Analytics. Let's see how it works.
Event: Passcamp, 07.12.2017
Speaker: Stefan Kirner
Mehr Tech-Vorträge: https://www.inovex.de/de/content-pool/vortraege/
Mehr Tech-Artikel: https://www.inovex.de/blog
Azure Data Factory is one of the newer data services in Microsoft Azure and is part of the Cortana Analyics Suite, providing data orchestration and movement capabilities.
This session will describe the key components of Azure Data Factory and take a look at how you create data transformation and movement activities using the online tooling. Additionally, the new tooling that shipped with the recently updated Azure SDK 2.8 will be shown in order to provide a quickstart for your cloud ETL projects.
Data Warehouse Modernization - Big Data in the Cloud Success with Qubole on O...Qubole
The effective use of big data is the key to gaining a competitive advantage and outperforming the competition. This change demands that companies consume and blend enormous amount of data created from divergent and inherently mismatched sources, which represents a paradigm shift to the traditional data warehouse.
Companies need to modernize their data warehouse, augmenting it with a platform that allows storage, processing, exploration and analysis of large and diverse datasets without limiting the ability to deliver the data access, and flexibility responding to the needs of the business. That’s where Oracle Cloud and Qubole work together delivering a new breed of data platform —capable of storing and processing the overwhelming amount of data that on-premises big data deployments cannot handle.
Watch this on-demand webinar to understand:
- Why deploying big data on-premises is expensive, complex to maintain and limits your ability to scale across new use cases and data sources
- How Oracle Bare Metal Cloud's predictable and fast performance compute and network services deliver the foundation of a cost-effective, high-performance big data platform
- How Qubole leverages Oracle Bare Metal Cloud to provide a turnkey big data service that optimizes cost, performance, and scale, enabling self-service data exploration.
Qubole delivers a cloud-based, turnkey, self-service big data service that removes the complexity and reduces the cost of doing big data. It leverages Oracle Bare Metal Cloud’s next generation of scalable, inexpensive and performant compute, network and storage public cloud infrastructure to provide a solution that accelerates time to market and reduces the risk of your big data initiatives.
Migrate a successful transactional database to azureIke Ellis
This slide deck will show you techniques and technologies necessary to take a large, transaction SQL Server database and migrate it to Azure, Azure SQL Database, and Azure SQL Database Managed Instance
Microsoft Ignite AU 2017 - Orchestrating Big Data Pipelines with Azure Data F...Lace Lofranco
Data orchestration is the lifeblood of any successful data analytics solution. Take a deep dive into Azure Data Factory's data movement and transformation activities, particularly its integration with Azure's Big Data PaaS offerings such as HDInsight, SQL Data warehouse, Data Lake, and AzureML. Participants will learn how to design, build and manage big data orchestration pipelines using Azure Data Factory and how it stacks up against similar Big Data orchestration tools such as Apache Oozie.
Video of presentation:
https://channel9.msdn.com/Events/Ignite/Australia-2017/DA332
Hello All,
It is time for the second Tokyo Azure Meetup!
As a natural continuation of our first topic, we will proceed with Big Data.
Until recently you needed to learn new language or master new concepts in order get started with Big Data.
Moreover, you needed to spend a lot of time setting up infrastructure that will meet the business demands for Big Data processing.
Not any more!
If you know C# and T-SQL you are ready to become Big Data master!
Public cloud and especially Microsoft Azure are very well suited for working with Big Data.
Join us for our next event and and I can assure you that after the session you will be ready to start working with Big Data.
And maybe you are asking why this is important.
I believe that we don't have choice but build smart applications and get as much possible insights from the data we collect from various sources in order to take the best business decisions and please our customers.
Today we have so much data available publicly or coming from our customers and it is very challenging to process it and turn it into valuable business asset.
Not any more!
Join for our next meetup and you will see how Microsoft create amazing opportunity for each .Net developer to become Big Data expert and every company to start using Big Data to accelerate its growth.
I have been working closely with the product team developing U-SQL language that empower Azure Data Lake Analytics, which is one of the processing engines for Azure Data Lake and I will be very happy to share my experience with you!
See you very soon!
Kanio
This presentation covers some of the major data science and AI announcements from the May 2020 Microsoft Build conference. Included in this talk are 1) Azure Synapse Link, 2) Responsible AI, 3) Project Bonsai & Project Moab, and 4) AI Models at Scale (deep learning with billions of parameters).
Large companies see an opportunity to replace expensive legacy data warehouse applications with Big Data technologies. But how realistic is the notion of switching from tried and true data warehouse implementations to something that's still maturing, and what are the pitfalls? What will a business user need to learn in order to adapt to the new platform?
This presentation examines some of the top stream analytic platforms in the enterprise. The slide deck explores the characteristics of enterprise stream analytic solutions and discusses the capabilties of some of the top stream analytic platform in the current market.
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.
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
Analyzing StackExchange data with Azure Data LakeBizTalk360
Big data is the new big thing where storing the data is the easy part. Gaining insights in your pile of data is something different. Based on a data dump of the well-known StackExchange websites, we will store & analyse 150+ GB of data with Azure Data Lake Store & Analytics to gain some insights about their users. After that we will use Power BI to give an at a glance overview of our learnings.
If you are a developer that is interested in big data, this is your time to shine! We will use our existing SQL & C# skills to analyse everything without having to worry about running clusters.
Analysing data analytics use cases to understand big data platformdataeaze systems
Get big picture of data platform architecture by knowing its purpose and problem it solves.
These slides take top down approach, starting with basic purpose of data platform ie. to serve analytics use cases. These slides categorise use cases and analyses their expectation from data platform.
Enterprise Data World 2018 - Building Cloud Self-Service Analytical SolutionDmitry Anoshin
This session will cover building the modern Data Warehouse by migration from the traditional DW platform into the cloud, using Amazon Redshift and Cloud ETL Matillion in order to provide Self-Service BI for the business audience. This topic will cover the technical migration path of DW with PL/SQL ETL to the Amazon Redshift via Matillion ETL, with a detailed comparison of modern ETL tools. Moreover, this talk will be focusing on working backward through the process, i.e. starting from the business audience and their needs that drive changes in the old DW. Finally, this talk will cover the idea of self-service BI, and the author will share a step-by-step plan for building an efficient self-service environment using modern BI platform Tableau.
Cherokee nation 2 day AIAD & DIAD - App in a day and Dashboard in dayVishal Pawar
Cherokee nation 2 day AIAD & DIAD - App in a day and Dashboard in day
Power Apps: A software as a service application platform that enables power users in line of business
roles to easily build and deploy custom business apps. You will learn how to build Canvas and Modeldriven
style of apps.
Common Data Service (CDS): Make it easier to bring your data together and quickly create powerful
apps using a compliant and scalable data service and app platform that’s integrated into Power Apps.
Power Automate: A business service for line of business specialists and IT pros to build automated
workflows intuitively.
Power BI: Self-service business intelligence capabilities, where end users can create reports and
dashboards by themselves, without having to depend on information technology staff or database
administrators.
Data Warehouse Modernization - Big Data in the Cloud Success with Qubole on O...Qubole
The effective use of big data is the key to gaining a competitive advantage and outperforming the competition. This change demands that companies consume and blend enormous amount of data created from divergent and inherently mismatched sources, which represents a paradigm shift to the traditional data warehouse.
Companies need to modernize their data warehouse, augmenting it with a platform that allows storage, processing, exploration and analysis of large and diverse datasets without limiting the ability to deliver the data access, and flexibility responding to the needs of the business. That’s where Oracle Cloud and Qubole work together delivering a new breed of data platform —capable of storing and processing the overwhelming amount of data that on-premises big data deployments cannot handle.
Watch this on-demand webinar to understand:
- Why deploying big data on-premises is expensive, complex to maintain and limits your ability to scale across new use cases and data sources
- How Oracle Bare Metal Cloud's predictable and fast performance compute and network services deliver the foundation of a cost-effective, high-performance big data platform
- How Qubole leverages Oracle Bare Metal Cloud to provide a turnkey big data service that optimizes cost, performance, and scale, enabling self-service data exploration.
Qubole delivers a cloud-based, turnkey, self-service big data service that removes the complexity and reduces the cost of doing big data. It leverages Oracle Bare Metal Cloud’s next generation of scalable, inexpensive and performant compute, network and storage public cloud infrastructure to provide a solution that accelerates time to market and reduces the risk of your big data initiatives.
Migrate a successful transactional database to azureIke Ellis
This slide deck will show you techniques and technologies necessary to take a large, transaction SQL Server database and migrate it to Azure, Azure SQL Database, and Azure SQL Database Managed Instance
Microsoft Ignite AU 2017 - Orchestrating Big Data Pipelines with Azure Data F...Lace Lofranco
Data orchestration is the lifeblood of any successful data analytics solution. Take a deep dive into Azure Data Factory's data movement and transformation activities, particularly its integration with Azure's Big Data PaaS offerings such as HDInsight, SQL Data warehouse, Data Lake, and AzureML. Participants will learn how to design, build and manage big data orchestration pipelines using Azure Data Factory and how it stacks up against similar Big Data orchestration tools such as Apache Oozie.
Video of presentation:
https://channel9.msdn.com/Events/Ignite/Australia-2017/DA332
Hello All,
It is time for the second Tokyo Azure Meetup!
As a natural continuation of our first topic, we will proceed with Big Data.
Until recently you needed to learn new language or master new concepts in order get started with Big Data.
Moreover, you needed to spend a lot of time setting up infrastructure that will meet the business demands for Big Data processing.
Not any more!
If you know C# and T-SQL you are ready to become Big Data master!
Public cloud and especially Microsoft Azure are very well suited for working with Big Data.
Join us for our next event and and I can assure you that after the session you will be ready to start working with Big Data.
And maybe you are asking why this is important.
I believe that we don't have choice but build smart applications and get as much possible insights from the data we collect from various sources in order to take the best business decisions and please our customers.
Today we have so much data available publicly or coming from our customers and it is very challenging to process it and turn it into valuable business asset.
Not any more!
Join for our next meetup and you will see how Microsoft create amazing opportunity for each .Net developer to become Big Data expert and every company to start using Big Data to accelerate its growth.
I have been working closely with the product team developing U-SQL language that empower Azure Data Lake Analytics, which is one of the processing engines for Azure Data Lake and I will be very happy to share my experience with you!
See you very soon!
Kanio
This presentation covers some of the major data science and AI announcements from the May 2020 Microsoft Build conference. Included in this talk are 1) Azure Synapse Link, 2) Responsible AI, 3) Project Bonsai & Project Moab, and 4) AI Models at Scale (deep learning with billions of parameters).
Large companies see an opportunity to replace expensive legacy data warehouse applications with Big Data technologies. But how realistic is the notion of switching from tried and true data warehouse implementations to something that's still maturing, and what are the pitfalls? What will a business user need to learn in order to adapt to the new platform?
This presentation examines some of the top stream analytic platforms in the enterprise. The slide deck explores the characteristics of enterprise stream analytic solutions and discusses the capabilties of some of the top stream analytic platform in the current market.
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.
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
Analyzing StackExchange data with Azure Data LakeBizTalk360
Big data is the new big thing where storing the data is the easy part. Gaining insights in your pile of data is something different. Based on a data dump of the well-known StackExchange websites, we will store & analyse 150+ GB of data with Azure Data Lake Store & Analytics to gain some insights about their users. After that we will use Power BI to give an at a glance overview of our learnings.
If you are a developer that is interested in big data, this is your time to shine! We will use our existing SQL & C# skills to analyse everything without having to worry about running clusters.
Analysing data analytics use cases to understand big data platformdataeaze systems
Get big picture of data platform architecture by knowing its purpose and problem it solves.
These slides take top down approach, starting with basic purpose of data platform ie. to serve analytics use cases. These slides categorise use cases and analyses their expectation from data platform.
Enterprise Data World 2018 - Building Cloud Self-Service Analytical SolutionDmitry Anoshin
This session will cover building the modern Data Warehouse by migration from the traditional DW platform into the cloud, using Amazon Redshift and Cloud ETL Matillion in order to provide Self-Service BI for the business audience. This topic will cover the technical migration path of DW with PL/SQL ETL to the Amazon Redshift via Matillion ETL, with a detailed comparison of modern ETL tools. Moreover, this talk will be focusing on working backward through the process, i.e. starting from the business audience and their needs that drive changes in the old DW. Finally, this talk will cover the idea of self-service BI, and the author will share a step-by-step plan for building an efficient self-service environment using modern BI platform Tableau.
Cherokee nation 2 day AIAD & DIAD - App in a day and Dashboard in dayVishal Pawar
Cherokee nation 2 day AIAD & DIAD - App in a day and Dashboard in day
Power Apps: A software as a service application platform that enables power users in line of business
roles to easily build and deploy custom business apps. You will learn how to build Canvas and Modeldriven
style of apps.
Common Data Service (CDS): Make it easier to bring your data together and quickly create powerful
apps using a compliant and scalable data service and app platform that’s integrated into Power Apps.
Power Automate: A business service for line of business specialists and IT pros to build automated
workflows intuitively.
Power BI: Self-service business intelligence capabilities, where end users can create reports and
dashboards by themselves, without having to depend on information technology staff or database
administrators.
Pascua Yaqui Tribe App in a day and dashboard in dayVishal Pawar
Microsoft organized app in a day and dashboard in a day, Learn and gain insight of Power Platform. App in a day and dashboard in a day are one-day learning events.
Analytics at the Speed of Thought: Actian Express Overview Actian Corporation
Deliver faster insight – reduce query response times to seconds
Analyze more data faster – explore billions of rows of data in seconds
More concurrent users – enable more concurrent BI users to explore more data
Utilized the Twitter WPF client to extract data based on Hashtags and fed to sentiment140 for sentiment analysis.
Loaded sentiment analyzed tweets in Azure using event hubs and performed analysis using SQL in stream analytics
Stored the analyzed data in Azure Blob Storage and visualized the outcomes of analysis in real time using Power BI
Most data visualisation solutions today still work on data sources which are stored persistently in a data store, using the so called “data at rest” paradigms. More and more data sources today provide a constant stream of data, from IoT devices to Social Media streams. These data stream publish with high velocity and messages often have to be processed as quick as possible. For the processing and analytics on the data, so called stream processing solutions are available. But these only provide minimal or no visualisation capabilities. One was is to first persist the data into a data store and then use a traditional data visualisation solution to present the data.
If latency is not an issue, such a solution might be good enough. An other question is which data store solution is necessary to keep up with the high load on write and read. If it is not an RDBMS but an NoSQL database, then not all traditional visualisation tools might already integrate with the specific data store. An other option is to use a Streaming Visualisation solution. They are specially built for streaming data and often do not support batch data. A much better solution would be to have one tool capable of handling both, batch and streaming data. This talk presents different architecture blueprints for integrating data visualisation into a fast data solution and highlights some of the products available to implement these blueprints.
POWER BI Training From SQL SchoolV2.pptxSequelGate
#PowerBIOnlineTraining from #SQLSchool
100% Realtime, Practical classes with Project Work and Resume.
100% Interactive Classes with Concept wise FAQs.
Power BI Training Highlights
> 100% HandsOn, Real-time
> Concept wise FAQs
> Real-time Project
> Azure Intergrations
> PL 300 Exam Guidance
Short Demo: https://youtu.be/cEm1wI-UClI
Register for Free Demo: https://www.sqlschool.com/PowerBI-Online-Training.html
New batch every 15 days.
Reach Us (24x7)
contact@sqlschool.com
+91 9666 44 0801 (India)
+91 9030 04 0801 (India)
+1 (956) 825-0401 (USA)
Tools For Report Design:
1. Power BI Desktop [For Power BI Service OR Power BI Cloud]
2. Power BI Desktop RS [For Power BI Report Server]
3. Power BI Report Builder [For Power BI Service or Power BI Cloud]
4. MICROSOFT Report Builder [For Power BI Report Server]
5. EXCEL Analytics
6. Mobile Report Publisher [For Reports Compatible with Mobiles, Tabs]
7. Data Gateway [For Data Refresh & LIVE Data Loads]
Production Environments
8. Power BI Cloud [SERVICE]
9. Power BI Report SERVER Technologies:
10. Power Query [For ETL: Data Extraction, Transformation, Data Loads]
11. DAX [Data Analysis Expressions: for Calculations, Analytics]
Advantages of Power BI:
1. Cheaper
2. Free Power BI Report Server
3. Free Power BI Design Tools
4. Easy to use
5. Suitable for BIG DATA Analytics
6. Easy Integration with any Cloud
Our Course Includes :
1. Day wise Notes
2. Study Material
3. Microsoft Certification Guidance (PL 300)
4. Interview FAQs
5. Project Work
6. Project FAQs
7. Scenarios & Solutions
For Clarifications, Career Guidance:
Call / Whatsapp: +919030040801
Choose #SQLSchool for your Trainings.
100% Job Oriented Trainings, Real-time Projects.
For Free Demo: +919666440801
Details Available at: www.sqlschool.com/courses.html
What this Power BI course includes?
This Power BI Training includes EVERY detail. From very basics - Installation, details of each Power BI Visual, On-premise and Cloud Data Access, Azure Integration, Data Modelling and ETL Techniques, Power Query (M Language), DAX Functions, Variables, Parameters, Power BI Dashboards, App Workspace, Data Gateways, Alerts, Power BI Report Server Components, Power BI Mobile Reports, Excel Integration, Excel Analysis, KPIs, Microsoft PL 300 Certification guidance, Resume Guidance, Concept wise Interview FAQs and ONE Real-time Project.
#LearnPowerBI From #SQLSchool
Upskill Yourself Today.
Power BI Training Demo Video: https://youtu.be/wbhd89wJvos
100% Real-time. Project Oriented, Job Oriented #DirectToDesk #ScenarioBased #CloudIntegrations
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.
AWS Summit Stockholm 2014 – B4 – Business intelligence on AWSAmazon Web Services
Business intelligence is often described as a set of methodologies and technologies that transform raw data into meaningful and useful information for business purposes. But this simple description hides many technical challenges IT teams struggle with. This session will show how to build business intelligence applications leveraging AWS, from the raw data import, consumption and storage down to the information production. We will also cover best practices for services such as Amazon Redshift or Amazon RDS, and how to use applications such as SAP Hana, Jaspersoft and others.
Geek Sync | Deployment and Management of Complex Azure EnvironmentsIDERA Software
You can watch the replay of this Geek Sync webinar in the IDERA Resource Center: http://ow.ly/pg7N50A4svf.
Today's data management professional is finding their landscape changing. They have multiple database platforms to manage, multi-OS environments and everyone wants it now.
Join IDERA and Kellyn Pot’Vin-Gorman as she discusses the power of auto deployment in Azure when faced with complex environments and tips to increase the knowledge you need at the speed of light. Kellyn will cover scripting basics, advanced Portal features, opportunities to lessen the learning curve and how multi-platform and tier doesn't have to mean multi-cloud.
Attendees can expect to learn how to build automation scripts efficiently, even if you have little scripting experience, and how to work with Azure automation deployments. This session will allow you to begin building a repository of multi-platform development scripts to use as needed.
About Kellyn: Kellyn Pot’Vin-Gorman is a member of the Oak Table Network and an IDERA ACE and Oracle ACE Director alumnus. She is the newest Technical Solution Professional in Power BI with AI in the EdTech group at Microsoft. Kellyn is known for her extensive work with multi-database platforms, DevOps, cloud migrations, virtualization, visualizations, scripting, environment optimization tuning, automation, and architecture design. She has spoken at numerous technical conferences for Oracle, Big Data, DevOps, Testing and SQL Server. Her blog, http://dbakevlar.com and social media activity under her handle, DBAKevlar is well respected for her insight and content.
Today, data lakes are widely used and have become extremely affordable as data volumes have grown. However, they are only meant for storage and by themselves provide no direct value. With up to 80% of data stored in the data lake today, how do you unlock the value of the data lake? The value lies in the compute engine that runs on top of a data lake.
Join us for this webinar where Ahana co-founder and Chief Product Officer Dipti Borkar will discuss how to unlock the value of your data lake with the emerging Open Data Lake analytics architecture.
Dipti will cover:
-Open Data Lake analytics - what it is and what use cases it supports
-Why companies are moving to an open data lake analytics approach
-Why the open source data lake query engine Presto is critical to this approach
How to choose between SharePoint lists, SQL Azure, Microsoft Dataverse with D...serge luca
Our European Collaboration Summit 2021 slides (with Isabelle Van Campenhoudt and serge Luca)
How to choose between SharePoint lists, SQL Azure, Microsoft Dataverse with Doctor Flow and Isa
Sql Saturday Jacksonville- Power BI Report Server Enterprise Architecture, to...Vishal Pawar
Sql Saturday Jacksonville- Power BI Report Server Enterprise Architecture, tools to publish reports and best practice
Power BI Ecosystem
Architecture of Power BI Report Server
Best Practices for PBI Report Server
General Best Practices Power BI Ecosystem
Q&A
Search on the fly: how to lighten your Big Data - Simona Russo, Auro Rolle - ...Codemotion
The talk presents a new technique of realtime single entity information extraction and investigation. The technique eliminates regular refresh and persistence of data within the search engine (ETL), providing real-time access to source data and improving response times using in-memory data techniques. The solution presented is a concrete solution with live customers, based upon real business needs. I will explain the architectural overview, the technology stack used based on Apache Lucene library, the accomplished results and how to scale out the solution.
With Power BI you can bring your BI architecture to the next level.
Architecture it's very important topic in a business intelligence project, let's discover which are right questions and possible scenarios to integrate Power BI in an existing environment or to build a new one from scratch.
We'll talkabout how to choose the right Storage Modes, how to design a refreshing policy, how to use dataflows to decouple and to lift the transformation process on Cloud and more.
SQL Bits 2018 | Best practices for Power BI on implementation and monitoring Bent Nissen Pedersen
This session is intended to do a deep dive into the Power BI Service and infrastructure to ensure that you are able to monitor your solution before it starts performing or when your users are already complaining.As part of the session i will give advise you on how to address the main pains causing slow performance by answering the following questions:
* What are the components of the Power BI Service?
- DirectQuery
- Live connection
- Import
* How do you identify a bottleneck?
* What should i do to fix performance?
* Monitoring
- What parts to monitor and why?
* What are the report developers doing wrong?
- how do i monitor the different parts?
* Overview of best practices and considerations for implementations
Power BI: Introduzione ai dataflow e alla preparazione dei dati self-serviceMarco Pozzan
Power BI Dataflow è il componente di trasformazione dei dati in Power BI. È un processo di Power Query che viene eseguito nel cloud. Bene, questa potrebbe non sembrare una funzionalità molto nuova, giusto? Quindi cosa c'è di nuovo con Dataflow? Le risposte alle vostre domande saranno nella mia sessione :-)
Analysts spend up to 80% of their time on data preparation delaying the time to analysis and decision making.” -Analysts spend up to 80% of their time on data preparation delaying the time to analysis and decision making.” Gartner
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
Gamify Your Mind; The Secret Sauce to Delivering Success, Continuously Improv...Shahin Sheidaei
Games are powerful teaching tools, fostering hands-on engagement and fun. But they require careful consideration to succeed. Join me to explore factors in running and selecting games, ensuring they serve as effective teaching tools. Learn to maintain focus on learning objectives while playing, and how to measure the ROI of gaming in education. Discover strategies for pitching gaming to leadership. This session offers insights, tips, and examples for coaches, team leads, and enterprise leaders seeking to teach from simple to complex concepts.
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Venez le découvrir lors de cette session ignite
AI Pilot Review: The World’s First Virtual Assistant Marketing SuiteGoogle
AI Pilot Review: The World’s First Virtual Assistant Marketing Suite
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https://sumonreview.com/ai-pilot-review/
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See My Other Reviews Article:
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(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
top nidhi software solution freedownloadvrstrong314
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Understanding Globus Data Transfers with NetSageGlobus
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
Software Engineering, Software Consulting, Tech Lead.
Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Security,
Spring Transaction, Spring MVC,
Log4j, REST/SOAP WEB-SERVICES.
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In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
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Experience our free, in-depth three-part Tendenci Platform Corporate Membership Management workshop series! In Session 1 on May 14th, 2024, we began with an Introduction and Setup, mastering the configuration of your Corporate Membership Module settings to establish membership types, applications, and more. Then, on May 16th, 2024, in Session 2, we focused on binding individual members to a Corporate Membership and Corporate Reps, teaching you how to add individual members and assign Corporate Representatives to manage dues, renewals, and associated members. Finally, on May 28th, 2024, in Session 3, we covered questions and concerns, addressing any queries or issues you may have.
For more Tendenci AMS events, check out www.tendenci.com/events
Listen to the keynote address and hear about the latest developments from Rachana Ananthakrishnan and Ian Foster who review the updates to the Globus Platform and Service, and the relevance of Globus to the scientific community as an automation platform to accelerate scientific discovery.
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About me
• Consultant and trainer in business intelligence, business analytics and data mining in
Méthode www.methode.it
• Since 2002, the main activities are related to the design of relational data warehouse and
multidimensional design with Microsoft tools.
• Teacher at the University of Pordenone in the course of data analysis and Big Data.
• Community Lead of 1nn0va (www.innovazionefvg.net)
• MCP, MCSA, MCSE, MCT and MVP Reconnect since 2014 for SQL Server.
• Speaker in several conferences on the topic info@marcopozzan.it
• @marcopozzan.it
• www.marcopozzan.it
• http://www.scoop.it/u/marco-pozzan
• http://paper.li/marcopozzan/1422524394
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Agenda
• Real time on Power BI
• Dataset type
• Pushing data method
• Best Practices
• Case Study
• Real-time dataset
• Gateway
• Power Apps
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Real Time on Power BI
• There is three type of real-time in Power BI
• Push
• Streaming
• PUbNub
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Push Type
• Power BI Service automatically creates a new DB;
• Dashboard tile refresh triggered whenever data is
pushed in;
• Enabled to create reports;
• Enabled to use all Power BI report features, such as
custom visuals, data alerts and pinned dashboard tiles;
• Pinning an entire report will not result in the data
automatically refreshed;
• Q&A to ask question when a visual is pinned to a
dashboard;
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Push Type
• Advantages:
• You can build reports, custom visuals, Q&A,etc..
• Limitations:
• Slower refresh times
• Max rate of data ingestion: 1 request/s and 16 MB/request
• Max rows per single push: (10k rows/hour Free, 1M
rows/hour Pro)
• if the dataset is not in a workspace assigned to Premium capacity, then
you will be limited to eight refreshes per day.
• When to use:
• > 3-5 second latency requirement
• Need to build report
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Streaming Type
• Data goes into Azure Redis cache (60 minutes)
• Power BI connects to Azure Redis cache when
a streaming visual is active on dashboard;
• Quick refresh rate (1s);
• Visual optimized for real-time scenarios;
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Streaming Type
• Advantages:
• Quick and dependable refresh rates (1s)
• Visuals optimized for real-time scenario(latest value, etc)
• Limitation:
• Limited set of visual:
• Cannot create report visual on top of the data
• Max rate of data ingestion: 5 request/s and 15 KB/request
• When to use:
• Need up-to-date data
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PubNub Type
• Data stream subscription:
• Quick refresh rate (1s);
• Visual optimized for real-time scenarios;
• SDK Platform:
• JavaScript
• .NET
• iOS
• Android
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PubNub Type
• Advantages:
• Quick and dependable refresh rates (1s)
• Visuals optimized for real time scenario (latest value, etc..)
• No limitation on max rate
• PubNub channels can be protected using a PubNub Access Manager (PAM) authentication
key. This key will be shared with all users who have access to the dashboard
• Limitation:
• Limited set of visual;
• Cannot create report visual on top of the data
• When to use:
• Need up-to-date data
• Your data is in PubNub
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Pushing data in with REST APIs
• Call API endpoint for push dataset
and/or streaming dataset;
• Two ways to create dataset (not with
Power BI Desktop):
• Programmatic creation
• UI Creation
• Programmatic creation:
• Flexible
• Use when want to complete control of how
the data is being pushed in
• Most secure
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Azure Stream Analytics
▪ Calls the Power BI REST APIs
• Creates the dataset and sends data to both push and streaming datasets
▪ Use when: data needs to be processed before being displayed
E.g. aggregating sensor data over time window
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Flow
▪ Calls the Power BI REST APIs
▪ Requires dataset to be created ahead of time
▪ Sends data to push/streaming/pushstreaming datasets
▪ Use when:
• Ease of set up
• Data comes from a data source that Flow connects to
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Best Practices: Reduce Data Volume
• Reduce data volume down to only what you need to display in Power BI
• For deeper analysis, send to a database, and connect Power BI to that via
import/live connection
• Be aware of data volume limits
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Case study
Objectives
• Create a dashboard available to customer services
and warehouse operators where they can highlight
in real time if the workload can be processed in
time or not.
Data sources
• repository that contain a delivery data
• repository that contain shifts work
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Case study: Data source Microsoft e non
Microsoft
Da Microsoft ignite
SAP HANA (In-Memory Data Platform)
Harness the power of your data and accelerate trusted
outcome-driven innovation by developing intelligent and
live solutions for real-time decisions and actions on a
single data copy. Support next-generation transactional
and analytical processing with a broad set of advanced
analytics – run securely across hybrid and multicloud
environments.
Bill McDermott, SAP CEO
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Case study (part 1): How to create a streaming
data set
• Go to Power BI Service
(http://powerbi.microsoft.com)
website. Log in to the website
with your Power BI Account.
When logged in create a new
streaming dataset;
• There are three ways to create
a streaming dataset. I have
explained the previously.
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Case study (part 1): How to save streaming
dataset’s data
• Than you specify the name of your
dataset, and add fileds to it. With adding
every new field you will see a JSON
format will be created underneath, which
is the format that the data needs to be
sent through REST API.
• If you want the history to be saved, you
have to switch this option to On.
• When you turn this option your dataset
from a streaming dataset, changes to be a
Hybrid dataset.
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Case study (part 1): Power BI API workflow
Create Application with REST API for pushing
data to Power BI
• Native Client
• Web application
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Case study (part 1): Power BI API workflow
Authenticate application in Azure Active Directory
using OAuth2:
• Create a new user account in Azure AD
• Add new application on Azure Management Portal
https://manage.windowsazure.com or
https://dev.powerbi.com/apps
• Grant application access to Power BI Service and set
permissions
• Get Client ID
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Case study (part 1): Power BI API workflow
REST API allows to interact and manage
almost all Power BI objects: Datasets,
Tables, Dashboards, ecc..
https://docs.microsoft.com/en-
us/rest/api/power-bi/
Library:
https://github.com/gbrueckl/PowerBI.A
PI.Client/tree/master/PowerBIClient
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Case study (part 2): gateway
• Centralized way to refresh on-premises
content in Power BI and other services
• Access control to data sources
• Monitor and track usage
• Live, interactive query with on-
premises data sources
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Che cosa è PowerApps?
A fully cloud-based platform for building, sharing and using business apps
• Get & manipulate external data via Connections
• Create apps with a Windows 10 App, share securely with Office 365 users
• Access via mobile devices, tablets, web browser and Windows apps
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Additional resources
• Real-time streaming documentation
• Tutorial: building real-time IoT dashboard with streaming datasets
• Documentation: connecting Azure Stream Analytics to Power BI
• Tutorial: adding PubNub stream from Power BI
• Real-time streaming GA announcement