VizEx Transform is a truly unique application enabling the transformation of multiple graphical data formats into CGM in one simple to use interface. The application also has the ability to add hotspot information to the CGM graphics during the transformation process. This is all done using a batch process saving time and money.
Infographic Debunking SharePoint Myths on Data Visualization and BIJoel Oleson
Myths and truths of Data visualization charting and business intelligence in the third party application space. People think it is expensive and complex to deploy solutions or you can't really build anything interesting for Office 365. This infographic addresses these myths and many more through Black compass as an example application that addresses these issues.
VizEx Transform is a truly unique application enabling the transformation of multiple graphical data formats into CGM in one simple to use interface. The application also has the ability to add hotspot information to the CGM graphics during the transformation process. This is all done using a batch process saving time and money.
Infographic Debunking SharePoint Myths on Data Visualization and BIJoel Oleson
Myths and truths of Data visualization charting and business intelligence in the third party application space. People think it is expensive and complex to deploy solutions or you can't really build anything interesting for Office 365. This infographic addresses these myths and many more through Black compass as an example application that addresses these issues.
Power BI Modeling Use Cases: Desktop to Enterprise with Questions and AnswersSenturus
Learn the different ways Power BI lets you source and prep data for analysis. We examine four different scenarios and their impacts on scalability, security and performance. Scenarios include: directly querying operational systems, querying the data warehouse, dataflows and datasets.
Senturus offers a full spectrum of services in business intelligence and training on Tableau, Power BI and Cognos. Our resource library has hundreds of free live and recorded webinars, blog posts, demos and unbiased product reviews available on our website at: http://www.senturus.com/senturus-resources/.
Microsoft’s Power BI is a business and data analytics service that enables professionals to process, analyze, and visualize vast volumes of data. It helps extract insights, draw conclusions, and share results in the form of reports and dashboards across various departments. It provides an easy drag and drops feature with a range of interactive data visualizations to generate reports and dashboards.
Microsoft Data Science Technologies: Back Office EditionMark Tabladillo
Microsoft provides several technologies in and around SQL Server which can be used for casual to serious data science. This presentation provides an authoritative overview of five major options: SQL Server Analysis Services, Excel Add-in for SSAS, Semantic Search, Microsoft Azure Machine Learning, and F#. Also included are tips on working with Python and R. These technologies have been used by the presenter in various companies and industries. This presentation will emphasize the back office story for supporting big data processing.
Power BI dataflows と Power Platform Data Integration の使いどころYugo Shimizu
Microsoft Ignite The Tour Tokyo と Osaka でお話した同タイトルのセッション資料です
BRK30034 @ Tokyo 2019/12/06 15:15 - 16:00 JST
BRK30156 @ Osaka 2020/01/24 12:15 - 13:00 JST
セッション概要:
Power BI dataflows と Power Platform dataflows は両方とも Power Query でデータを集め、使いたい形に変えることが可能ですが、その用途は使い分けるべきです。(=Data Preparation, ETL)
似たような機能がなぜそれぞれに存在するのか?それは目的が異なるからです。本セッションでは、シナリオベースでそれぞれの使い方をご紹介します。
What is the Power BI and learn the Power BI by self and this presentation contains some use full links which help us at time of developing the Power BI.
Big Data, IoT, data lake, unstructured data, Hadoop, cloud, and massively parallel processing (MPP) are all just fancy words unless you can find uses cases for all this technology. Join me as I talk about the many use cases I have seen, from streaming data to advanced analytics, broken down by industry. I’ll show you how all this technology fits together by discussing various architectures and the most common approaches to solving data problems and hopefully set off light bulbs in your head on how big data can help your organization make better business decisions.
Your Roadmap for An Enterprise Graph StrategyNeo4j
Speaker: Michael Moore, Ph.D., Executive Director, Knowledge Graphs + AI, EY National Advisory
Abstract: Knowledge graphs have enormous potential for delivering superior customer experiences, advanced analytics and efficient data management.
Learn valuable tips from a leading practitioner on how to position, organize and implement your first enterprise graph project.
Architectural Options for Using IBM Cognos with SAP, including Alternatives t...Senturus
Architectural challenges of reporting from SAP. View the webinar video recording and download this deck: http://www.senturus.com/resources/architectural-options-for-using-ibm-cognos-with-sap/.
We present options for connecting SAP to Cognos, along with pros and cons for each. This includes several lesser known approaches that have been highly successful with our clients – methods that can be implemented today without the high cost and risk associated with SAP’s standard answer to the problem, HANA.
Senturus, a business analytics consulting firm, has a resource library with hundreds of free recorded webinars, trainings, demos and unbiased product reviews. Take a look and share them with your colleagues and friends: http://www.senturus.com/resources/.
The presentation discusses the different aspects of Power BI like Power BI for O365, Data Discovery, Data Analysis, Data Visualization & Power Maps, Natural Language Search etc.
Its a business analytics solution presented by Netwoven at the Microsoft Power BI workshop held on Oct 30th at SVC Microsoft, Mountain View.
Microsoft Data Science Technologies: Architecture Edition 201509Mark Tabladillo
Microsoft provides several technologies in and around SQL Server which can be used for casual to serious data science. This presentation provides an authoritative overview of five major options: SQL Server Analysis Services, Excel Add-in for SSAS, Semantic Search, Microsoft Azure Machine Learning, and F#. Also included are tips on working with Python and R. These technologies have been used by the presenter in various companies and industries.
Power BI & SAP - Integration Options and possible PifallsJJDE
Dein Unternehmen setzt als ERP/BI-System auf SAP? Und du suchst nach den besten Möglichkeiten, um alle SAP BW / HANA-Daten in Microsoft Power BI zu integrieren und das Beste aus beiden Welten zu nutzen? Dann ist diese Session für dich! Du erhältst einen Überblick über die verschiedenen Integrationsoptionen und -Überlegungen, die du berücksichtigen solltest.
English Version:
Your Company's ERP and/or BI-System is SAP? And you are looking for the best options to get all your SAP BW/HANA Data to Microsoft (Power) BI and leverage the best of both worlds? Then this session is for you! You will get an overview of the several integration options and considerations you should be aware. The session will be hold in german language but of course we can switch to English as needed.
Slides used during 2016 edition of SharePoint Saturday Toronto to present Microsoft PowerApps and how easy it is to create application from Azure SQL, Microsoft CRM and SharePoint Content.
Best Practices for Building and Deploying Data Pipelines in Apache SparkDatabricks
Many data pipelines share common characteristics and are often built in similar but bespoke ways, even within a single organisation. In this talk, we will outline the key considerations which need to be applied when building data pipelines, such as performance, idempotency, reproducibility, and tackling the small file problem. We’ll work towards describing a common Data Engineering toolkit which separates these concerns from business logic code, allowing non-Data-Engineers (e.g. Business Analysts and Data Scientists) to define data pipelines without worrying about the nitty-gritty production considerations.
We’ll then introduce an implementation of such a toolkit in the form of Waimak, our open-source library for Apache Spark (https://github.com/CoxAutomotiveDataSolutions/waimak), which has massively shortened our route from prototype to production. Finally, we’ll define new approaches and best practices about what we believe is the most overlooked aspect of Data Engineering: deploying data pipelines.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Power BI Modeling Use Cases: Desktop to Enterprise with Questions and AnswersSenturus
Learn the different ways Power BI lets you source and prep data for analysis. We examine four different scenarios and their impacts on scalability, security and performance. Scenarios include: directly querying operational systems, querying the data warehouse, dataflows and datasets.
Senturus offers a full spectrum of services in business intelligence and training on Tableau, Power BI and Cognos. Our resource library has hundreds of free live and recorded webinars, blog posts, demos and unbiased product reviews available on our website at: http://www.senturus.com/senturus-resources/.
Microsoft’s Power BI is a business and data analytics service that enables professionals to process, analyze, and visualize vast volumes of data. It helps extract insights, draw conclusions, and share results in the form of reports and dashboards across various departments. It provides an easy drag and drops feature with a range of interactive data visualizations to generate reports and dashboards.
Microsoft Data Science Technologies: Back Office EditionMark Tabladillo
Microsoft provides several technologies in and around SQL Server which can be used for casual to serious data science. This presentation provides an authoritative overview of five major options: SQL Server Analysis Services, Excel Add-in for SSAS, Semantic Search, Microsoft Azure Machine Learning, and F#. Also included are tips on working with Python and R. These technologies have been used by the presenter in various companies and industries. This presentation will emphasize the back office story for supporting big data processing.
Power BI dataflows と Power Platform Data Integration の使いどころYugo Shimizu
Microsoft Ignite The Tour Tokyo と Osaka でお話した同タイトルのセッション資料です
BRK30034 @ Tokyo 2019/12/06 15:15 - 16:00 JST
BRK30156 @ Osaka 2020/01/24 12:15 - 13:00 JST
セッション概要:
Power BI dataflows と Power Platform dataflows は両方とも Power Query でデータを集め、使いたい形に変えることが可能ですが、その用途は使い分けるべきです。(=Data Preparation, ETL)
似たような機能がなぜそれぞれに存在するのか?それは目的が異なるからです。本セッションでは、シナリオベースでそれぞれの使い方をご紹介します。
What is the Power BI and learn the Power BI by self and this presentation contains some use full links which help us at time of developing the Power BI.
Big Data, IoT, data lake, unstructured data, Hadoop, cloud, and massively parallel processing (MPP) are all just fancy words unless you can find uses cases for all this technology. Join me as I talk about the many use cases I have seen, from streaming data to advanced analytics, broken down by industry. I’ll show you how all this technology fits together by discussing various architectures and the most common approaches to solving data problems and hopefully set off light bulbs in your head on how big data can help your organization make better business decisions.
Your Roadmap for An Enterprise Graph StrategyNeo4j
Speaker: Michael Moore, Ph.D., Executive Director, Knowledge Graphs + AI, EY National Advisory
Abstract: Knowledge graphs have enormous potential for delivering superior customer experiences, advanced analytics and efficient data management.
Learn valuable tips from a leading practitioner on how to position, organize and implement your first enterprise graph project.
Architectural Options for Using IBM Cognos with SAP, including Alternatives t...Senturus
Architectural challenges of reporting from SAP. View the webinar video recording and download this deck: http://www.senturus.com/resources/architectural-options-for-using-ibm-cognos-with-sap/.
We present options for connecting SAP to Cognos, along with pros and cons for each. This includes several lesser known approaches that have been highly successful with our clients – methods that can be implemented today without the high cost and risk associated with SAP’s standard answer to the problem, HANA.
Senturus, a business analytics consulting firm, has a resource library with hundreds of free recorded webinars, trainings, demos and unbiased product reviews. Take a look and share them with your colleagues and friends: http://www.senturus.com/resources/.
The presentation discusses the different aspects of Power BI like Power BI for O365, Data Discovery, Data Analysis, Data Visualization & Power Maps, Natural Language Search etc.
Its a business analytics solution presented by Netwoven at the Microsoft Power BI workshop held on Oct 30th at SVC Microsoft, Mountain View.
Microsoft Data Science Technologies: Architecture Edition 201509Mark Tabladillo
Microsoft provides several technologies in and around SQL Server which can be used for casual to serious data science. This presentation provides an authoritative overview of five major options: SQL Server Analysis Services, Excel Add-in for SSAS, Semantic Search, Microsoft Azure Machine Learning, and F#. Also included are tips on working with Python and R. These technologies have been used by the presenter in various companies and industries.
Power BI & SAP - Integration Options and possible PifallsJJDE
Dein Unternehmen setzt als ERP/BI-System auf SAP? Und du suchst nach den besten Möglichkeiten, um alle SAP BW / HANA-Daten in Microsoft Power BI zu integrieren und das Beste aus beiden Welten zu nutzen? Dann ist diese Session für dich! Du erhältst einen Überblick über die verschiedenen Integrationsoptionen und -Überlegungen, die du berücksichtigen solltest.
English Version:
Your Company's ERP and/or BI-System is SAP? And you are looking for the best options to get all your SAP BW/HANA Data to Microsoft (Power) BI and leverage the best of both worlds? Then this session is for you! You will get an overview of the several integration options and considerations you should be aware. The session will be hold in german language but of course we can switch to English as needed.
Slides used during 2016 edition of SharePoint Saturday Toronto to present Microsoft PowerApps and how easy it is to create application from Azure SQL, Microsoft CRM and SharePoint Content.
Best Practices for Building and Deploying Data Pipelines in Apache SparkDatabricks
Many data pipelines share common characteristics and are often built in similar but bespoke ways, even within a single organisation. In this talk, we will outline the key considerations which need to be applied when building data pipelines, such as performance, idempotency, reproducibility, and tackling the small file problem. We’ll work towards describing a common Data Engineering toolkit which separates these concerns from business logic code, allowing non-Data-Engineers (e.g. Business Analysts and Data Scientists) to define data pipelines without worrying about the nitty-gritty production considerations.
We’ll then introduce an implementation of such a toolkit in the form of Waimak, our open-source library for Apache Spark (https://github.com/CoxAutomotiveDataSolutions/waimak), which has massively shortened our route from prototype to production. Finally, we’ll define new approaches and best practices about what we believe is the most overlooked aspect of Data Engineering: deploying data pipelines.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
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
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.
45. Firewall
Azure Service Bus
Power BI Enterprise Gateway communicates on
outbound ports: TCP 443 (default), 5671, 5672,
9350 thru 9354. The Connector does not require
inbound ports.
Reference: https://powerbi.microsoft.com/en-us/documentation/
powerbi-gateway-enterprise-indepth/#ports
Dashboards
Reports
Datasets
Cloud, Office 365
Data
Model
Data
Warehouse
SQL database (generic)
Storage (Azure)
Hadoop
46.
47.
48. Data
Warehouse
SQL database (generic)
Storage (Azure)
Hadoop
Data
Model
Excel
PBI Gateway
Cloud, Office 365
http://www.designmind.com/business-intelligence/analysis-services-tabular/
49. Process DB
Process DimDate Process DimProduct
Process
DimEmployee
Process
DimSalesTerritory
Process Internet
Sales
Process Inventory
Process Sales Quota
52. Process Add
Inventory
Change Inventory
Partition Query
Change Inventory
Partition Query
Incremental
Load?
Process DB
NO
Snapshot
Updated?
YES
NO
Processing Starts
Dim
Dim
Dim
Fact
Fact
YES
Process Ends
Editor's Notes
What drives reports in Power BI?
Answer: The Data Model
Through the interaction of the data model and the report, we are analyzing our data. As we analyze, more business questions surface. As we answer our own questions, we realize that others have questions we don’t even know about. We don’t know what we don’t know. So those questions come into light, we make the necessary adjustments in the data model, and then voila, we have new answers to new questions we didn’t even know we could answer.
Demo the Finished Solar demo. Do a simple chart
Navigation: Add new dashboards, rename and remove
Menu: Where you can duplicate, print, and refresh dashboards
Tiles:
Visual Tiles
Report Live Tiles
Edit Menu (Edit View):
Print Report
Save/Save As
Visual Interactions
Shapes
Same data model lives and breathes in the Service, but is not editable.
Publish the Solar demo to our Solar workspace via One Drive and discuss why its important.
Looks for better Disconnected Table example
Modeling tab has some important uses:
Create a new Data table
Set Data types
Set Format for report display (MM/DD/YYYY)
Set Home Table for measures (where they live)
Data Categorization (such as Lat/Lon, Zip, Address)
Default Summarization: Do Not Summarize
Relationships are visualized here. Suggested layout is to have lookups above the data tables so you can confirm that fields from lookups will span across multiple data tables.
There is a new
Prepare the Output table for PVOutput before hand and add the System table.
Add Date Table via M query
Open the same prior model and add Generation, PY Generation, and YoY %
Add some talking point in the notes
RELATED function example
Filters instead of Slicers
Drill-down to fields in X-Axis (no hierarcy needed)
Reference Lines
Analyze Power BI Model in Excel
Export data
Pin Tiles using different Filter sets
Advantages:
Quick analytics into your data
Quick to visualize
Can perform transformations to data
Can data from SaaS
Learn it by learning import methodology. Then go the DirectQuery method.
Open up Adventure Works VS project that has two Fact tables and a few dimensions ready to go
Show how to create calculated and measures.
Show where to Categorize and Summarize fields.
Show Perspectives
Show Processing
Show Row-level security
Setup VS on DMSQL2014
Deploy AdventureWorks sample beforehand
Publish AdventureWorks report