This document advertises CData Power BI connectors which allow users to connect Power BI to over 110 live data sources using DirectQuery. The connectors treat APIs like databases by wrapping SQL queries around them and mapping API resources and objects to tables and views. This provides a uniform SQL experience across different data sources and allows for features like nested JSON values in columns, stored procedures, and relating sub-collections as tables. A demonstration connects to MongoDB and QuickBooks Desktop as examples.
Master the Multi-Clustered Data Warehouse - SnowflakeMatillion
Snowflake is one of the most powerful, efficient data warehouses on the market today—and we joined forces with the Snowflake team to show you how it works!
In this webinar:
- Learn how to optimize Snowflake
- Hear insider tips and tricks on how to improve performance
- Get expert insights from Craig Collier, Technical Architect from Snowflake, and Kalyan Arangam, Solution Architect from Matillion
- Find out how leading brands like Converse, Duo Security, and Pets at Home use Snowflake and Matillion ETL to make data-driven decisions
- Discover how Matillion ETL and Snowflake work together to modernize your data world
- Learn how to utilize the impressive scalability of Snowflake and Matillion
Affordable Business Intelligence (BI) ToolAnswergen
Answergen BI provides a business intelligence tool that can easy to use. Answergen analytics are obtainable in many different types-dashboard, mapping, grid, mobile bi, security, combined report and more. That makes it simple to assess, observe and understand of any big data related to your business.
Master the Multi-Clustered Data Warehouse - SnowflakeMatillion
Snowflake is one of the most powerful, efficient data warehouses on the market today—and we joined forces with the Snowflake team to show you how it works!
In this webinar:
- Learn how to optimize Snowflake
- Hear insider tips and tricks on how to improve performance
- Get expert insights from Craig Collier, Technical Architect from Snowflake, and Kalyan Arangam, Solution Architect from Matillion
- Find out how leading brands like Converse, Duo Security, and Pets at Home use Snowflake and Matillion ETL to make data-driven decisions
- Discover how Matillion ETL and Snowflake work together to modernize your data world
- Learn how to utilize the impressive scalability of Snowflake and Matillion
Affordable Business Intelligence (BI) ToolAnswergen
Answergen BI provides a business intelligence tool that can easy to use. Answergen analytics are obtainable in many different types-dashboard, mapping, grid, mobile bi, security, combined report and more. That makes it simple to assess, observe and understand of any big data related to your business.
Providing Interactive Analytics on Excel with Billions of RowsTyler Wishnoff
See how to get lightning-fast query performance on Microsoft Excel that scales into the petabytes. This presentation shares the top challenges Excel faces with big data and outlines strategies to keep Excel running smoothly. Learn more at: https://kyligence.io/solution/big-data-analytics-in-excel/
Solution architecture for big data projects
solution architecture,big data,hadoop,hive,hbase,impala,spark,apache,cassandra,SAP HANA,Cognos big insights
Power BI Dashboard | Microsoft Power BI Tutorial | Data Visualization | EdurekaEdureka!
This Edureka Power BI Dashboard Tutorial will take you through step by step creation of Power BI dashboard. It helps you learn different functionalities present in Power BI tool with a demo on superstore dataset. You will learn how to create a Power BI dashboard by taking out multiple insights from superstore dataset and representing them visually.
Why HR Should Consider Agile Modern Data Delivery Platformsyed_javed
Modern data delivery platform like Lyftron provides universal data model capability to HR departments that enables changes from the source dynamically in the semantic layer and allows enterprises to avoid manual semantic data model changes.
Architecting Data Lake on AWS by the Data Engineering Team at HiFX ITMohan Thomas
This is the presentation we shared at the AWS Summit 2017 in Bangalore. We are showcasing our high performance framework with the various components which enables an organization to be data driven. Find out how our components are engineered to scale, store data securely and process the data for insights.
Hassle-Free Data Lake Governance: Automating Your Analytics with a Semantic L...Tyler Wishnoff
Simplify data lake governance, no matter how much data you work with and how many data sources and BI tools you manage. This presentation offers all you need to develop your own strategy for smarter data lake governance. Learn more at: https://kyligence.io/
The solution for building the Data Warehouse on AWS with the scalable-data across AWS regions.
The benefits of this solution: it enables users to access, analyze and visualize any data to get the insight faster in order to make better decisions for the business.
The solution is secure, scalable, comprehensive, and cost-effective.
Introduction to Power BI a Business Intelligence Tool by Apurva RamtekeApurva Ramteke
Power BI is a tool which provides users with very intelligent statistical analysis of raw data and to derive beautiful reports out of it using hundreds of power Visualization. Not just it Power BI provides a build in advantage of Power Views and Power Queries derived from Excel as a base with a very easy process learning. I personally call it very Intelligently dumb tool, because its so easy for normal user to use it and make highly interactive reporting and Dashboards. The Dashboard which are created can be shared with multiple users with specific permission levels to access the reports.
Learn more about PowePivot, Microsoft's new in-memory engine, and how you can extend it with advanced analytics and a data security layer for enterprise wide deployment.
Get technically equipped to grow and build your Power BI (Business Intelligence) practice, enabling you to offer new solutions and services to customers. With Power BI, you can transform your customers' data into rich visuals they can collect and organize, helping them focus on what matters most to their businesses.
Leveraging Microsoft Power BI To Support Enterprise Business IntelligenceRightpoint
Take control over your data. View our presentation of end-to-end enterprise business intelligence leveraging Microsoft solutions including SQL Server, Power Pivot, and Power BI.
Demonstration includes:
• How to build a Tabular model by importing a Power Pivot workbook
• Connecting a Tabular model to Power BI
• Developing Power BI dashboards/reports connected to an on-premise Tabular model
• Refreshing Power BI dashboards/reports
R Visualizations in Power BI | Power BI Training | EdurekaEdureka!
YouTube: https://youtu.be/Klvybl642ug
** Power BI Training: https://www.edureka.co/power-bi-training **
This Edureka Live about "The Power of R in Power BI", discusses the Integration of R in Power BI. The main aim here is to understand how to Leverage R to expand the utility of Power BI. The agenda of the session is as follows:
Why R in Power BI?
How the R Integration Works?
Demo
- R script visuals
- R as a Data Source
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Preview presentation for the RDU Power BI User Group of the upcoming CData Power BI Connectors (Custom connectors for more than 110+ SaaS, Big Data, & NoSQL sources).
Providing Interactive Analytics on Excel with Billions of RowsTyler Wishnoff
See how to get lightning-fast query performance on Microsoft Excel that scales into the petabytes. This presentation shares the top challenges Excel faces with big data and outlines strategies to keep Excel running smoothly. Learn more at: https://kyligence.io/solution/big-data-analytics-in-excel/
Solution architecture for big data projects
solution architecture,big data,hadoop,hive,hbase,impala,spark,apache,cassandra,SAP HANA,Cognos big insights
Power BI Dashboard | Microsoft Power BI Tutorial | Data Visualization | EdurekaEdureka!
This Edureka Power BI Dashboard Tutorial will take you through step by step creation of Power BI dashboard. It helps you learn different functionalities present in Power BI tool with a demo on superstore dataset. You will learn how to create a Power BI dashboard by taking out multiple insights from superstore dataset and representing them visually.
Why HR Should Consider Agile Modern Data Delivery Platformsyed_javed
Modern data delivery platform like Lyftron provides universal data model capability to HR departments that enables changes from the source dynamically in the semantic layer and allows enterprises to avoid manual semantic data model changes.
Architecting Data Lake on AWS by the Data Engineering Team at HiFX ITMohan Thomas
This is the presentation we shared at the AWS Summit 2017 in Bangalore. We are showcasing our high performance framework with the various components which enables an organization to be data driven. Find out how our components are engineered to scale, store data securely and process the data for insights.
Hassle-Free Data Lake Governance: Automating Your Analytics with a Semantic L...Tyler Wishnoff
Simplify data lake governance, no matter how much data you work with and how many data sources and BI tools you manage. This presentation offers all you need to develop your own strategy for smarter data lake governance. Learn more at: https://kyligence.io/
The solution for building the Data Warehouse on AWS with the scalable-data across AWS regions.
The benefits of this solution: it enables users to access, analyze and visualize any data to get the insight faster in order to make better decisions for the business.
The solution is secure, scalable, comprehensive, and cost-effective.
Introduction to Power BI a Business Intelligence Tool by Apurva RamtekeApurva Ramteke
Power BI is a tool which provides users with very intelligent statistical analysis of raw data and to derive beautiful reports out of it using hundreds of power Visualization. Not just it Power BI provides a build in advantage of Power Views and Power Queries derived from Excel as a base with a very easy process learning. I personally call it very Intelligently dumb tool, because its so easy for normal user to use it and make highly interactive reporting and Dashboards. The Dashboard which are created can be shared with multiple users with specific permission levels to access the reports.
Learn more about PowePivot, Microsoft's new in-memory engine, and how you can extend it with advanced analytics and a data security layer for enterprise wide deployment.
Get technically equipped to grow and build your Power BI (Business Intelligence) practice, enabling you to offer new solutions and services to customers. With Power BI, you can transform your customers' data into rich visuals they can collect and organize, helping them focus on what matters most to their businesses.
Leveraging Microsoft Power BI To Support Enterprise Business IntelligenceRightpoint
Take control over your data. View our presentation of end-to-end enterprise business intelligence leveraging Microsoft solutions including SQL Server, Power Pivot, and Power BI.
Demonstration includes:
• How to build a Tabular model by importing a Power Pivot workbook
• Connecting a Tabular model to Power BI
• Developing Power BI dashboards/reports connected to an on-premise Tabular model
• Refreshing Power BI dashboards/reports
R Visualizations in Power BI | Power BI Training | EdurekaEdureka!
YouTube: https://youtu.be/Klvybl642ug
** Power BI Training: https://www.edureka.co/power-bi-training **
This Edureka Live about "The Power of R in Power BI", discusses the Integration of R in Power BI. The main aim here is to understand how to Leverage R to expand the utility of Power BI. The agenda of the session is as follows:
Why R in Power BI?
How the R Integration Works?
Demo
- R script visuals
- R as a Data Source
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Preview presentation for the RDU Power BI User Group of the upcoming CData Power BI Connectors (Custom connectors for more than 110+ SaaS, Big Data, & NoSQL sources).
SendGrid Improves Email Delivery with Hybrid Data WarehousingAmazon Web Services
When you received your Uber ‘Tuesday Evening Ride Receipt’ or Spotify’s ‘This Week’s New Music’ email, did you think about how they got there?
SendGrid’s reliable email platform delivers each month over 20 Billion transactional and marketing emails on behalf of many of your favorite brands, including Uber, Airbnb, Spotify, Foursquare and NextDoor.
SendGrid was looking to evolve its data warehouse architecture in order to improve decision making and optimize customer experience. They needed a scalable and reliable architecture that would allow them to move nimbly and efficiently with a relatively small IT organization, while supporting the needs of both business and technical users at SendGrid.
SendGrid’s Director of Enterprise Data Operations will be joining architects from Amazon Web Services (AWS) and Informatica to discuss SendGrid’s journey to a hybrid cloud architecture and how a hybrid data warehousing solution is optimized to support SendGrid’s analytics initiative. Speakers will also review common technologies and use cases being deployed in hybrid cloud today, common data management challenges in hybrid cloud and best practices for addressing these challenges.
Join us to learn:
• How to evolve to a hybrid data warehouse with Amazon Redshift for scalability, agility and cost efficiency with minimal IT resources
• Hybrid cloud data management use cases
• Best practices for addressing hybrid cloud data management challenges
Abstract: Data preparation and modelling are the activities that take most of the time in a typical data scientist workday. In this session we’ll see how AWS services for Analytics and data management can be effectively used and integrated in AI/ML pipelines. We’ll focus on AWS Glue, AWS Glue DataBrew and AWS Data Wrangler with a bit of theory and hands-on demos.
Bio:
Francesco Marelli is a senior solutions architect at Amazon Web Services. He has lived and worked in UK, italy, Switzerland and other countries in EMEA. He is specialized in the design and implementation of Analytics, Data Management and Big Data systems. Francesco also has a strong experience in systems integration and design and implementation of applications.
Topics: machine learning pipelines, AWS, cloud.
Why Standards-Based Drivers Offer Better API IntegrationNordic APIs
As enterprises grow, so too does the number and variety of data sources they use to drive business. The average company is using at least sixteen SaaS applications and has data in at least that many on-premises data stores and internal apps.
With such disparate data, each tied to a unique API, integrating, managing, and maintaining integrations for all of a company’s data creates a whole new set of challenges. Thankfully, solutions exist that enable enterprises to rely on data to drive business without causing undue strain. In this session, we’ll explore and compare the different options for solving the data integration problem and explain why you should be using standards-based drivers to abstract your API integrations.
Enterprise Cloud Data Platforms - with Microsoft AzureKhalid Salama
These slides gives an overview on MS Azure Data Architecture and Services, including Data Lake Analytics, Data Factory, Azure SQL DW, Stream Analytics, Azure Machine learning tools, and Data Catalog. This is also known as Cortana Analytical Suite
Product lead data approach to modern data ecosystems. It outlines some key questions to consider such as what business problems need to be solved, what data is needed and where it will come from, and what needs to be done to the data to make it usable.
It then provides examples of potential data sources, such as operational systems, streamed events, legacy data warehouses, IoT, database replication, APIs, and external or manual input. Some examples of potential data products are listed as performance KPIs, analysis, visualization, publication, AI/ML, automation, and optimization.
Data data processing may involve applying business rules and logic, cleaning and conforming the data, storing it in a data lake, data warehouse or data marts. It also mentions organizing the data into business domains.
Finally, it lists some important aspects that need to be supported to enable a product lead data approach, such as people & skills, operating model, data governance, technology & architecture, and planning & roadmap. This includes considerations around capabilities, recruitment, infrastructure, documentation, data security, understandability and management.
Why Standards-Based Drivers Offer Better API IntegrationJerod Johnson
A brief overview of API integration solutions (direct, SDK, middleware, drivers) and an argument in favor of using drivers to solve your integration needs.
AWS Data Pipeline Tutorial | AWS Tutorial For Beginners | AWS Certification T...Edureka!
( ** AWS Architect Traininhg: https://www.edureka.co/cloudcomputing ** )
This “AWS Data Pipeline Tutorial” by Edureka will help you understand how to process, store & analyze data with ease from the same location using AWS Data Pipeline.
Below is the list of topics covered in this session:
1. Need for Data Pipeline
2. What is AWS Data Pipeline?
3. AWS Data Pipeline Components
4. Demo on AWS Data Pipeline
Check out our complete AWS Playlist here: https://goo.gl/8qrfKU
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
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BI in the Cloud - Microsoft Power BI Overview and DemoChristopher Foot
RDX Insights Series Presentation focusing on Microsoft Power BI in the cloud. We begin with a high-level overview of the Microsoft BI product suite and discuss the SSIS/SSAS/SSRS tech stack and Power BI. The webinar continues with a deep dive into Power BI and includes instructions on how to use the product to capture, model, analyze and visualize business data. We end the webinar with a Power BI demo highlighting some of its most beneficial and interesting features.
We live in a world of unprecedented change. To be successful in this world of change, you will need to develop a data culture, creating an environment where every team and every individual is empowered to do great things because of the data at their fingertips. In this event you will learn how to create a culture of data and how the Microsoft Modern BI platform and tools can help you to can harness the power of data once only reserved for data scientists. Learn about how to tap into the power of natural language, self-service business insights and visualization capabilities – and make insights available to anyone, anywhere, at any time.
Improve Time to Market with Real-Time Analytics on Time-Series DataVin Dahake
Maximizes the data that power financial services with
fast cloud performance
Powers fundamental operations like investment
strategies, risk assessments, and fraud detections
Highly secure, scalable, reliable, and performing
infrastructure to handle data-intensive workloads
In this session you will learn how Qlik’s Data Integration platform (formerly Attunity) reduces time to market and time to insights for modern data architectures through real-time automated pipelines for data warehouse and data lake initiatives. Hear how pipeline automation has impacted large financial services organizations ability to rapidly deliver value and see how to build an automated near real-time pipeline to efficiently load and transform data into a Snowflake data warehouse on AWS in under 10 minutes.
Power BI for Big Data and the New Look of Big Data SolutionsJames Serra
New features in Power BI give it enterprise tools, but that does not mean it automatically creates an enterprise solution. In this talk we will cover these new features (composite models, aggregations tables, dataflow) as well as Azure Data Lake Store Gen2, and describe the use cases and products of an individual, departmental, and enterprise big data solution. We will also talk about why a data warehouse and cubes still should be part of an enterprise solution, and how a data lake should be organized.
Enabling transparent SQL/SPARQL access to both static and dynamically-computed data
Query languages for databases (e.g., SQL) and knowledge graphs (e.g., SPARQL) provide a concise, declarative, and highly flexible mechanism to access stored data. Yet, many use cases also involve dynamically-computed data available through web APIs or other forms of external services. In such settings, data access is comparatively less flexible (e.g., due to restrictions on available input/output methods), convenient, and sometimes prohibitively slow for users interactively querying data. In this talk, we discuss these problems and present open source solutions that enable querying dynamically-computed data as a “virtual” (since not fully materialized) relational database via SQL, or as a “virtual” knowledge graph via SPARQL, at the same time providing pre-computation and caching solutions to speed up data access. The core components presented in the talk have been developed in the context of the HIVE “Fusion Grant” project and the OntoCRM project, both involving UNIBZ and Ontopic srl. In both projects, we aim at extending virtual knowledge graphs to dynamically-computed data, with a particular focus on applications in the domains of environmental sustainability and climate risk management.
Similar to CData Power BI Connectors - MS Business Application Summit (20)
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
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
TROUBLESHOOTING 9 TYPES OF OUTOFMEMORYERRORTier1 app
Even though at surface level ‘java.lang.OutOfMemoryError’ appears as one single error; underlyingly there are 9 types of OutOfMemoryError. Each type of OutOfMemoryError has different causes, diagnosis approaches and solutions. This session equips you with the knowledge, tools, and techniques needed to troubleshoot and conquer OutOfMemoryError in all its forms, ensuring smoother, more efficient Java applications.
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/
Top Features to Include in Your Winzo Clone App for Business Growth (4).pptxrickgrimesss22
Discover the essential features to incorporate in your Winzo clone app to boost business growth, enhance user engagement, and drive revenue. Learn how to create a compelling gaming experience that stands out in the competitive market.
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.
May Marketo Masterclass, London MUG May 22 2024.pdfAdele Miller
Can't make Adobe Summit in Vegas? No sweat because the EMEA Marketo Engage Champions are coming to London to share their Summit sessions, insights and more!
This is a MUG with a twist you don't want to miss.
Large Language Models and the End of ProgrammingMatt Welsh
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
How Recreation Management Software Can Streamline Your Operations.pptxwottaspaceseo
Recreation management software streamlines operations by automating key tasks such as scheduling, registration, and payment processing, reducing manual workload and errors. It provides centralized management of facilities, classes, and events, ensuring efficient resource allocation and facility usage. The software offers user-friendly online portals for easy access to bookings and program information, enhancing customer experience. Real-time reporting and data analytics deliver insights into attendance and preferences, aiding in strategic decision-making. Additionally, effective communication tools keep participants and staff informed with timely updates. Overall, recreation management software enhances efficiency, improves service delivery, and boosts customer satisfaction.
top nidhi software solution freedownloadvrstrong314
This presentation emphasizes the importance of data security and legal compliance for Nidhi companies in India. It highlights how online Nidhi software solutions, like Vector Nidhi Software, offer advanced features tailored to these needs. Key aspects include encryption, access controls, and audit trails to ensure data security. The software complies with regulatory guidelines from the MCA and RBI and adheres to Nidhi Rules, 2014. With customizable, user-friendly interfaces and real-time features, these Nidhi software solutions enhance efficiency, support growth, and provide exceptional member services. The presentation concludes with contact information for further inquiries.
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?
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.
Enhancing Project Management Efficiency_ Leveraging AI Tools like ChatGPT.pdfJay Das
With the advent of artificial intelligence or AI tools, project management processes are undergoing a transformative shift. By using tools like ChatGPT, and Bard organizations can empower their leaders and managers to plan, execute, and monitor projects more effectively.
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
This is CData Software Power BI Connectors – If you’re looking for latest (and fastest) way to connect to live data from more than 100 different sources, then you’re in the right spot!
CData Software is a leading provider of Data Connectivity solutions (we’ll dig into what that means in a bit), with roots in data connectivity going back to 1994.
My name is Jerod Johnson. I’m a technology evangelist with CData and I’ve been with the company for around 5 years.
In this session, I’ll give a general overview of the CData technology, introduce the CData Power BI Connectors, and discuss how they relate to connecting via ODBC.
Then we’ll spend the bulk of our time together in a demo of connecting to live data from Power BI using the CData connectors, starting with configuring a connection and ending with simple visualizations in Power BI.
Let’s start with the wow factor. CData Software offers connectors that enable live connectivity to over 110 different SaaS, Big Data, and NoSQL sources through a familiar SQL interface. Sources range from the enterprise and widely used like Salesforce and various MS Dynamics platforms to the niche sources like generic REST APIs or XML data. On this slide you can see almost all of our sources.
So what is it that CData software does? We make APIs look like databases. Data analysts and business app users are generally familiar with tabular presentation of data, if not with SQL itself. What our connectors do is provide a SQL interface to your data, no matter where it is. For our Power BI connectors, this means that whenever Power BI submits a SQL query to a data source, the connectors translate that query into the appropriate API or protocol-level request for the source. When the source responds, the connectors then translate the response into a table, with rows and columns.
How does CData make APIs look like databases?
We starts with a database metaphor for API data. Each table represents a set of entities or objects. Each row represents an individual entity of the given table, and individual columns represent attributes within that entity. So imagine a table of Dynamics CRM Leads, where each row is a lead and there are columns for attributes like name, email address, priority and all of the other Lead information the Dynamics CRM API exposes.
For the most part, the connectors are wrapped around REST/SOAP APIs, so SQL commands correspond with HTTP verbs. SELECT with GET; INSERT and UPDATE with POST,PUT, and PATCH, and (shock of shocks) DELETE with DELETE.
For those API operations that aren’t easily tabularized, the CData drivers make judicious use of Stored Procedures. This might mean uploading a file to Sharepoint, or manually working through an OAuth flow.
For data sources with nested values (like JSON or XML) the connector will return the full aggregate of the value. The connectors do support JSON and XML parsing functions in the SQL query to drill down into the nested data as needed.
For all supported data sources, the connectors leverage collaborative query processing. This means that whenever possible, complex querying is pushed down to the server, minimizing the need for client-side processing. A built-in SQL engine manages whatever functionality isn’t supported at the source and processes data on the client side. For example, a source might support filtering, but not JOINs. In this case, the filter is passed into the HTTP/protocol request and the JOIN is performed in-memory on the client side.
So what are the CData Power BI Connectors?
These are native Power BI connectors that utilize the custom connector functionality of Power BI.
The setup is practically identical to ODBC (meaning you configure the connection via a DSN).
Since the connectors leverage the custom connector functionality, DirectQuery is available (unlike ODBC)
As I’ve mentioned before, the CData connectors enable connectivity to more than 110 sources, both on-premise and in the cloud.
CData Connectors have built-in, optimized data processing (we’re the fastest connectors in the business, often only limited by web speeds when it comes to returning data).
Thanks to deliberate API implementations, each connector is able to push down all supported request features based on the data source.
CData drivers have a robust, innovative SQL to NoSQL interface, offering flattening of nested data and the ability to treat hierarchical structures as separate tables or as a single table built with implicit JOINs.
Why should you use the CData Power BI Connectors?
As businesses grow, so to does the number of data sources they use. Studies show that the average enterprise utilizes 20 cloud-based data sources and at least as many on-premises data stores. Connecting to this disparate data often incurs high development and maintenance costs. And even if you had standard connectivity (via ODBC driver), LIVE access to your disparate data was only a dream.
With an Import connection, you likely dealing with static data or you need to schedule a refresh of the data.
With CData Connectors, the development and maintenance is done for you. And since the DirectQuery functionality is supported, whenever you refresh your dashboards, visualizations, and reports, the underlying data is updated live data from the source.
With the explanations out of the way, it’s time to see the connectors in action. I’ll be performing live demos of our MongoDB and QuickBooks Desktop connectors. I chose on-premise sources since you never know what your connectivity will be like at a conference.
With MongoDB, we can take a look at how the connectors handle the SQL to NoSQL interface and how we push down queries.
With QuickBooks, we’ll get a look at a more business-oriented source that can be used to build visualizations and analytics that result in actionable insights.
Let’s start with MongoDB –
For this demo, we’ll be connecting to a pared down version of the restaurants primer dataset provided by MongoDB.
Let’s start by taking a look at what a document in the restaurants collection looks like.
As you can see, we’ve got some nested objects and arrays in our documents. With the CData Power BI connectors, how this data is parsed is fully configurable. You can choose to leave all objects as aggregates or choose to flatten the objects, the arrays, or both. When the data is flattened, we use dot notation (which often gets translated into underscores for various tools, including Power BI) to denote the nested structure.
The connectors are capable of creating schema files for NoSQL data, to allow further customization of data parsing or to simply accelerate data consumption. The drivers determine the schema through intelligent row scanning and data typing. Before we go any further, lets take a look at configuring our connection to MongoDB. When you configure the connection, you can set the server and port, any authentication (including an authentication database), and configure the NoSQL to SQL interface. For this demo, I want to flatten all objects and I want to flatten the first 2 elements in any arrays we encounter. We can even configure the connector to create schema files and have full control over where those schema files are saved.
Here is a sample schema for the restaurants collection. As you can see, all of the top level fields are easily parsed as columns. The address object is flattened, as are both elements of the coord array. The grades array is also flattened as are the objects that serve as array elements. Note that the dot notation to represent hierarchical data becomes underscore notation for the column names.
With the configuration done, we’re ready to test the connection and get started.
We’ll start with a new Power BI report. When we click data, we can search for CData or click the other tab and find the connector we want. From there, the sequence is just like getting data from any other source. We navigate into the database, select the “table” that we want, and click load data.
From here, we’re ready to build a visualization. In this case, we want to get a map of all of the restaurants, coloring the entries based on the borough and using the score to determine the size of the dot. In the tooltip, we’ll put the name and cuisine of the restaurant. If we wanted, we could filter the results by cuisine. Each time we change the fields and filters, a new query is sent to the MongoDB database and fresh data is returned. The SQL request created by Power BI is translated into a MongoDB request and pushed down to the MongoDB server. Whatever query functionality isn’t supported by MongoDB will be handled in-memory by the SQL Engine built into the connector.
I’ve got a log file that shows the SQL query created by Power BI and the subsequent MongoDB request. So you can see that the specific fields are requested and the filter is applied at the server level, instead of importing the data and relying on the installation machine to handle the data processing.
Next, let’s take a look at an integration with QuickBooks Desktop. (Worth nothing: we have connectors for QuickBooks Online and QuickBooks Point of Sale as well).
Since we’re connecting to structured QuickBooks data, we can jump right into the configuration. Now, it should be said that our QuickBooks Desktop connector comes bundle with another app that eases connectivity to QuickBooks desktop data. The Remote Connector simply provides an easy-to-use web-based proxy for servicing requests between Apps and QuickBooks desktop. We’ve already configured a user for the company file we’ll be working with.
In the DSN, there isn’t actually much for us to do. We simply configure the user and password for the Remote Connector user with access to our Company File. Since our remote connector is local, we get to use the default connection property values. Click test connection and we’re ready to go.
For QuickBooks, we’ll build a stacked chart that for the vendors to display bill payments, by check or credit card. To do so, we want to JOIN the Vendors, BillPaymentChecks and BillPaymentCreditCards tables together. We can do this from the Relationships tab. By JOINing the tables and requesting a limited data set, we drastically reduce the amount of data to be processed by PowerBI, offloading the bulk of the work to the QuickBooks machine. Now, for the demo, that won’t improve much, since QuickBooks is running on the laptop, but in a production environment, it would make a difference. With the relationships configured we’re ready to build our visualization, leveraging the configured relationship to inform the aggregations by Vendor. From there, we can build our chart. And since the connectors use a directquery, every time the visualization is refreshed, new data is requested from QuickBooks.
As you’ve seen, the CData Power BI Connectors provide live connectivity to data from more than 110 different sources
Two key benefits include optimized data processing (we’re seriously the fastest connectors on the market) and collaborative query processing, meaning that you can rely on the data source to manage complex queries and know that you’re working with the minimum amount of data in Power BI.
Learn more (and download a beta or 5) from cdata.com/powerbi
Any questions?
