Choosing a data visualization tool is like being a barista serving coffee: everyone wants their data, their way, personalized, fast, and perfect. Many organizations have a cottage industry of data visualization tools, and it's difficult to know what tool to use, and when. Different tools exist in different departments, and if it doesn't meet the user requirements, the default position is to go back to Excel and move the data around there.
This session will examine data visualization tools such as SSRS Excel, Tableau, QlikView, Datazen, Kibana and PowerBI, in order to craft and blend your data visualization tools to serve your data customers better.
Guidelines for data visualisation: eye vegetables and eye candyJen Stirrup
What's your data visualization vegetables? What's your candy? This session will look at data visualization theory and practice of hot data visualization topics such as: how can you choose which chart to choose and when?
How can you best structure your dashboard?
What about pie charts? What is the fuss about, and when are they best used?
Color blindness - how can you cater for the 1 out of 12 color blind males (and not forgetting the 1 out of 100 color blind females?)
To 3D or not to 3D? Why is it missing in Power View? And any other data visualization topics you care to mention! Come along for dataviz fun, and to learn the "why" along with practical advice.
Synapse is a solution provider with an innovative alternative to commercial off-the-shelf IT applications. Empowering business professionals to shape business processes without being chained to IT applications.
Data Visualisation with Hadoop Mashups, Hive, Power BI and Excel 2013Jen Stirrup
This session focused on data visualisation using Power BI, based on big data. Some examples of Hive and HDFS file storage are given. An overview of Microsoft HDInsight is supplied.
Guidelines for data visualisation: eye vegetables and eye candyJen Stirrup
What's your data visualization vegetables? What's your candy? This session will look at data visualization theory and practice of hot data visualization topics such as: how can you choose which chart to choose and when?
How can you best structure your dashboard?
What about pie charts? What is the fuss about, and when are they best used?
Color blindness - how can you cater for the 1 out of 12 color blind males (and not forgetting the 1 out of 100 color blind females?)
To 3D or not to 3D? Why is it missing in Power View? And any other data visualization topics you care to mention! Come along for dataviz fun, and to learn the "why" along with practical advice.
Synapse is a solution provider with an innovative alternative to commercial off-the-shelf IT applications. Empowering business professionals to shape business processes without being chained to IT applications.
Data Visualisation with Hadoop Mashups, Hive, Power BI and Excel 2013Jen Stirrup
This session focused on data visualisation using Power BI, based on big data. Some examples of Hive and HDFS file storage are given. An overview of Microsoft HDInsight is supplied.
Here are some of the things our Data Analytics team can doLoren Moss
Using tools like Alteryx, AWS Quicksight, and methods such as RegEx, JSON, Python, SQL and SPARQL we can help extract the knowledge hidden in your data. www.unidodigital.com
Due to recent advances in technology, humanity is collecting vast amounts of data at an unprecedented rate, making the skills necessary to mine insights from this data increasingly valuable. So what does it take for a Developer to enter the world of data science?
Join me on a journey into the world of big data and machine learning where we will explore what the work actually looks like, identify which skills are most important, and design a road map for how you too can join this exciting and profitable industry.
Kyvos Insights is unlocking the power of Big Data analytics with “OLAP on Hadoop” technology.
Kyvos is a solution which brings a new model of online analytical processing (OLAP) to Big Data that allows users to visually create and analyze cubes on Hadoop. This technology enables users to easily derive valuable insights for better, more informed business decisions through previously unattainable levels of scalability and interactivity.
Data Con LA 2019 - Big Data Modeling with Spark SQL: Make data valuable by Ja...Data Con LA
In this Data age, business applications generate big data. To generate value out of large scale data applications, data models are the key. Data models serve various purposes, and it is essential to show reliable insights in a timely fashion. This session will cover the technical aspect of leveraging Spark's distributed engine to process Big data to generate insights. It includes a few aspects to optimize processes with Spark SQL. Come join me to explore the process of making data interesting!
Learn How Financial Services Organizations Can Use Big Data to Mitigate RisksMapR Technologies
Risk comes in a variety of forms including uncertainty in financial markets, legal liabilities, operational risk, fraud, and protection against external and internal attacks. Models are becoming increasingly granular and improving risk modeling is a high priority.
Review this presentation from Splunk and MapR to learn how you can study months’ or years’ worth of raw data from disparate sources, without sampling, to understand and reduce risk.
기업은 역사상 가장 급격한 기술 변화 시기에 진입했으며 인공 지능(AI)은 전체 인력의 혁명을 주도하고 있습니다. '일자리의 미래'에 관한 세계 경제 포럼 보고서에 따르면 2018년에는 12개 산업에서 기계가 29%의 작업을 처리했지만, 2022년까지 모든 작업의 42%와 조직의 정보/데이터 처리 및 정보 검색 작업의 62%를 시스템과 알고리즘이 처리할 것이라고 합니다. 이는 불과 4년 만에 이루어지는 급진적 변화입니다.
AI로의 여정은 잘 구축된 정보 아키텍처를 통해 이루어집니다. 대부분의 AI 실패는 AI 모델 자체가 아니라 데이터 준비 및 구성으로 인한 것입니다. AI 모델의 성공은 먼저 성공적인 데이터 수집 방법에 달려 있습니다. 강력한 데이터 기반을 수립해야만 데이터 위치에 관계없이 간편하고 액세스가 쉬워집니다.
이 강연에서 기술자인 아누프 쿠마르(Anup Kumar)는 기업이 성공적으로 AI를 도입하도록 안내하는 중요한 측면을 탐구합니다.
Jira - Solving Reporting Problems using eazyBIMarlon Palha
Presentation and demonstration to show various ways of solving reporting problems in Jira - in this case using eazyBI tools.
Lauma Cirule
Zane Baranovska
Ilze Leite-Apine
Marlon Palha
Dileep Bhat
Madhu Matruba
PyCaret is an open-source, low-code machine learning library in Python that allows you to go from preparing your data to deploying your model within minutes in your choice of environment. This talk is a practical demo on how to use PyCaret in your existing workflows and supercharge your data science team’s productivity.
Frank Bien, CEO of Looker - along with Amazon, Google and other data disrupters - discuss how innovators are deeply integrating analytics into every aspect of their businesses, from mobile to warehouse to cloud.
Frank shares Looker’s vision for the future of business intelligence and data analytics and reveal pivotal product and partnership updates.
Business Intelligence Barista: What DataViz Tool to Use, and When?Jen Stirrup
Choosing a data visualization tool is like being a barista serving coffee: everyone wants their data, their way, personalized, fast, and perfect. Many organizations have a cottage industry of data visualization tools, and it's difficult to know what tool to use, and when. Different tools exist in different departments, and if it doesn't meet the user requirements, the default position is to go back to Excel and move the data around there.
This session will examine data visualization tools such as SSRS Excel, Tableau, QlikView, Datazen, Kibana and PowerBI, in order to craft and blend your data visualization tools to serve your data customers better.
Restructuring Technical Debt - A Software and System Quality ApproachAdnan Masood
Agile Software Architecture based overview of the technical debt metaphor … idea is that developers sometimes accept compromises in a system in one dimension (e.g., modularity) to meet an urgent demand in some other dimension (e.g., a deadline), and that such compromises incur a "debt": on which "interest" has to be paid and which the "principal" should be repaid at some point for the long-term health of the project. (ACM)
Here are some of the things our Data Analytics team can doLoren Moss
Using tools like Alteryx, AWS Quicksight, and methods such as RegEx, JSON, Python, SQL and SPARQL we can help extract the knowledge hidden in your data. www.unidodigital.com
Due to recent advances in technology, humanity is collecting vast amounts of data at an unprecedented rate, making the skills necessary to mine insights from this data increasingly valuable. So what does it take for a Developer to enter the world of data science?
Join me on a journey into the world of big data and machine learning where we will explore what the work actually looks like, identify which skills are most important, and design a road map for how you too can join this exciting and profitable industry.
Kyvos Insights is unlocking the power of Big Data analytics with “OLAP on Hadoop” technology.
Kyvos is a solution which brings a new model of online analytical processing (OLAP) to Big Data that allows users to visually create and analyze cubes on Hadoop. This technology enables users to easily derive valuable insights for better, more informed business decisions through previously unattainable levels of scalability and interactivity.
Data Con LA 2019 - Big Data Modeling with Spark SQL: Make data valuable by Ja...Data Con LA
In this Data age, business applications generate big data. To generate value out of large scale data applications, data models are the key. Data models serve various purposes, and it is essential to show reliable insights in a timely fashion. This session will cover the technical aspect of leveraging Spark's distributed engine to process Big data to generate insights. It includes a few aspects to optimize processes with Spark SQL. Come join me to explore the process of making data interesting!
Learn How Financial Services Organizations Can Use Big Data to Mitigate RisksMapR Technologies
Risk comes in a variety of forms including uncertainty in financial markets, legal liabilities, operational risk, fraud, and protection against external and internal attacks. Models are becoming increasingly granular and improving risk modeling is a high priority.
Review this presentation from Splunk and MapR to learn how you can study months’ or years’ worth of raw data from disparate sources, without sampling, to understand and reduce risk.
기업은 역사상 가장 급격한 기술 변화 시기에 진입했으며 인공 지능(AI)은 전체 인력의 혁명을 주도하고 있습니다. '일자리의 미래'에 관한 세계 경제 포럼 보고서에 따르면 2018년에는 12개 산업에서 기계가 29%의 작업을 처리했지만, 2022년까지 모든 작업의 42%와 조직의 정보/데이터 처리 및 정보 검색 작업의 62%를 시스템과 알고리즘이 처리할 것이라고 합니다. 이는 불과 4년 만에 이루어지는 급진적 변화입니다.
AI로의 여정은 잘 구축된 정보 아키텍처를 통해 이루어집니다. 대부분의 AI 실패는 AI 모델 자체가 아니라 데이터 준비 및 구성으로 인한 것입니다. AI 모델의 성공은 먼저 성공적인 데이터 수집 방법에 달려 있습니다. 강력한 데이터 기반을 수립해야만 데이터 위치에 관계없이 간편하고 액세스가 쉬워집니다.
이 강연에서 기술자인 아누프 쿠마르(Anup Kumar)는 기업이 성공적으로 AI를 도입하도록 안내하는 중요한 측면을 탐구합니다.
Jira - Solving Reporting Problems using eazyBIMarlon Palha
Presentation and demonstration to show various ways of solving reporting problems in Jira - in this case using eazyBI tools.
Lauma Cirule
Zane Baranovska
Ilze Leite-Apine
Marlon Palha
Dileep Bhat
Madhu Matruba
PyCaret is an open-source, low-code machine learning library in Python that allows you to go from preparing your data to deploying your model within minutes in your choice of environment. This talk is a practical demo on how to use PyCaret in your existing workflows and supercharge your data science team’s productivity.
Frank Bien, CEO of Looker - along with Amazon, Google and other data disrupters - discuss how innovators are deeply integrating analytics into every aspect of their businesses, from mobile to warehouse to cloud.
Frank shares Looker’s vision for the future of business intelligence and data analytics and reveal pivotal product and partnership updates.
Business Intelligence Barista: What DataViz Tool to Use, and When?Jen Stirrup
Choosing a data visualization tool is like being a barista serving coffee: everyone wants their data, their way, personalized, fast, and perfect. Many organizations have a cottage industry of data visualization tools, and it's difficult to know what tool to use, and when. Different tools exist in different departments, and if it doesn't meet the user requirements, the default position is to go back to Excel and move the data around there.
This session will examine data visualization tools such as SSRS Excel, Tableau, QlikView, Datazen, Kibana and PowerBI, in order to craft and blend your data visualization tools to serve your data customers better.
Restructuring Technical Debt - A Software and System Quality ApproachAdnan Masood
Agile Software Architecture based overview of the technical debt metaphor … idea is that developers sometimes accept compromises in a system in one dimension (e.g., modularity) to meet an urgent demand in some other dimension (e.g., a deadline), and that such compromises incur a "debt": on which "interest" has to be paid and which the "principal" should be repaid at some point for the long-term health of the project. (ACM)
Digital Pragmatism with Business Intelligence, Big Data and Data VisualisationJen Stirrup
Contact details:
Jen.Stirrup@datarelish.com
In a world where the HiPPO’s (Highest Paid Person’s Opinion) is final, how can we use technology to drive the organisation towards data-driven decision making as part of their organizational DNA? R provides a range of functionality in machine learning, but we need to expose its richness in a world where it is made accessible to decision makers. Using Data Storytelling with R, we can imprint data in the culture of the organization by making it easily accessible to everyone, including decision makers. Together, the insights and process of machine learning are combined with data visualisation to help organisations derive value and insights from big and little data.
System Quality Attributes for Software ArchitectureAdnan Masood
Software Quality Attributes are the benchmarks that describe system’s intended behavior. These slides go through an overview of what some of these attributes are and how to evaluate them.
How Universities Use Big Data to Transform EducationHortonworks
Student performance data is increasingly being captured as part of software-based and online classroom exercises and testing. This data can be augmented with behavioral data captured from sources such as social media, student-professor meeting notes, blogs, student surveys, and so forth to discover new insights to improve student learning. The results transcend traditional IT departments to focus on issues like retention, research, and the delivery of content and courses through new modalities.
Hortonworks is partnering with Microsoft to show you how the Hortonworks Data Platform (HDP) running on the Microsoft stack enables you to develop a “single view of a student”.
Intorducing Big Data and Microsoft AzureKhalid Salama
The purpose of these slides is to give a high-level overview of Big Data concepts and techniques, as well as its related tools and technologies, focusing on Microsoft Azure. It starts by defining what Big Data is, as well as why Big Data platforms are needed. Fundamental components of a Big Data Platform are discussed, followed by a little bit of theory about Distributed Processing & CAP Theorem, and its relevance to how Big Data Solutions compare to Traditional RDBMS. Use case of how Big Data fits in Enterprise Data Platforms are shown. The Hadoop Ecosystem is briefly reviewed before Big Data on Microsoft Azure is discussed. Then some directions of How to get started with Big Data.
How to Use Apache Zeppelin with HWX HDBHortonworks
Part five in a five-part series, this webcast will be a demonstration of the integration of Apache Zeppelin and Pivotal HDB. Apache Zeppelin is a web-based notebook that enables interactive data analytics. You can make beautiful data-driven, interactive and collaborative documents with SQL, Scala and more. This webinar will demonstrate the configuration of the psql interpreter and the basic operations of Apache Zeppelin when used in conjunction with Hortonworks HDB.
Building the Data Lake with Azure Data Factory and Data Lake AnalyticsKhalid Salama
In essence, a data lake is commodity distributed file system that acts as a repository to hold raw data file extracts of all the enterprise source systems, so that it can serve the data management and analytics needs of the business. A data lake system provides means to ingest data, perform scalable big data processing, and serve information, in addition to manage, monitor and secure the it environment. In these slide, we discuss building data lakes using Azure Data Factory and Data Lake Analytics. We delve into the architecture if the data lake and explore its various components. We also describe the various data ingestion scenarios and considerations. We introduce the Azure Data Lake Store, then we discuss how to build Azure Data Factory pipeline to ingest the data lake. After that, we move into big data processing using Data Lake Analytics, and we delve into U-SQL.
Dynamic Column Masking and Row-Level Filtering in HDPHortonworks
As enterprises around the world bring more of their sensitive data into Hadoop data lakes, balancing the need for democratization of access to data without sacrificing strong security principles becomes paramount. In this webinar, Srikanth Venkat, director of product management for security & governance will demonstrate two new data protection capabilities in Apache Ranger – dynamic column masking and row level filtering of data stored in Apache Hive. These features have been introduced as part of HDP 2.5 platform release.
Think of big data as all data, no matter what the volume, velocity, or variety. The simple truth is a traditional on-prem data warehouse will not handle big data. So what is Microsoft’s strategy for building a big data solution? And why is it best to have this solution in the cloud? That is what this presentation will cover. Be prepared to discover all the various Microsoft technologies and products from collecting data, transforming it, storing it, to visualizing it. My goal is to help you not only understand each product but understand how they all fit together, so you can be the hero who builds your companies big data solution.
Modern Data Architecture for a Data Lake with Informatica and Hortonworks Dat...Hortonworks
How do you turn data from many different sources into actionable insights and manufacture those insights into innovative information-based products and services?
Industry leaders are accomplishing this by adding Hadoop as a critical component in their modern data architecture to build a data lake. A data lake collects and stores data across a wide variety of channels including social media, clickstream data, server logs, customer transactions and interactions, videos, and sensor data from equipment in the field. A data lake cost-effectively scales to collect and retain massive amounts of data over time, and convert all this data into actionable information that can transform your business.
Join Hortonworks and Informatica as we discuss:
- What is a data lake?
- The modern data architecture for a data lake
- How Hadoop fits into the modern data architecture
- Innovative use-cases for a data lake
Data science with Windows Azure - A Brief IntroductionAdnan Masood
Data Science with Windows Azure is an introduction to HDInsight and Hadoop offerings from Microsoft Machine Learning and Big Data Cloud based platform. This was presented at Microsoft Data Science Group – Tampa Analytics Professionals.
This presentation was given to the Tech Change Technology for Monitoring and Evaluation Diploma course on 25th September 2015. It covers:
Why visualise data?
Where to start?
Which tools to use?
It ends with an overview of Kwantu's approach to this area and the technology choices that we've made.
The New Frontier: Optimizing Big Data ExplorationInside Analysis
The Briefing Room with Dr. Robin Bloor and Cirro
Live Webcast on February 11, 2014
Watch the archive: https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=0ec1fa381886313cc06d841015c65898
As information ecosystems continue to expand, businesses are searching for ways to combine traditional analytics with a new source of insight: Big Data. But with data flooding in from all kinds of sources, fast access and performance at scale can easily become an issue. One effective approach for solving this challenge is data federation, a method that involves taking the analytical processing to the data, allowing streamlined access to multiple data sources without the expensive ETL overhead or building of semantic layers.
Register for this episode of The Briefing Room to hear veteran Analyst Dr. Robin Bloor as he explains how the prevalence of distributed data calls for a new approach to Big Data. He will be briefed by Mark Theissen of Cirro, who will tout his company’s Data Hub, a data federation solution that provides a single point of access to all enterprise data assets without excessive data movements, preprocessing or staging. He will discuss how data federation differs from virtualization and ETL approaches, and demonstrate how a Cirro deployment solves the analytics challenge of integrating data silos across the data center – and the cloud – using the BI tools you already have on your desktop for real-time distributed analytics.
Visit InsideAnlaysis.com for more information.
Education Analytics solution based on open source including KPIs, reports, OLAP Analysis, Dashboards, Scorecards, Big Data and Machine Learning with 'predefined templates, dashboards and KPIs/ratios' and fully customizable environment
This is a Powerpoint Presentation based on the comparison of various available analytical tools. This includes various tools for business analytics and their detailed description.
Data Visualization - UC Analytics Conference 2018Russell Spangler
Data visualization presentation provided during the University of Cincinnati Data and Analytics conference. Discusses how to build out a data visualization group from scratch.
Riga dev day 2016 adding a data reservoir and oracle bdd to extend your ora...Mark Rittman
This talk focus is on what a data reservoir is, how it related to the RDBMS DW, and how Big Data Discovery provides access to it to business and BI users
Public Administration Analytics solution based on open source including KPIs, reports, OLAP Analysis, Dashboards, Scorecards, Big Data and Machine Learning with 'predefined templates, dashboards and KPIs/ratios' and fully customizable environment
Telco and IT Analytics solution based on open source including KPIs, reports, OLAP Analysis, Dashboards, Scorecards, Big Data and Machine Learning with 'predefined templates, dashboards and KPIs/ratios' and fully customizable environment
Pharma Analytics solution based on open source including KPIs, reports, OLAP Analysis, Dashboards, Scorecards, Big Data and Machine Learning with 'predefined templates, dashboards and KPIs/ratios' and fully customizable environment
Human Resources Analytics solution based on open source including KPIs, reports, OLAP Analysis, Dashboards, Scorecards, Big Data and Machine Learning with 'predefined templates, dashboards and KPIs/ratios' and fully customizable environment
Jen Vaughan will walk you through readying yourself to apply for jobs using Tableau. From what to look for in a candidate, resume and how to gain a competitive edge.
Lean Analytics is a set of rules to make data science more streamlined and productive. It touches on many aspects of what a data scientist should be and how a data science project should be defined to be successful. During this presentation Richard will present where data science projects go wrong, how you should think of data science projects, what constitutes success in data science and how you can measure progress. This session will be loaded with terms, stories and descriptions of project successes and failures. If you're wondering whether you're getting value out of data science, how to get more value out of it and even whether you need it then this talk is for you!
What you will take away from this session
Learn how to make your data science projects successful
Evaluate how to track progress and report on the efficacy of data science solutions
Understand the role of engineering and data scientists
Understand your options for processes and software
A design system can vastly improve your team's productivity, but most of all, it leads to better products! The challenge lies in creating a mature system and leading its adoption across the company successfully. Let's talk about how we learned to meet the needs of different designers and developers on different products, on different tech stacks, on different platforms. Attendees will go home with tips they can use to improve design systems of any stage.
Similar to Business Intelligence Barista: What DataViz Tool to Use, and When? (20)
The Metaverse and AI: how can decision-makers harness the Metaverse for their...Jen Stirrup
The Metaverse is popularized in science fiction, and now it is becoming closer to being a part of our daily lives through the use of social media and shopping companies. How can businesses survive in a world where Artificial Intelligence is becoming the present as well as the future of technology, and how does the Metaverse fit into business strategy when futurist ideas are developing into reality at accelerated rates? How do we do this when our data isn't up to scratch? How can we move towards success with our data so we are set up for the Metaverse when it arrives?
How can you help your company evolve, adapt, and succeed using Artificial Intelligence and the Metaverse to stay ahead of the competition? What are the potential issues, complications, and benefits that these technologies could bring to us and our organizations? In this session, Jen Stirrup will explain how to start thinking about these technologies as an organisation.
AI Applications in Healthcare and Medicine.pdfJen Stirrup
This session was delivered for the Global Business Roundtable. The topic: AI applications in Healthcare and Medicine. In this session, Jennifer Stirrup takes people through a general process of adopting AI in their organisations.
BUILDING A STRONG FOUNDATION FOR SUCCESS WITH BI AND DIGITAL TRANSFORMATIONJen Stirrup
The objective of Digital Transformation is improve the quality and resilience of digital services to serve customers better, and data is a cruel part of fulfilling that ambition. As the organisation moves forward in pursuit of its strategic ambitions, it will need to remain focused on the stabilisation and improvement of existing technology and data foundations. To succeed, organisations need continuously strive to improve data, systems and processes for people using digital solutions; it is not simply digitising paper processes. The challenge of digital transformation is to work with people, but how can you build systems that serve them well to achieve and deliver more in a customer-focused way? Innovators will relish the opportunity to adopt new technology, but laggars are often waiting for proof that this will help them deliver better services or products. The challenge is that the adoption of digital solutions varies significantly from one person to the next, one team to the next and one organisation to the next. In this keynote, there will be a discussion of the industry landscape followed by takeaways that will help digital transformation in your organization.
1. Do more than get the basics right
2. Build confidence in changes through better use of data
3. How to oversee delivery while considering strategy
CuRious about R in Power BI? End to end R in Power BI for beginners Jen Stirrup
In this session, we will start R right from the beginning, from installing R through to datatransformation and integration, through to visualizing data by using R in PowerBI. Then, we will move towards powerful but simple to use datatypes in R such as data frames. We will also upgrade our data analysis skills by looking at Rdata transformation using a powerful set of tools to make things simple: the tidyverse. Then, we will look at integrating our R work into Power BI, and visualizing our data using beautiful visualizations with R and Power BI. Finally, we will share our work by publishing our Power BI project, with our R code, to the Power BI service. We will also look at refreshing our dataset so that our new dashboard has refreshed data.
This session is aimed at getting beginners up to speed as gently and quickly as possible. Join this session if you are curious about R and want to know more. If you are already a Power BI expert, join this session to open up a whole new world of Power BI to add toyour skill set. If you are new to Power BI, you will still get value from this session since you'll be able to see a Power BI dashboard being built in an end-to-end solution.
Artificial Intelligence Ethics keynote: With Great Power, comes Great Respons...Jen Stirrup
Artificial Intelligence has been receiving some bad press recently, with respect to its ethical consequences in terms of changes to working conditions, deepfake technology and even job losses. Organizations are concerned about bias in their data, perpetuating stereotypes and neglecting responsibility. How can AI systems treat all people fairly? What about concerns of safety and reliability?
In this keynote, we will explore the toolkits available in Azure to help businesses to navigate the complex ethics environment. Join this session to understand what Microsoft can offer in terms of supporting organisations to consider ethics as an integral part of their AI solutions.
1 Introduction to Microsoft data platform analytics for releaseJen Stirrup
Part 1 of a conference workshop. This forms the morning session, which looks at moving from Business Intelligence to Analytics.
Topics Covered: Azure Data Explorer, Azure Data Factory, Azure Synapse Analytics, Event Hubs, HDInsight, Big Data
Comparing Microsoft Big Data Platform TechnologiesJen Stirrup
In this segment, we look at technologies such as HDInsight, Azure Databricks, Azure Data Lake Analytics and Apache Spark. We compare the technologies to help you to decide the best technology for your situation.
Introduction to Analytics with Azure Notebooks and PythonJen Stirrup
Introduction to Analytics with Azure Notebooks and Python for Data Science and Business Intelligence. This is one part of a full day workshop on moving from BI to Analytics
When looking at Sales Analytics, where should you start? What should you measure? This session provides ideas on sales metrics, implemented in Power BI
Diversity and inclusion for the newbies and doersJen Stirrup
This presentation is aimed at people who want to *do* something positive for diversity and inclusion in their workplaces and communities, but don't know where to start to have a quick impact. I've made up a checklist of 7 'E's to help people along. We cover crucial topics such as: • What can we do to tackle unconscious bias in our systems, solutions and interactions with others? • How can we be more inclusive towards others? • How can we encourage and mentor younger generations to get involved in STEM topics and technical roles both as leaders and in the communities of people who surround us? I hope you enjoy this interactive and thought-provoking discussion of diversity and inclusion, aimed at people who want to get started and do something positive and impactful to help others.
Artificial Intelligence from the Business perspectiveJen Stirrup
What is AI from the Business perspective? In this presentation, Jen Stirrup discusses the 8 'C's of Artificial Intelligence from the business leadership perspective.
How to be successful with Artificial Intelligence - from small to successJen Stirrup
Keynote from AI World Congress in October 2019. Artificial Intelligence isn't just for the technies; it is crucial that business-oriented individuals adopt this technology, which can be conceived as the fourth industrial age. Artificial intelligence is becoming closer to being a a part of our daily lives through the use of technologies like virtual assistants such as Alexa, smart homes, and automated customer service. Now, we are running the race not just to win, but to survive in a world where Artificial Intelligence is becoming the present as well as the future of technology, and futurist ideas are developing into reality at accelerated rates.
How can you help your your company to evolve, adapt and succeed using Artificial Intelligence to stay at the forefront of the competition, and win the race for AI adoption in your organization? What are the potential issues, complications and benefits that artificial intelligence could bring to us and our organisations? In this session, Jen Stirrup will explain the quick wins to win the Red Queen's Race in Artificial Intelligence.
Artificial Intelligence: Winning the Red Queen’s Race Keynote at ESPC with Je...Jen Stirrup
Artificial Intelligence is popularised in fiction films such as “The Terminator” and “AI: Artificial Intelligence”. Now, artificial intelligence is becoming closer to being a part of our daily lives through the use of technologies like virtual assistants such as Cortana, smart homes, and automated customer service.
Now, we are running the Red Queen’s race not just to win, but to survive in a world where Artificial Intelligence is becoming the present as well as the future of technology, and futurist ideas are developing into reality at accelerated rates.
How can you help your your company to evolve, adapt and succeed using Artificial Intelligence to stay at the forefront of the competition, and win the Red Queen’s Race? What are the potential issues, complications and benefits that artificial intelligence could bring to us and our organisations?
In this keynote, Jen Stirrup explains the quick wins to win the Red Queen’s Race, using demos from Microsoft technologies such as AutoML to help you and your organisation win the Red Queen’s race.
Data Visualization dataviz superpower! Guidelines on using best practice data visualization principles for Power BI, Excel, SSRS, Tableau and other great tools!
R - what do the numbers mean? #RStats This is the presentation for my Demo at Orlando Live60 AILIve. We go through statistics interpretation with examples
Artificial Intelligence and Deep Learning in Azure, CNTK and TensorflowJen Stirrup
Artificial Intelligence and Deep Learning in Azure, using Open Source technologies CNTK and Tensorflow. The tutorial can be found on GitHub here: https://github.com/Microsoft/CNTK/tree/master/Tutorials
and the CNTK video can be found here: https://youtu.be/qgwaP43ZIwA
Blockchain Demystified for Business Intelligence ProfessionalsJen Stirrup
Blockchain is a transformational technology with the potential to extend digital transformation beyond an organization and into the processes it shares with suppliers, customers, and partners.
What is blockchain? What can it do for my organization? How can your organisation manage a blockchain implementation? How does it work in Azure?
Join this session to learn about blockchain and see it in action. We will also discuss the use cases for blockchain, and whether it is here to stay.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
23. Why R?
• most widely used data analysis software - used by 2M + data scientist,
statisticians and analysts
• Most powerful statistical programming language
• flexible, extensible and comprehensive for productivity
• Create beautiful and unique data visualisations - as seen in New York Times,
Twitter and Flowing Data
• Thriving open-source community - leading edge of analytics research
• Fills the talent gap - new graduates prefer R.
24. Growth in Demand
• Rexer Data Mining survey, 2007 - 2013
• R is the highest paid IT skill Dice.com, Jan 2014
• R most used-data science language after SQL -
O'Reilly, Jan 2014
• R is used by 70% of data miners. Rexer, Sept 2013
25. Growth in Demand
• R is #15 of all programming languages. REdMonk, Jan
2014
• R growing faster than any other data science language.
KDNuggs.
• R is in-memory and limited in the size of data that you
can process.
26. What do I need to install?
• Install R – www.r-project.org
• Install Rstudio – www.rstudio.com
• Handy Shortcuts
• Tab – autocomplete of available functions
• Control and Up Arrow – History
• Control and enter – executes the line of code
27. What tools do we have in R?
• 80% of your time will be spent preparing and wrangling data
• The remainder of your time will be spent complaining about it.
• dplyr: the essential data manipulation toolset
• In data wrangling, what are the main tasks?
• – Filtering rows
– Selecting columns of data
– Adding new variables
– Sorting
– Aggregating
36. Kibana
• It is highly customizable dashboarding
• It is constituted of panels:
– Time picker / Query / Filtering
– Charts / Table / Text
37. Flexible analytics and visualization platform
Real-time summary and charting of streaming
data
Intuitive interface for a variety of users
Instant sharing and embedding of dashboards
38. To better understand large volumes of data..
• easily create bar charts
• line and scatter plots
• Histograms
• pie charts
• maps.
39. To better understand large volumes of data..
• easily create bar charts
• line and scatter plots
• Histograms
• pie charts
• maps.
We will look at: introductory R and why it's useful, and where to go for more information. We will learn statistics and R by looking at: independent events, dependent probability, combinatorics, hypothesis testing, descriptive statistics, random variables, probability distributions, regression, and inferential statistics. We will loosely base the curriculum on the Khan Academy statistics course, but we aim to help the curious, the scared, and the rookie.
Effective: the viewer gets it (ease of interpretation)
Accurate: sufficient for correct quantitative evaluation. Lie factor = size of visual effect/size of data effect
Efficient: minimize data-ink ratio and chart-junk, show data, maximize data-ink ratio, brase non-data-ink, brase redundant data-ink
Aesthetics: must not offend viewer's senses (e.g. moire patterns)
Adaptable: can adjust to serve multiple needs
Effective: the viewer gets it (ease of interpretation)
Accurate: sufficient for correct quantitative evaluation. Lie factor = size of visual effect/size of data effect
Efficient: minimize data-ink ratio and chart-junk, show data, maximize data-ink ratio, brase non-data-ink, brase redundant data-ink
Aesthetics: must not offend viewer's senses (e.g. moire patterns)
Adaptable: can adjust to serve multiple needs