Presentation made to Alteryx Inspire Conference (London 2019) by Matt Semple (Iron Mountain) and David Turley (InterWorks) explaining the data journey undertaken by Iron Mountain to transform its analytics function and deliver advanced commercial and operational analytics to its global management teams.
A transformation journey leveraging the advanced technology of Alteryx and Tableau aligned to a clear vision of the data roadmap. All supported by a great consulting partnership with the InterWorks team in London.
This document provides an overview of the Alteryx self-service data analytics platform. It describes Alteryx as a platform that combines data preparation, blending, and predictive, statistical and spatial analytics in an intuitive interface. It then discusses the different types of users of Alteryx, including data analysts, BI developers, and DBAs. Finally, it promotes trying Alteryx for free and provides a demonstration of its data preparation, blending, statistical analysis and spatial analysis capabilities using Pokémon Go datasets.
The Alteryx Designer solves this by delivering an intuitive workflow for data blending and advanced analytics that leads to deeper insights in hours, not the weeks typical of traditional approaches! The Alteryx Designer empowers data analysts by combining data blending, predictive analytics, spatial analytics, and reporting, visualization and analytic apps into one workflow.
1) The document discusses business intelligence and data visualization. It covers topics like choosing the right visualization type, showing data clearly without distortion, providing proper context, making efficient use of screen space, and considering the consumption medium.
2) A news article announces that Datameer and Tableau now have a technology connector, allowing joint customers to consume, shape, enrich, and visualize big data.
3) Datawatch Corporation declares the general availability of its flagship data preparation solution Datawatch Monarch version 13, which provides self-service data preparation capabilities.
Radical Stack is an end-to-end architecture that offers business analysts access to data and the ability to ask new questions quickly without needing additional personnel for programming or administration. Traditional ELT and data warehousing approaches require months of work from programmers and administrators to prepare the data for business analysts, who then have limited control and must repeat the process to get new insights. Radical Stack uses Hadoop technologies like SQL on Hadoop, MapReduce, Hive and Pig to make data easily accessible to data administrators, data scientists and business analysts within minutes without additional hiring, allowing for faster collaboration and exploration of the data.
This document summarizes the growth and strategy of InfluxData, a time-series database company. It discusses how InfluxData was founded in 2013, has grown to over 450 customers with 175,000 instances in use today. It outlines InfluxData's platform strategy to be the platform of choice for metrics and event workloads across infrastructure, IoT, and business applications. The document characterizes InfluxData's customers and their use cases, and highlights some example customers including Bethesda Games, Wayfair, and Playtech. It discusses InfluxData's core focus on developer happiness, being purpose-built for time-series data, and commitment to open source.
Achieving Massive Concurrency & Sub-second Query Latency on Cloud Warehouses ...Alluxio, Inc.
Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
Achieving Massive Concurrency & Sub-second Query Latency on Cloud Warehouses & Data Lakes with Kyligence Cloud
George Demarest, Head of Marketing, Kyligence
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
Using Apache Spark for Intelligent Services: Keynote at Spark Summit East by ...Spark Summit
Salesforce is developing Einstein which is an artificial intelligence (AI) capability built into the core of the Salesforce Platform. Einstein helps power the world’s smartest CRM to deliver advanced AI capabilities to sales, services, and marketing teams – helping them discover new insights, predict likely outcomes to power smarter decision making, recommend next steps, and automate workflows so users can focus on building meaningful relationships with every customer.
Salesforce is using Apache Spark (batch, streaming, GraphX and ML) to power the Einstein platform and services. In this keynote and demo, Alexis will highlight how Salesforce is building intelligent Services for Einstein using activity data by leveraging Spark and Databricks to scale data science and engineering.
How a global manufacturing company built a data science capability from scratchCarlo Torniai
In less than a year, Pirelli, a global manufacturing company best known for high-performance tires and motorsports, grew an impactful data science capability from the ground up. I am sharing a how-to guide for doing the same in your organization, equipping you with arguments to marshal and concrete tips to follow, while calling out pitfalls to watch out for along the way.
This document provides an overview of the Alteryx self-service data analytics platform. It describes Alteryx as a platform that combines data preparation, blending, and predictive, statistical and spatial analytics in an intuitive interface. It then discusses the different types of users of Alteryx, including data analysts, BI developers, and DBAs. Finally, it promotes trying Alteryx for free and provides a demonstration of its data preparation, blending, statistical analysis and spatial analysis capabilities using Pokémon Go datasets.
The Alteryx Designer solves this by delivering an intuitive workflow for data blending and advanced analytics that leads to deeper insights in hours, not the weeks typical of traditional approaches! The Alteryx Designer empowers data analysts by combining data blending, predictive analytics, spatial analytics, and reporting, visualization and analytic apps into one workflow.
1) The document discusses business intelligence and data visualization. It covers topics like choosing the right visualization type, showing data clearly without distortion, providing proper context, making efficient use of screen space, and considering the consumption medium.
2) A news article announces that Datameer and Tableau now have a technology connector, allowing joint customers to consume, shape, enrich, and visualize big data.
3) Datawatch Corporation declares the general availability of its flagship data preparation solution Datawatch Monarch version 13, which provides self-service data preparation capabilities.
Radical Stack is an end-to-end architecture that offers business analysts access to data and the ability to ask new questions quickly without needing additional personnel for programming or administration. Traditional ELT and data warehousing approaches require months of work from programmers and administrators to prepare the data for business analysts, who then have limited control and must repeat the process to get new insights. Radical Stack uses Hadoop technologies like SQL on Hadoop, MapReduce, Hive and Pig to make data easily accessible to data administrators, data scientists and business analysts within minutes without additional hiring, allowing for faster collaboration and exploration of the data.
This document summarizes the growth and strategy of InfluxData, a time-series database company. It discusses how InfluxData was founded in 2013, has grown to over 450 customers with 175,000 instances in use today. It outlines InfluxData's platform strategy to be the platform of choice for metrics and event workloads across infrastructure, IoT, and business applications. The document characterizes InfluxData's customers and their use cases, and highlights some example customers including Bethesda Games, Wayfair, and Playtech. It discusses InfluxData's core focus on developer happiness, being purpose-built for time-series data, and commitment to open source.
Achieving Massive Concurrency & Sub-second Query Latency on Cloud Warehouses ...Alluxio, Inc.
Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
Achieving Massive Concurrency & Sub-second Query Latency on Cloud Warehouses & Data Lakes with Kyligence Cloud
George Demarest, Head of Marketing, Kyligence
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
Using Apache Spark for Intelligent Services: Keynote at Spark Summit East by ...Spark Summit
Salesforce is developing Einstein which is an artificial intelligence (AI) capability built into the core of the Salesforce Platform. Einstein helps power the world’s smartest CRM to deliver advanced AI capabilities to sales, services, and marketing teams – helping them discover new insights, predict likely outcomes to power smarter decision making, recommend next steps, and automate workflows so users can focus on building meaningful relationships with every customer.
Salesforce is using Apache Spark (batch, streaming, GraphX and ML) to power the Einstein platform and services. In this keynote and demo, Alexis will highlight how Salesforce is building intelligent Services for Einstein using activity data by leveraging Spark and Databricks to scale data science and engineering.
How a global manufacturing company built a data science capability from scratchCarlo Torniai
In less than a year, Pirelli, a global manufacturing company best known for high-performance tires and motorsports, grew an impactful data science capability from the ground up. I am sharing a how-to guide for doing the same in your organization, equipping you with arguments to marshal and concrete tips to follow, while calling out pitfalls to watch out for along the way.
The document discusses reporting options for the Oracle Eloqua marketing automation platform. It provides an overview of the current native reporting tools Insight and Analyzer, and details about the future state including the new Oracle Business Intelligence (OBI) tool. It also discusses taking data out of Eloqua through the bulk API or custom applications to do additional custom reporting and analytics.
SQL In Hadoop: Big Data Innovation Without the RiskInside Analysis
The Briefing Room with Dr. Robin Bloor and Actian
Live Webcast July 14, 2015
Watch the Archive: https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=bbd4395ea2f8c60a03cfefc68c7aa823
Innovation often implies risk, which is why businesses have many issues to weigh when considering change. Yet the remarkable growth of data is driving many traditional systems into the ground, forcing information workers to take a critical look at their existing tools. Technologies like Hadoop offer economical solutions to big data management, but to truly take advantage of its capabilities, organizations must modernize their infrastructure.
Register for this episode of The Briefing Room to learn from veteran Analyst Dr. Robin Bloor as he explains how and why organizations should improve legacy systems. He’ll be briefed by Todd Untrecht of Actian, who will tout his company’s Actian Vortex, a SQL-in-Hadoop solution. He will show how integrating a SQL engine directly in the Hadoop cluster can lead to faster analytics and greater control, while still maintaining existing investments.
Visit InsideAnalysis.com for more information.
This document discusses using big data analytics for traffic management. It describes capturing live traffic and accident data in a big data reservoir to analyze traffic congestion. The solution allows users to view, analyze, and act on real-time traffic data and provide alerts to save lives. It also simulates traffic scenarios to predict the impact of accidents.
Presentation of candidates for StartUp Pitch Contest "Unlocking the Value of Data in Logistics", powered by DB Schenker at #VivaTech, on 16th May 2019 in Paris.
SAP Database Platform, ASE & IoT RoadmapPaul Marriott
Paul Marriott presented on SAP's database platform roadmap and key topics including Sybase ASE, IoT, and HANA adoption. The presentation covered enhancements to Sybase ASE 16 including improved scalability, performance, security and manageability. It also discussed how digital transformation and the rise of IoT is driving new business models and the need for real-time analytics. Examples were given of how companies like John Deere, Harley Davidson, and Hamburg Port Authority are leveraging connected technologies.
EPSi was founded in 1999 with the goal of re-engineering decision support. Over the past 20 years we have grown our client base to over 950+ individual healthcare institutions across the United States and internationally. Our customers rely on our platform for the insights they need, including 15 of the top 20 U.S. News & World Best Hospitals; and, and, our experience in delivering world-class financial decision support and integrated performance management applications is unparalleled.
EPSi’s platform has always been highly scalable. We have installations in regional medical centers and community hospitals, as well as large health systems. This includes 128 Integrated Health System customers, among them Catholic Health Initiatives, a flagship EPSi customer and one of the nation's largest healthcare systems comprised of 108 acute care hospitals and over 11,000 beds. EPSi’s base also includes 40 very prestigious academic medical centers and 14 stand-alone pediatric hospitals using our software applications.
In addition to the above, EPSi continues our rich history of innovation with the launch of our new RealCost™ platform. Our vision for RealCost™ was catalyzed by the rapidly changing healthcare landscape with new reimbursement models, increasing cost of care and organizational consolidation; while available systems today do not offer the level of integration, precision, and timeliness required to optimize effective decision making.
RealCost™ changes all of this with a high performing, cloud-based solution encompassing specific application modules along with intuitive workflow and embedded analytics. One of the goals of RealCost™ is to predict upcoming cost variances so that you can avoid costs before they happen – thereby empowering healthcare organizations to move away from the traditional practice of month-end retrospective analysis and inefficient backend processes – in favor of real-time actions – to help drive more timely and effective decision making for streamlining operations and improving financial outcomes.
RealCost will supplement existing decision support applications – and in some cases replace specific decision support system functions entirely – like Cost Accounting, the first RealCost™ module released in 2018. Additional modules scheduled for release in 2019 include Rolling Forecast and Real Time Cost.
The document discusses Tableau and Alteryx data analytics platforms. It provides an overview of Alteryx, describing it as a self-service data analytics platform that allows users to analyze, enrich, prepare, blend, and share data using a visual workflow interface. The document also includes sections on Alteryx's market, demonstrations of its capabilities through use cases, reference customer cases, and a question and answer period.
Altilia Enterprise Data World 2014 PresentationMassimo Ruffolo
The presentation I will use at the enterprise Data World 2014 for introducing the MANTRA Smart Data Management Platform and the two products MANTRA Data Capture and Mantra Holistic Intelligence
EWS has undertaken several initiatives to improve its data analytics capabilities, mobile services, and development processes:
1) The data analytics initiative introduced a big data ecosystem focusing on descriptive, exploratory, inferential, predictive, causal, and mechanistic analytics using tools like Hadoop, Spark, and R. Specialized skills and technologies were acquired.
2) The mobility services initiative leveraged existing talent to implement cross-platform mobile apps using HTML5 while strengthening native and cross-platform skills. Tools for rapid mobile app development and AWS Mobile were also introduced.
3) The Agile/CI/CD initiative brought the organization into test-driven Agile development with continuous integration and delivery through training, documentation,
The document summarizes a program kickoff event for Tableau and Alteryx users. It included sessions on trends in self-service BI, Tableau enablement at a company, the Tableau roadmap, and using Alteryx for data flow control. About 200 professionals attended the event, which featured a recap session using the Sli.do platform to gather feedback. Trends discussed included digitalization, consumerization, mobility, cloud, and artificial intelligence. A survey showed that data discovery/self-service BI and data preparation/blending were top priorities.
Embedding Insight through Prediction Driven LogisticsDatabricks
Aggreko are a leading provider of temporary power and temperature control solutions, serving customers across the globe as they work on projects ranging from the Olympics to aiding humanitarian disaster relief. In this talk, Helena and Andy will discuss how the Insights team have developed scalable machine learning solutions to support the business. In particular they will discuss fuel consumption forecasts that have helped Aggreko’s fuel logistics teams improve customer service levels and reduce costs by becoming more proactive and insight driven.
The document outlines an agenda for the Manchester MuleSoft Meetup Group meeting. The agenda includes introductions of organizers, sponsors, and a new attendee poll. It then covers two main topics: API Specification Automation via Platform APIs and 7 Steps to Achieving Effective API Insights. Each topic includes a presentation and Q&A section. The document provides details on the speakers and their backgrounds. It concludes with announcements about Anypoint Studio and Anypoint Flex Gateway updates.
Bringing Velocity and Momentum to Digital Transformation ProjectsAcquia
If your digital transformation efforts feel like they are forever stuck in the planning stage, you are not alone. Drawing on lessons learned from high-velocity digital transformations for enterprise built on Drupal and Acquia, Ben Beath will bring to life a framework for delivering customer value in just 12 weeks.
This document discusses the WALD stack, a modern and sustainable analytics stack combining Snowflake, Airbyte, dbt, Lightdash, and optionally Streamlit. It provides an example of analyzing Formula 1 racing data using these tools, with Airbyte ingesting data into Snowflake, dbt for transformations, Lightdash for visualization, and dbt with Snowpark for machine learning predictions. The speaker argues the WALD stack is flexible for many use cases from analytics to full data products at scale.
Well thought-out inventory management processes can reduce costs and save significant time throughout your organization. In this presentation, Ultra provides best practices overview to streamline inventory, and the webinar showcases resources needed for manual processing. See how inventory workflows and processes can be improved with dedicated inventory systems.
This document contains the agenda and details for a company meeting. The agenda includes reviewing Q1 performance, discussing the Q2 plan, and reviewing various topics like access control sales, cable sales, marketing activities, training, and projects. For Q1, access control and cable sales targets were achieved. The Q2 plan includes access control and cable order targets. Marketing activities for Q2 include distribution cars, flyers, showcases and digital marketing. Top performing access control models and distributors for Q1 are identified. The Q2 plan also discusses potential new accounts, inventory levels, trainings and other key actions.
Splunk AI & Machine Learning Roundtable 2019 - ZurichSplunk
Splunk Artificial Intelligence and Machine Learning Roundtable held in Zurich on November 6th 2019. Presented by Philipp Drieger, Staff Machine Learning Architect.
The document outlines the agenda for a Salesforce event taking place in Gothenburg, Sweden. The agenda includes:
1. An introduction to Salesforce by Kjell Ahlzén, the Regional Vice President of Salesforce in Sweden.
2. A presentation on digitalization and innovation by My Lindström from Volvo Car Group.
3. A presentation on innovative cloud solutions by Allan Lorentzen and Elena Klepikova from Accenture.
4. A Salesforce demonstration by Lars Göransson from Salesforce.
5. A concluding question and answer session and networking opportunities.
The document discusses reporting options for the Oracle Eloqua marketing automation platform. It provides an overview of the current native reporting tools Insight and Analyzer, and details about the future state including the new Oracle Business Intelligence (OBI) tool. It also discusses taking data out of Eloqua through the bulk API or custom applications to do additional custom reporting and analytics.
SQL In Hadoop: Big Data Innovation Without the RiskInside Analysis
The Briefing Room with Dr. Robin Bloor and Actian
Live Webcast July 14, 2015
Watch the Archive: https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=bbd4395ea2f8c60a03cfefc68c7aa823
Innovation often implies risk, which is why businesses have many issues to weigh when considering change. Yet the remarkable growth of data is driving many traditional systems into the ground, forcing information workers to take a critical look at their existing tools. Technologies like Hadoop offer economical solutions to big data management, but to truly take advantage of its capabilities, organizations must modernize their infrastructure.
Register for this episode of The Briefing Room to learn from veteran Analyst Dr. Robin Bloor as he explains how and why organizations should improve legacy systems. He’ll be briefed by Todd Untrecht of Actian, who will tout his company’s Actian Vortex, a SQL-in-Hadoop solution. He will show how integrating a SQL engine directly in the Hadoop cluster can lead to faster analytics and greater control, while still maintaining existing investments.
Visit InsideAnalysis.com for more information.
This document discusses using big data analytics for traffic management. It describes capturing live traffic and accident data in a big data reservoir to analyze traffic congestion. The solution allows users to view, analyze, and act on real-time traffic data and provide alerts to save lives. It also simulates traffic scenarios to predict the impact of accidents.
Presentation of candidates for StartUp Pitch Contest "Unlocking the Value of Data in Logistics", powered by DB Schenker at #VivaTech, on 16th May 2019 in Paris.
SAP Database Platform, ASE & IoT RoadmapPaul Marriott
Paul Marriott presented on SAP's database platform roadmap and key topics including Sybase ASE, IoT, and HANA adoption. The presentation covered enhancements to Sybase ASE 16 including improved scalability, performance, security and manageability. It also discussed how digital transformation and the rise of IoT is driving new business models and the need for real-time analytics. Examples were given of how companies like John Deere, Harley Davidson, and Hamburg Port Authority are leveraging connected technologies.
EPSi was founded in 1999 with the goal of re-engineering decision support. Over the past 20 years we have grown our client base to over 950+ individual healthcare institutions across the United States and internationally. Our customers rely on our platform for the insights they need, including 15 of the top 20 U.S. News & World Best Hospitals; and, and, our experience in delivering world-class financial decision support and integrated performance management applications is unparalleled.
EPSi’s platform has always been highly scalable. We have installations in regional medical centers and community hospitals, as well as large health systems. This includes 128 Integrated Health System customers, among them Catholic Health Initiatives, a flagship EPSi customer and one of the nation's largest healthcare systems comprised of 108 acute care hospitals and over 11,000 beds. EPSi’s base also includes 40 very prestigious academic medical centers and 14 stand-alone pediatric hospitals using our software applications.
In addition to the above, EPSi continues our rich history of innovation with the launch of our new RealCost™ platform. Our vision for RealCost™ was catalyzed by the rapidly changing healthcare landscape with new reimbursement models, increasing cost of care and organizational consolidation; while available systems today do not offer the level of integration, precision, and timeliness required to optimize effective decision making.
RealCost™ changes all of this with a high performing, cloud-based solution encompassing specific application modules along with intuitive workflow and embedded analytics. One of the goals of RealCost™ is to predict upcoming cost variances so that you can avoid costs before they happen – thereby empowering healthcare organizations to move away from the traditional practice of month-end retrospective analysis and inefficient backend processes – in favor of real-time actions – to help drive more timely and effective decision making for streamlining operations and improving financial outcomes.
RealCost will supplement existing decision support applications – and in some cases replace specific decision support system functions entirely – like Cost Accounting, the first RealCost™ module released in 2018. Additional modules scheduled for release in 2019 include Rolling Forecast and Real Time Cost.
The document discusses Tableau and Alteryx data analytics platforms. It provides an overview of Alteryx, describing it as a self-service data analytics platform that allows users to analyze, enrich, prepare, blend, and share data using a visual workflow interface. The document also includes sections on Alteryx's market, demonstrations of its capabilities through use cases, reference customer cases, and a question and answer period.
Altilia Enterprise Data World 2014 PresentationMassimo Ruffolo
The presentation I will use at the enterprise Data World 2014 for introducing the MANTRA Smart Data Management Platform and the two products MANTRA Data Capture and Mantra Holistic Intelligence
EWS has undertaken several initiatives to improve its data analytics capabilities, mobile services, and development processes:
1) The data analytics initiative introduced a big data ecosystem focusing on descriptive, exploratory, inferential, predictive, causal, and mechanistic analytics using tools like Hadoop, Spark, and R. Specialized skills and technologies were acquired.
2) The mobility services initiative leveraged existing talent to implement cross-platform mobile apps using HTML5 while strengthening native and cross-platform skills. Tools for rapid mobile app development and AWS Mobile were also introduced.
3) The Agile/CI/CD initiative brought the organization into test-driven Agile development with continuous integration and delivery through training, documentation,
The document summarizes a program kickoff event for Tableau and Alteryx users. It included sessions on trends in self-service BI, Tableau enablement at a company, the Tableau roadmap, and using Alteryx for data flow control. About 200 professionals attended the event, which featured a recap session using the Sli.do platform to gather feedback. Trends discussed included digitalization, consumerization, mobility, cloud, and artificial intelligence. A survey showed that data discovery/self-service BI and data preparation/blending were top priorities.
Embedding Insight through Prediction Driven LogisticsDatabricks
Aggreko are a leading provider of temporary power and temperature control solutions, serving customers across the globe as they work on projects ranging from the Olympics to aiding humanitarian disaster relief. In this talk, Helena and Andy will discuss how the Insights team have developed scalable machine learning solutions to support the business. In particular they will discuss fuel consumption forecasts that have helped Aggreko’s fuel logistics teams improve customer service levels and reduce costs by becoming more proactive and insight driven.
The document outlines an agenda for the Manchester MuleSoft Meetup Group meeting. The agenda includes introductions of organizers, sponsors, and a new attendee poll. It then covers two main topics: API Specification Automation via Platform APIs and 7 Steps to Achieving Effective API Insights. Each topic includes a presentation and Q&A section. The document provides details on the speakers and their backgrounds. It concludes with announcements about Anypoint Studio and Anypoint Flex Gateway updates.
Bringing Velocity and Momentum to Digital Transformation ProjectsAcquia
If your digital transformation efforts feel like they are forever stuck in the planning stage, you are not alone. Drawing on lessons learned from high-velocity digital transformations for enterprise built on Drupal and Acquia, Ben Beath will bring to life a framework for delivering customer value in just 12 weeks.
This document discusses the WALD stack, a modern and sustainable analytics stack combining Snowflake, Airbyte, dbt, Lightdash, and optionally Streamlit. It provides an example of analyzing Formula 1 racing data using these tools, with Airbyte ingesting data into Snowflake, dbt for transformations, Lightdash for visualization, and dbt with Snowpark for machine learning predictions. The speaker argues the WALD stack is flexible for many use cases from analytics to full data products at scale.
Well thought-out inventory management processes can reduce costs and save significant time throughout your organization. In this presentation, Ultra provides best practices overview to streamline inventory, and the webinar showcases resources needed for manual processing. See how inventory workflows and processes can be improved with dedicated inventory systems.
This document contains the agenda and details for a company meeting. The agenda includes reviewing Q1 performance, discussing the Q2 plan, and reviewing various topics like access control sales, cable sales, marketing activities, training, and projects. For Q1, access control and cable sales targets were achieved. The Q2 plan includes access control and cable order targets. Marketing activities for Q2 include distribution cars, flyers, showcases and digital marketing. Top performing access control models and distributors for Q1 are identified. The Q2 plan also discusses potential new accounts, inventory levels, trainings and other key actions.
Splunk AI & Machine Learning Roundtable 2019 - ZurichSplunk
Splunk Artificial Intelligence and Machine Learning Roundtable held in Zurich on November 6th 2019. Presented by Philipp Drieger, Staff Machine Learning Architect.
The document outlines the agenda for a Salesforce event taking place in Gothenburg, Sweden. The agenda includes:
1. An introduction to Salesforce by Kjell Ahlzén, the Regional Vice President of Salesforce in Sweden.
2. A presentation on digitalization and innovation by My Lindström from Volvo Car Group.
3. A presentation on innovative cloud solutions by Allan Lorentzen and Elena Klepikova from Accenture.
4. A Salesforce demonstration by Lars Göransson from Salesforce.
5. A concluding question and answer session and networking opportunities.
Scraim - Online service for project management based on adaptable processes, to help standardize best practices, revolutionizing the implementation of international certifications.
The document outlines the agenda for a webinar series hosted by Cleantech Open. The webinar series provides mentorship and guidance to cleantech startups. The agenda lists the dates and topics that will be covered in the summer webinar program, including sessions on business models, markets, fundraising, and preparing for investor presentations. It also outlines the agenda for the September 11th national webinar, which will include a session on perfecting the startup pitch as well as an overview of the next steps in Cleantech Open's program.
This document summarizes the business strategy and operations of Nuvo Logistics Pvt Ltd. It discusses their goals of quick expansion through an asset-light model and focus on user experience. It provides an overview of their mobile app product and funding rounds. Key statistics on revenue, employees and funding are presented. The document also includes a SWOT analysis, discussion of competitors like BigBasket and Grofers, and proposed solutions to challenges like real-time inventory updates and cross-docking operations.
Ahead of the Stream: How to Future-Proof Real-Time AnalyticsInside Analysis
Business seems to move faster by the day, with the most cutting edge companies taking advantage of real-time data streams for heavy duty analytics. But with so much innovation happening in so many places, how can companies stay ahead of the game? One answer is to future-proof your analytics architecture by using an abstraction layer that can translate your business use-case or work-flow to one of many leading innovative technologies to address the growing number of use cases in this dynamic field.
Register for this episode of The Briefing Room to hear veteran Analyst Dr. Robin Bloor, as he explains how a data flow architecture can harness a wide range of streaming solutions. He'll be briefed by Anand Venugopal of Impetus Technologies, who will showcase his company's StreamAnalytix platform, which was designed from the ground up to leverage multiple major streaming engines available today, including Apache Spark, Apache Storm and others. He'll demonstrate how StreamAnalytix provides enterprise-class performance while incorporating best-of-breed open-source components.
View the archive at: https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=925d1e9b639b78c6cf76a1bbbf485b2b
Envisioning the Next Generation of AnalyticsLora Cecere
The presentation during a panel discussion at the Supply Chain Insights Global Summit in Scottsdale, AZ on September 10, 2014.
Envisioning the Next Generation of Analytics
Join this panel to hear case studies on new ways to use analytics and unleash the Art of the Possible. Gain new insights for the use of cognitive learning, concurrent optimization, and embracing new forms of data.
The panel included:
Facilitator: Lora Cecere, Founder and CEO of Supply Chain Insights
Dr. Mani Janakiram, Director of Supply Chain Strategy at Intel
Stephen N. Wagner, Global Supply Chain, Global Director, Network Design & Logistics Analytics at Schneider Electric
How to Build Business Forecasts With Microsoft Excel Using 10x the Data at 20...AtScale
Watch this presentation from the experts from SafeGraph and AtScale to learn how to turn Microsoft Excel into a crystal ball for your business forecasting - painlessly. You’ll learn how to:
combine your data with public or purchased data to enrich insights; build sophisticated time-relative analyses like period-to-date calculations; use Excel pivot tables against billions of data points for data exploration; and, build a model that will automatically refresh at the cell level.
And then you’ll be able to:
Understand the product mix and product level by store location
Model and forecast revenue and expenses
Use semi-additive measure for tracking inventory levels
Calculate per member per month KPIs
1 CS 170 ‐ Computer Applications for Business Fall .docxhoney725342
1
CS 170 ‐ Computer Applications for Business
Fall 2016 ‐ Assignment 6
Introduction to JavaScript
Due Date Before 11:00 PM - Friday, October 21st, 2016
Accept Until Before 11:00 PM - Friday, October 28th, 2016
Evaluation 15 points
Submit to Sakai Assignment6_answers.html file
To get credit for this assignment:
Upload and submit the Assignment6_answers.html file through Sakai.
Learning Objectives:
This assignment is designed to practice:
1. Basic understanding of JavaScript variables, including;
a The declaration, initialization and assignment processes
2. Obtain user input by via the prompt() function and present output to the user through
the alert() function
3. Data type conversion in variables (strings to numbers, convert to upper case)
4. Use of the conditional if and if/else statements
5. Use of arithmetic and logic operators
6. Use of comments
Directions:
You are provided an html program. Your responsibility is to insert the JavaScript statements
that will solve the problem discussed below, and to comment the html file with the
requested information per the requirements.
For the JavaScript, you will only complete the section inside of the <script> tags that are
located within the provided skeleton program:
<script id="COMPLETE_THIS_SECTION_ASSIGNMENT_6">
Insert your JavaScript code here
</script>
2
Problem to solve:
The Serendipity Booksellers has a book club that awards points to its customers based on the
number of books purchased each month. The points are awarded as follows:
If a customer purchases 0 books, they earn 0 points
If a customer purchases 1 book, they earn 3 points
If a customer purchases 2 books, they earn 7 points
If a customer purchases 3 books, they earn 12 points
If a customer purchases more than 3 books, they earn an additional 5 points on top of
the 12 points for each book above 3.
Preferred Customers receive a bonus of double award points.
The Serendipity Booksellers website needs to be updated to ask the customer to enter the
number of books purchased last month, confirm if they are a Preferred Customer, and then
calculate and display the number of award points earned.
Requirements:
For this assignment;
1. Your program will calculate the award points as described above.
2. You will generate HTML comments to add your name, section and TA name. Each on a
separate line within the <Head> tags. This will (should) NOT be visible in the document on
the web browser).
3. You will then add JavaScript code to the provided assignment6.html skeleton file within
the <script> tags:
<script id="COMPLETE_THIS_SECTION_ASSIGNMENT_6">
/* INSERT YOUR JAVASCRIPT HERE */
</script>
4. A typical program flow would declare the variables needed to solve the problem,
initialize the variables, solicit input, perform the data manipulation and/or calculations
and display the result.
5 ...
What is Value Stream Management and why do you need it?Tasktop
Agile has provided a framework for shortening iterations and adapting to ever changing requirements. DevOps established practices for automating the software delivery pipeline. While these methods are becoming standard practices in building software, scaling these concepts is problematic. That’s where Value Stream Management (VSM) comes in.
During this webinar, Senior VSM Strategist, Carmen DeArdo, discusses:
- What is Value Stream Management and why you need it
- How to architect your delivery pipeline for end-to-end flow and delivery speed
- Why moving from a project to product approach is critical to survive in the age of digital disruption
AI and Machine Learning for the Connected Home with Stephen GalsworthyDatabricks
Quby is the creator and provider of Toon, a leading European smart home platform. We enable Toon users to control and monitor their homes using both an in-home display and app. As a data driven company, we use AI and machine learning to generate actionable insights for our end users. Using the data we collect via our IoT devices we have introduced multiple data driven services, including an energy waste checker and a boiler monitoring service. In this talk, Stephen will describe how AI and machine learning are implemented on the Toon platform, and will show multiple AI use cases relating to the connected home. We’ll take a look at how Deep Learning algorithms are used to detect inefficient appliances from electricity meter data and how streaming algorithms allow users to be alerted to anomalies with their heating systems in near real-time. Stephen will share the experiences from the Data Science and Data Engineering teams at Quby with bringing data science algorithms from R&D to production and the lessons learned in offering multiple data driven services to hundreds of thousands of users on a daily basis.
The document provides guidance on how to create an effective pitch deck for funding. It outlines 11 steps to tell a compelling story: 1) Define the problem and solution, 2) Tell a story with a sample company, 3) Describe the market size and opportunity, 4) Explain how the solution solves customer problems, 5) Provide proof through testimonials and data, 6) Prove the business model and revenue streams, 7) Show the capable leadership team, 8) Address the competition, 9) Specify the financial requirements and use of funds, 10) Outline the roadmap, and 11) End with a clear call to action. The overall goal is to open the investor's mind to the vision and get them
The document appears to be a presentation by Splunk Inc. discussing their data platform. Some key points:
1. Splunk's platform allows customers to investigate, monitor, analyze and act on data from any source in real-time.
2. It addresses challenges of collecting and making sense of massive amounts of data from various systems and devices across IT, security, and IoT use cases.
3. Splunk provides solutions and services to help customers accelerate their data journey from initial investigation to taking action.
Similar to Alteryx and Tableau: Iron Mountain's Sherpa to business insight (20)
The Ipsos - AI - Monitor 2024 Report.pdfSocial Samosa
According to Ipsos AI Monitor's 2024 report, 65% Indians said that products and services using AI have profoundly changed their daily life in the past 3-5 years.
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeWalaa Eldin Moustafa
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake
Codeless Generative AI Pipelines
(GenAI with Milvus)
https://ml.dssconf.pl/user.html#!/lecture/DSSML24-041a/rate
Discover the potential of real-time streaming in the context of GenAI as we delve into the intricacies of Apache NiFi and its capabilities. Learn how this tool can significantly simplify the data engineering workflow for GenAI applications, allowing you to focus on the creative aspects rather than the technical complexities. I will guide you through practical examples and use cases, showing the impact of automation on prompt building. From data ingestion to transformation and delivery, witness how Apache NiFi streamlines the entire pipeline, ensuring a smooth and hassle-free experience.
Timothy Spann
https://www.youtube.com/@FLaNK-Stack
https://medium.com/@tspann
https://www.datainmotion.dev/
milvus, unstructured data, vector database, zilliz, cloud, vectors, python, deep learning, generative ai, genai, nifi, kafka, flink, streaming, iot, edge
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
State of Artificial intelligence Report 2023kuntobimo2016
Artificial intelligence (AI) is a multidisciplinary field of science and engineering whose goal is to create intelligent machines.
We believe that AI will be a force multiplier on technological progress in our increasingly digital, data-driven world. This is because everything around us today, ranging from culture to consumer products, is a product of intelligence.
The State of AI Report is now in its sixth year. Consider this report as a compilation of the most interesting things we’ve seen with a goal of triggering an informed conversation about the state of AI and its implication for the future.
We consider the following key dimensions in our report:
Research: Technology breakthroughs and their capabilities.
Industry: Areas of commercial application for AI and its business impact.
Politics: Regulation of AI, its economic implications and the evolving geopolitics of AI.
Safety: Identifying and mitigating catastrophic risks that highly-capable future AI systems could pose to us.
Predictions: What we believe will happen in the next 12 months and a 2022 performance review to keep us honest.
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...Aggregage
This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!
Global Situational Awareness of A.I. and where its headedvikram sood
You can see the future first in San Francisco.
Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there’s a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.
The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be un-leashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.
Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the wilful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.
Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.
Let me tell you what we see.
Predictably Improve Your B2B Tech Company's Performance by Leveraging DataKiwi Creative
Harness the power of AI-backed reports, benchmarking and data analysis to predict trends and detect anomalies in your marketing efforts.
Peter Caputa, CEO at Databox, reveals how you can discover the strategies and tools to increase your growth rate (and margins!).
From metrics to track to data habits to pick up, enhance your reporting for powerful insights to improve your B2B tech company's marketing.
- - -
This is the webinar recording from the June 2024 HubSpot User Group (HUG) for B2B Technology USA.
Watch the video recording at https://youtu.be/5vjwGfPN9lw
Sign up for future HUG events at https://events.hubspot.com/b2b-technology-usa/
End-to-end pipeline agility - Berlin Buzzwords 2024Lars Albertsson
We describe how we achieve high change agility in data engineering by eliminating the fear of breaking downstream data pipelines through end-to-end pipeline testing, and by using schema metaprogramming to safely eliminate boilerplate involved in changes that affect whole pipelines.
A quick poll on agility in changing pipelines from end to end indicated a huge span in capabilities. For the question "How long time does it take for all downstream pipelines to be adapted to an upstream change," the median response was 6 months, but some respondents could do it in less than a day. When quantitative data engineering differences between the best and worst are measured, the span is often 100x-1000x, sometimes even more.
A long time ago, we suffered at Spotify from fear of changing pipelines due to not knowing what the impact might be downstream. We made plans for a technical solution to test pipelines end-to-end to mitigate that fear, but the effort failed for cultural reasons. We eventually solved this challenge, but in a different context. In this presentation we will describe how we test full pipelines effectively by manipulating workflow orchestration, which enables us to make changes in pipelines without fear of breaking downstream.
Making schema changes that affect many jobs also involves a lot of toil and boilerplate. Using schema-on-read mitigates some of it, but has drawbacks since it makes it more difficult to detect errors early. We will describe how we have rejected this tradeoff by applying schema metaprogramming, eliminating boilerplate but keeping the protection of static typing, thereby further improving agility to quickly modify data pipelines without fear.
End-to-end pipeline agility - Berlin Buzzwords 2024
Alteryx and Tableau: Iron Mountain's Sherpa to business insight
1. # A L T E R Y X E U 1 9
PRESENTED BY
David Turley
Analytics Consultant
InterWorks
ALTERYX: IRON
MOUNTAIN’S SHERPA
TO BUSINESS INSIGHT
Matt Semple
FP&A Director
Iron Mountain
msemple@ironmountain.co.uk david.turley@interworks.co.uk
2. # A L T E R Y X E U 1 9 2
With Alteryx, I can dream big!!!
MATT
SEMPLE
When I use Alteryx, I feel in control of
my data and fully confident I can deliver
insightful analysis…
A L T E R Y X U S E R S I N C E ( 2 0 1 4 )
3. # A L T E R Y X E U 1 9 3
With Alteryx, I can…fix my clients’ data!!
DAVID
TURLEY
When I use Alteryx, I feel…
Free… ‘like a candy wrapper caught in an
updraft’ – Homer Simpson
A L T E R Y X U S E R S I N C E ( 2 0 1 6 )
4. # A L T E R Y X E U 1 9 4
TODAY’S
AGENDA
1. You’ll learn about Iron
Mountain’s business
model and its specific
analytical
requirements
2. You’ll hear about Iron
Mountain’s journey from a
‘data rich / insight poor’
organisation to one that delivers
advanced insights to all
levels of management
3. You’ll see demonstrations of
how Alteryx is integral to the
new insights delivered for
Commercial, Real
Estate & Financial
performance
4. You’ll gain an understanding
of how Iron Mountain &
InterWorks partner for
analytical success
5. # A L T E R Y X E U 1 9
IRON MOUNTAIN – INTRO
5
26,000 EMPLOYEES
≈50 COUNTRIES
225,000+ CUSTOMERS
GLOBAL LEADER IN RECORDS & INFORMATION MANAGEMENT
$4.2 BILLION REVENUE
700 million
cubic feet of hardcopy records
89 million
pieces of media stored
1.2 billion
images scanned annually
1,450+
facilities worldwide
11
data centres
6. # A L T E R Y X E U 1 9
Pennsylvania London
Singapore
Sydney
IRON MOUNTAIN
WORLDWIDE
6
Rio de Janeiro
7. # A L T E R Y X E U 1 9
LONG TERM
PARTNERSHIPS
WE NEGOTIATE DEALS TO
SAFELY STORE AND
MANAGE THE CRITICAL
ASSETS OF OUR
CUSTOMERS
SIMPLIFIED BUSINESS MODEL
7
WE BUILD OR RENT A SAFE & SECURE
STORAGE WAREHOUSE
WE INSTALL STORAGE
RACKING SOLUTIONS
WE HELP CUSTOMERS
MANAGE THEIR
INFORMATION LIFE CYCLES
INCLUDING SECURE
DESTRUCTION
Note: Iron Mountain archiving boxes referred to as Cube or CuFt (Cubic Feet)
8. # A L T E R Y X E U 1 9
RETURNS ON INVESTMENT
SIGNIFICANT REAL ESTATE & CAPITAL INVESTMENTS
8
Durable long-term business model
Strong cashflow generation
Time
Cumulative
Cashflow
Indicative figures only
9. # A L T E R Y X E U 1 9
THE ANALYTICS WE REQUIRE
9
COMMERCIAL REAL ESTATE
What are the current capacity
utilisation rates by facility / market?
Where do we need to invest in new
space based on commercial demand?
How do we best respond to changes
in customer volume and other
commercial trends?
FINANCIALS
Are we hitting our Budget targets?
Are we driving improved margins
and enhancing shareholder value?
Which are the most profitable
product lines in our portfolio?
Can we get early visibility to areas
of financial risk & opportunity?
1 2 3
Is our demand generation engine
effective?
How well are we selling?
Is our sales pipeline healthy enough to
drive achievement of growth targets
Can we improve our win rates?
10. # A L T E R Y X E U 1 9
OUR ANALYTICS JOURNEY
STAGE 1: ‘FINDING
ALTERYX’
10
11. # A L T E R Y X E U 1 9
COMMERCIAL
IMPROVEMENT OBSESSION
PASSION / OBSESSION
11
• Evaluate Tableau Salesforce connector
Prohibitively long refresh time, limited data prep
• Evaluate various Salesforce data download
tools (Dataloader.io, Jitterbit)
Limited functionality, no E-T-L capability
• Took a trial version of Alteryx, set up the
Salesforce connectors and started to build
workflow
FIRST STEPS
1. How can I capture historic pipeline trends
from a ‘point in time’ system (Salesforce)
2. How can I create better reporting than this…
Perfect fit, connectivity plus full suite of
analytical tools, no data limits
12. # A L T E R Y X E U 1 9
OUR ANALYTICS JOURNEY
STAGE 2: ‘PROBLEM
SOLVING’
12
13. # A L T E R Y X E U 1 9
THE SALESFORCE
CONNECTOR
13
INPUT YOUR
SALESFORCE LOGIN
THEN CONNECT TO
THE SALESFORCE
DATA TABLES YOU
REQUIRE FOR YOUR
WORKFLOW
14. # A L T E R Y X E U 1 9
BUILDING THE DATASET
- IRON MOUNTAIN EXAMPLE
14
Alteryx
Commercial
Workflow
Key Salesforce Tables
Opportunity
1m records
Account
1m records
Opportunity Line Item
4m records
Opportunity History
7m records
Opportunity Field History
2m records
User
10k records
Tableau visualisations
15. # A L T E R Y X E U 1 9
SOLVING THE PIPELINE
CONUNDRUM
15
Finding a way to “create” a sales pipeline history from a ‘point in time’ system
Opportunity
1m records
Append: List of Week Ending dates for last 10+ years
Expanded
Opportunity
‘by all weeks’
table
520m records
Filter out
• Weeks before opportunity created
Framework to build
out accurate
weekly history for
each opportunity
~150m records
16. # A L T E R Y X E U 1 9
OUR ANALYTICS JOURNEY
STAGE 3:
‘PARTNERSHIP’
16
17. # A L T E R Y X E U 1 9
DELIVERING COMMERCIAL
PERFORMANCE INSIGHTS
17
PIPELINE
HEALTH
Age of sales
opportunities &
velocity
through sales
stages
DEMAND
GENERATION
Growth in sales
pipeline over
previous
1, 13, 52 weeks
SALES
FORECASTING
Full year
projections based
on latest pipeline
& close rates
WIN
CONVERSION
Overall win rates
& close rates
from each sales
stage
PIPELINE
COVERAGE
Current pipeline
size measured
against annual
sales target
18. # A L T E R Y X E U 1 9
GROSS DEMAND GENERATION
18
Design brief: How to use Alteryx to power new leading indicator of future sales health
Worked example
What is the annual target
for Salesperson A?
100k Cubic Feet
What is their historic Win
Rate for this product line?
20%
How much pipeline do
they require to hit target?
500k CuFt (100k / 20%)
TARGET
‘Par’
ACTUAL
GDG
% of
Target
Weekly
Last 1 Week
10k
CuFt
5k
CuFt
50%
Quarterly
Last 13 Weeks
125k
CuFt
150k
CuFt
120%
Annual
Last 52 Weeks
500k
CuFt
450k
CuFt
90%
19. # A L T E R Y X E U 1 9
Requirements:
Current view of sales
pipeline by sales stage
Historic Close Rate by sales
stage for each individual
salesperson
Output:
Weighted sales forecast by
salesperson / country /
region
SALES FORECASTING
19
Worked Example:
Current view of Sales Pipeline opportunities won or expected to be won in FY19
Total
Value
Close
Rate
FY19
Forecast
Stage 1
Qualification
30k 10% 3k
Stage 2
Solution
Developed
15k 25% 4k
Stage 3
Solution
Agreed
15k 50% 8k
Stage 4
Negotiate
25k 70% 18k
Stages
5 to 7
Won
20k 100% 20k
105k - 52k
Booked Date / Expected Close Date
Jan’19
Pipeline
Stage
Progression
Wins
5k
10k
3k
2k
5k
4k
3k
6k
2k
5k
10k
5k
=
x
Current
Week Dec’19
=
x
=
x
=
x
5k
3k
4k
3k
12k
5k
10k
3k
=
x
Current
Forecast
for expected
Full Year Wins
Design brief: How to use Alteryx to power advanced analytics into future sales performance
20. # A L T E R Y X E U 1 9
WHAT'S INVOLVED
20
• Data Recap
• History of all sales opportunities including
progress through sales stages
• Building key calculations
• Close rates by sales stage, Win rate
21. # A L T E R Y X E U 1 9
STEP BY STEP
21
Filtering to relevant
Stage Data
22. # A L T E R Y X E U 1 9
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Regional Leadership Regional Support Country Leadership Country Sales Management Country Support
80%
100%
89% 90% 88%
22
END USER DASHBOARD
ACTIVE PARTICIPATION RATES
% of users viewing Commercial dashboard within last 30 days
# users: 20 # users: 50 # users: 30 # users: 60 # users: 40
EXPECTATION
ACTUAL RESULTS
Total # users: 200
23. # A L T E R Y X E U 1 9 23
CURRENT COMMERCIAL
PERFORMANCE
GDG % OF PAR
In last 52 weeks we’ve exceeded
our target (above par) for adding
new sales opportunities to the
pipeline
(Gross Demand Generation)
109%
YTD WINS %
After 8 months of the year, we’re
well ahead of our wins target for
the Year to Date & on course for
a record sales year
(% Quota achievement)
151%
YTD WINS VS LY
Our wins performance in first 8
months of 2019 is significantly
higher than the wins recorded in
same 8 months of 2018
(Year on Year Sales Growth)
+73%
24. # A L T E R Y X E U 1 9
OUR ANALYTICS JOURNEY
STAGE 4: ‘PRODUCTION’
24
25. # A L T E R Y X E U 1 9 25
Using Google Map API and Spatial Tools to group storage
facilities based on where they are located in the world
GROUPING DATA BY LOCATION
REAL ESTATE:
LOCATION
INTELLIGENCE
26. # A L T E R Y X E U 1 9
WHY DO IT?
26
• 1,500 Storage Facilities located throughout the world
• We need to be able to:-
• Have capacity in the right locations to meet client’s storage requirements
• Ensure utilisation of all facilities is high, to maximise investment returns
• To ensure that we can:-
• Continue to serve our customer base (existing and new)
• Take the right decisions on where to grow or rationalise our real estate portfolio
27. # A L T E R Y X E U 1 9
REAL ESTATE ANALYTICS
27
Note:
commercially
sensitive data
redacted from the
dashboard view
shown here
28. # A L T E R Y X E U 1 9
WHAT'S INVOLVED
28
Data set with the address of each of the facilities
1. Google API Connector
• Coordination points of each of the Facilities
2. Spatial Tools
• To group facilities based on location and distance
from each other
29. # A L T E R Y X E U 1 9
1. FACILITY COORDINATES
29
Aim: Use the Google API connector to file coordinates of facilities
Output file
with Latitude /
Longitude
30. # A L T E R Y X E U 1 9
2. SPATIAL GROUPING
30
Aim: Group Facilities in a 10 Mile radius
1. Create Points
4. Make Group
3. Spatial Match
2. Trade Area
31. # A L T E R Y X E U 1 9
SPATIAL GROUPING
31
Aim: Group Facilities in a 10 Mile radius
32. # A L T E R Y X E U 1 9 32
OUR ANALYTICS JOURNEY
STAGE 5: ‘FINAL ASCENT’
33. # A L T E R Y X E U 1 9
DEMAND MODELLING
33
REAL ESTATE CAPACITY BY MARKET + COMMERCIAL SALES FORECAST BY MARKET
Current pipeline opportunities by location by market
We know our Real Estate capacity status by facility and
market
We know where our new commercial opportunities exist
and have an algorithmic prediction of how much we are
likely to win and when
Output: Demand Model by market
MARKET
SPARE
CAPACITY
TOTAL
SALES
PIPELINE
WEIGHTED
SALES
PIPELINE
Q4’19
FC
WINS
Q1’20
FC
WINS
Q2’20
FC
WINS
Q3’20
FC
WINS
Q4’20
FC
WINS
Warsaw xxxx xxxxx xxxx xx xx xx xx xx
Krakow xxxx xxxxx xxxx xx xx xx xx xx
Gdansk xxxx xxxxx xxxx xx xx xx xx xx
…..
Sales demand covered by spare capacity
Warning: additional capacity required
Indicative example only
34. # A L T E R Y X E U 1 9
STAGE 5: FINAL ASCENT?
34
• DELIVER INTEGRATED ANALYTICS PLATFORM
• EMBRACE NEW TECHNOLOGY & TECHNOLOGY CHANGES
• SET THE NEXT CHALLENGE
• CONTINUE THE JOURNEY
35. # A L T E R Y X E U 1 9 35
Thanks for your time today and listening to Iron Mountain’s analytics
journey. Almost anything is possible with a clear plan, the right tools,
expert assistance and the passion to deliver new insights!!
GOOD LUCK ON YOUR DATA JOURNEY
FIVE KEY
POINTS
Alteryx can deliver the content
you need to deliver insights to
business leaders
Have a clear vision of where
you want to go on the analytics
journey for your company
Be prepared for obstacles,
delays and setbacks but keep
faith in yourself and the tools
Partner wisely to accelerate the
delivery of your advanced
insights to the business
Delight your customers! Seek
regular feedback and refine your
journey plans accordingly
1
2
4
5
3
36. # A L T E R Y X E U 1 9
THANK
YOU
msemple@ironmountain.co.uk
36
(44) 207-939-1650
www.ironmountain.com
MATT SEMPLE
david.turley@interworks.co.uk
(44) 203-137-2233
www.interworks.com
DAVID TURLEY
37. # A L T E R Y X E U 1 9
COMPLETE
SESSION SURVEYS
ATTENTION
37
We want your feedback! Be sure to complete session surveys
within the mobile app after this session.
Surveys are anonymous, and we rely on your opinion for
improvement
Editor's Notes
Welcome to your template. Please follow the predesigned slides and use our presentation tips to make the most of your information. Custom slides and your corporate template are discouraged. Include presentation title, name and contact details here. Logo can be placed on each slide.
This is your intro slide. Please fill in the year you started using Alteryx. Follow the instructions in the red text on the slide and delete the once you are done.
This is your intro slide. Please fill in the year you started using Alteryx. Follow the instructions in the red text on the slide and delete the once you are done.
This slide is great for: screenshots, workflows, meaningful quotes to drive a point home, or any images with impact.
This slide is great for: screenshots, workflows, meaningful quotes to drive a point home, or any images with impact.
This slide is great for: screenshots, workflows, meaningful quotes to drive a point home, or any images with impact.
This slide is great for: screenshots, workflows, meaningful quotes to drive a point home, or any images with impact.
Use this as an alternate way to compare up to (3) items. All of the text and graphic boxes on this slide are editable/removable. Should your list be shorter than (3) items, simply delete the text and graphics that do not apply.
For each opportunity – As it is a live opportunity, we have a track of it through the whole process. So we have the timeline of the each opportunity of each point of the process, this means we can calculated the likelihood of a close, at each stage of the business
Use this slide for any data you would like to plot on a bar chart if you have more than 4 categories. To edit your data double click the pie and select “edit data” from the menu bar.
Use this to break up your presentation into sections. Consider this your jump slide to launch into your next point.
What we are trying to do here
What we are trying to do here
What we are trying to do here
This slide is great for: screenshots, workflows, meaningful quotes to drive a point home, or any images with impact.
Use this slide to summarize your key points/takeaways for your audience. The (5) item list and corresponding graphic boxes are editable. Should you want to summarize a smaller number of key takeaways, simply delete the extra text/boxes and change your slide header to reflect the number of items.
Close this out with your contact details. Attendees would love to engage on your subject.