We have worked with 40+ universities in the UK, Australia, and NZ to help them with their Data & Analytics needs. We have leveraged this experience to create an admissions dashboard that allows university stakeholders to track applications throughout the admissions cycle.
Join Peter Hopwood, as he demonstrates the admissions dashboard and describes the process required to bring together the relevant data to build such a dashboard for your university.
John Dowd - Lock Stock and Two Smoking Barrelssconul
SCONUL Conference 20-21 June 2013
Workshop - Lock Stock and Two Smoking Barrels: LMS outsourcing & organisational impact, with John Dowd, Assistant Director, Planning and Business Development, Learning and Information Services, University of Wolverhampton
The document provides an overview and analysis of machine learning, data mining, and decision support courses available online. It categorizes the courses based on intended audience (computer science students, managers, IT professionals) and provider (universities, commercial organizations). The document also discusses the characteristics of courses within and between categories, and provides examples of specific courses. It concludes with a review of efforts to increase awareness and education around data mining and decision support through the development of seminars, workshops and distance learning activities.
The document discusses the Texas STaR Chart, which is used by Texas teachers to rate their own performance and their school's performance in four key areas: teaching and learning, educator preparation, leadership and support, and technology infrastructure. It then provides the results from Bear Branch Junior High's 2007-2008 STaR Chart, noting their strength was in technology infrastructure while areas for improvement included professional development, teaching and learning, and support.
This document is a resume for Susan Hoddinott summarizing her qualifications and experience. She has extensive experience as an IT consultant working for various private companies and government organizations. She has an LLB from Murdoch University, an MBA from UWA, and a Bachelor of Science with Honors in psychology from UWA. Currently she is a law student and volunteer researcher who also holds roles in several professional and political organizations.
Research information management: making sense of it allDigital Science
"Research information management: making sense of it all" - Julia Hawks, VP North America, Symplectic
Slides from Shaking It Up: Challenges and Solutions in Scholarly Information Management, San Francisco, April 22, 2015
Creating Interactive Dashboards with Microsoft ExcelAACRAO
Sign up to view the archived webinar here: http://www.aacrao.org/conferences/conferences-detail-view/creating-interactive-dashboards-in-excel
Other college’s dashboards making you see green even though it is not your school color? No budget for specialized dashboard programs? Can’t keep up with end-user demands for different analyses?
New features in Excel 2010 and 2013 allow even casual users to create interactive dashboards that are both functional and great looking allowing you and your end-users to explore your data in ways you have only imagined—allowing you to convert your data into actionable information.
Even if you are a Pivot Table novice, you can create functional and great looking dashboards. In this webinar, we will show you the basic steps for creating interactive dashboards in Excel 2010 and 2013. Taking a holistic SEM approach, we will examine several use-cases throughout the student lifecycle.
From setting up your data, to creating the dashboard and modifying it to your own school colors, we will cover the basics of setting up a simple, yet interactive and informative dashboards. Some basic knowledge of Pivot Tables is useful but not required.
R. Brendan Aldrich, Executive Director of Data Warehousing at City Colleges of Chicago, discussed moving from a data dictatorship or aristocracy model to a data democracy model where all employees have access to data. This involves providing interactive reporting instead of static reports, using dynamic data environments tailored to user roles, integrated training and data dictionaries, and rethinking expensive licensing models. The City Colleges of Chicago is taking these approaches using a custom system built by Zogotech on Microsoft SQL Server to empower its over 5,800 employees and 120,000 students.
This presentation was provided by Rachel Lewellen of Harvard University during the NISO event, Assessment Practices and Metrics in the 21st Century Training Session Four held on Friday, November 9th.
John Dowd - Lock Stock and Two Smoking Barrelssconul
SCONUL Conference 20-21 June 2013
Workshop - Lock Stock and Two Smoking Barrels: LMS outsourcing & organisational impact, with John Dowd, Assistant Director, Planning and Business Development, Learning and Information Services, University of Wolverhampton
The document provides an overview and analysis of machine learning, data mining, and decision support courses available online. It categorizes the courses based on intended audience (computer science students, managers, IT professionals) and provider (universities, commercial organizations). The document also discusses the characteristics of courses within and between categories, and provides examples of specific courses. It concludes with a review of efforts to increase awareness and education around data mining and decision support through the development of seminars, workshops and distance learning activities.
The document discusses the Texas STaR Chart, which is used by Texas teachers to rate their own performance and their school's performance in four key areas: teaching and learning, educator preparation, leadership and support, and technology infrastructure. It then provides the results from Bear Branch Junior High's 2007-2008 STaR Chart, noting their strength was in technology infrastructure while areas for improvement included professional development, teaching and learning, and support.
This document is a resume for Susan Hoddinott summarizing her qualifications and experience. She has extensive experience as an IT consultant working for various private companies and government organizations. She has an LLB from Murdoch University, an MBA from UWA, and a Bachelor of Science with Honors in psychology from UWA. Currently she is a law student and volunteer researcher who also holds roles in several professional and political organizations.
Research information management: making sense of it allDigital Science
"Research information management: making sense of it all" - Julia Hawks, VP North America, Symplectic
Slides from Shaking It Up: Challenges and Solutions in Scholarly Information Management, San Francisco, April 22, 2015
Creating Interactive Dashboards with Microsoft ExcelAACRAO
Sign up to view the archived webinar here: http://www.aacrao.org/conferences/conferences-detail-view/creating-interactive-dashboards-in-excel
Other college’s dashboards making you see green even though it is not your school color? No budget for specialized dashboard programs? Can’t keep up with end-user demands for different analyses?
New features in Excel 2010 and 2013 allow even casual users to create interactive dashboards that are both functional and great looking allowing you and your end-users to explore your data in ways you have only imagined—allowing you to convert your data into actionable information.
Even if you are a Pivot Table novice, you can create functional and great looking dashboards. In this webinar, we will show you the basic steps for creating interactive dashboards in Excel 2010 and 2013. Taking a holistic SEM approach, we will examine several use-cases throughout the student lifecycle.
From setting up your data, to creating the dashboard and modifying it to your own school colors, we will cover the basics of setting up a simple, yet interactive and informative dashboards. Some basic knowledge of Pivot Tables is useful but not required.
R. Brendan Aldrich, Executive Director of Data Warehousing at City Colleges of Chicago, discussed moving from a data dictatorship or aristocracy model to a data democracy model where all employees have access to data. This involves providing interactive reporting instead of static reports, using dynamic data environments tailored to user roles, integrated training and data dictionaries, and rethinking expensive licensing models. The City Colleges of Chicago is taking these approaches using a custom system built by Zogotech on Microsoft SQL Server to empower its over 5,800 employees and 120,000 students.
This presentation was provided by Rachel Lewellen of Harvard University during the NISO event, Assessment Practices and Metrics in the 21st Century Training Session Four held on Friday, November 9th.
Open Data Initiatives – Empowering Students to Make More Informed Choices? - ...Terminalfour
Are the developments in the HEFCE and JISC XCRI XML standards finally giving students the information they need to compare one university against the other? By standardising the output of content about courses, results and post graduation success in the job market, are students better positioned to evaluate the right University for them. This presentation will answer this question and discuss how universities can utilize Web Content Management to deliver on the demands of these standards and maximise student engagement.
This document provides an overview of a presentation about business intelligence (BI) and the software InfoManager. The presentation covers the challenges companies face in providing timely information to meet business goals, and how BI solutions can help aggregate and deliver information to users. It includes an agenda that outlines foundational information, discussing BI solutions from InfoManager that are either software as a service or on-premise. The presentation demonstrates InfoManager's capabilities like dashboards, drilling down into data, exception reporting, and exporting reports to Excel. It also discusses best practices for BI adoption and how InfoManager can help more types of users access information.
Pam Muth and Lisa Bolton: Optimising QILT to improve the student experienceStudiosity.com
The document discusses optimizing the Quality Indicators for Learning and Teaching (QILT) program to improve the student experience. QILT administers the Student Experience Survey (SES) and Graduate Outcomes Survey (GOS) to measure student engagement, teaching quality, and graduate employment outcomes. The SES collects data from current students on their educational experience. Results are available on the QILT website to allow students to compare institutions. Institutions receive detailed SES results and can integrate QILT data into strategic planning to monitor performance indicators over time. Customizing QILT surveys allows institutions to address questions not covered and better evaluate specific strategic initiatives.
Emerging Services for Research Informatio Management (RIM) through Enterprise...OCLC
This document discusses research information management (RIM) systems in universities. RIM systems integrate information about a university's researchers and their scholarly outputs. The primary uses of RIM systems are to facilitate faculty reporting, integrate with institutional repositories, enable benchmarking and reporting, and create public profiles of researcher expertise. RIM systems draw data from internal university sources like human resources systems and external sources like publication databases. They support collaboration between various university departments and partners like libraries. Common RIM uses seen in case studies of universities include faculty activity reporting, integrating with institutional repositories, creating public researcher profiles, and compiling reports.
The Sixty Minute (Data Dashboard) Makeover!Marieke Guy
Workshop run at the Institutional Web Management Workshop (IWMW) 2017 at Univeristy of kent, Tuesday 11th July 2017. Facilitated with Jon Rathmill, University of kent
How to start an online school budget and staffingAndrew Saint
This document discusses funding and budgeting considerations for starting an online school. It covers sources of funding such as state funding, grants, tuition/fees and donations. The budget sections outlines operational costs including staffing, instruction/curriculum/testing, technology, and professional services. Staffing considerations include personnel, salaries, and professional development. The document provides details on specific budget and staffing areas like curriculum, technology, operations, and other expenses.
This document discusses the importance of libraries using data and metrics to inform decision making and communicate their value. It notes that while librarians are good at collecting statistics, they often lack the ability or willingness to analyze, interpret, and apply the data. Without using data to take action or inform strategies, it has little value beyond justifying budgets. The document provides examples of how libraries can select peer institutions for benchmarking, analyze trends over time, and use multiple data sets to understand user needs and behaviors. It emphasizes telling "stories" combined with data ("Stories + Stats") to communicate effectively with stakeholders.
Lifecycle Integration with the University of KentuckySalesforce.org
Presentation from Salesforce.org Higher Ed Summit 2018 by: Tyler Gayheart, Office of Strategic Communication.
The University of Kentucky is embarking on a lifecycle enterprise approach to our digital and constituency relationship management (CRM) by way of a Enterprise Level Agreement (ELA) with Salesforce.org with the intention to deploy Salesforce for prospect, current student, alumni and donor operations carrying out over a multi-year period. This session will cover the process for planning, acquiring and building a lifecycle approach to deploying Salesforce across the enterprise at the University of Kentucky. An overview of activities will be shared from the completed phases of the project and speak to how the institutions plans to transform the way they engage prospects, current students, donors, alumni of the University.
Watch a recording of this presentation: https://youtu.be/8vKmN0oyIDM
A CRIS (Current Research Information System) is used to manage an institution's research information and outputs. It acts as an academic CV for the whole institution. A CRIS integrates data from various systems, allows complex workflows, and provides services for researchers and administrators. It covers the full research lifecycle from funding to publications to impact. Content is standardized, connected, and can be analyzed, reused for various purposes, and transported to external systems. A CRIS aims to provide a single point of access to showcase an institution's research capabilities.
The document discusses gaining business intelligence from user activity data in libraries and higher education institutions. It outlines challenges in collecting and analyzing comprehensive user data from different systems. The Open University perspective is that most students do not visit physical libraries and sign up for individual courses rather than degrees. However, the university has significant online user traffic that could provide insights if integrated across various learning and library systems. Overcoming cultural, technical, and data challenges will be key to developing a comprehensive view of user activity data.
Lifecycle Integration with the University of KentuckyTyler Gayheart
This document summarizes the University of Kentucky's implementation of Salesforce across multiple phases to integrate lifecycle data and improve recruitment, enrollment, alumni engagement, and philanthropic operations. Some key points:
- UK conducted a market study and chose Salesforce for its flexibility and because it could integrate across existing systems.
- Phase 1 focused on recruitment and included building out email marketing. It is on track to complete in April 2018.
- Future phases will address graduate admissions and alumni/donor relationships.
- Over 111 users are active now after moving from separate CRM systems to a centralized Salesforce model.
- Integration of data from various sources like applications and transcripts is underway.
-
This document provides information about Haluk Demirkan's background and experience. It summarizes his educational and professional qualifications, including over 10 years of research and higher education experience, as well as over 15 years of consulting and executive education experience. It also lists some of his academic accomplishments such as over 150 publications and research funded by several major companies. Finally, it provides details on some of the education topics he teaches related to services, information technology, and project management.
The document discusses national learning analytics in the UK and Jisc's role in providing learning analytics services. It describes Jisc's learning analytics tools and products like the Data Explorer dashboards, Study Goal app, and Learning Data Hub. It outlines Jisc's onboarding process for institutions and examples of how they are working with universities and colleges to implement learning analytics.
This document discusses the vision and strategic priorities of consolidating information systems at a university under a single entity called "One I.S.". It identifies challenges such as multiple disjointed systems and a lack of coordination. The strategic priorities are outlined as creating a single administration system, unified teaching and learning ecosystem, and unified research computing. The document discusses how centralizing services can help realize economies of scale, reduce costs, and mitigate risks. It provides comparisons to other universities and outlines changes to organizational structure, planning processes, and projects to work towards the "One I.S." vision.
This document summarizes the results of a needs assessment survey conducted by UNC Greensboro Library to understand faculty research data management practices and needs. The survey found that the top research data formats were text, PDFs, and spreadsheets. Most faculty backed up their data to external drives but not automatically. Three quarters of respondents did not anticipate sharing their data. The greatest needs identified were assistance with storage, backup, and meeting data sharing requirements. The library collaborated with campus partners to address these needs through new storage services, training, and guidance on developing data management plans.
This document provides an overview of analytics for learning and discusses implementation at GRCC. It begins with definitions of analytics, business intelligence, academic analytics, and learning analytics. It then discusses GRCC's strategic needs in areas like access to data, early alert systems, and measuring outcomes. The document outlines GRCC's analytics implementation, including hiring a data warehouse architect and campus training. It shows sample student and instructor reports in Blackboard Analytics and discusses next steps like dedicating time, building capacity, and engaging culture. It provides additional analytics resources.
Open data in ubi systems research data management plan (part 4)Heli Väätäjä
This slideset motivates to creating a data management plan and gives initial advice. Slides are from the seminar on Open Data in Ubiquitous Systems Research aimed for doctoral students in HCI and CS.
Defining the Libraries' Role in Research: A Needs Assessment Case StudyKathryn Crowe
This document summarizes the results of a needs assessment survey conducted at UNC Greensboro to understand faculty research data management needs. Key findings include: the most common data formats are text, PDFs, and spreadsheets; most faculty back up data themselves but do not follow best practices; the top priorities for support are storage/backup, meeting sharing requirements, and assistance with data management plans. Barriers to sharing include large data sizes and lack of knowledge about requirements and options. The survey informed new research data services from the libraries and other campus units, including data storage, curation, and consultation on data management plans and sharing requirements.
BbWorld 2013 - Learning Analytics: A Journey to Implementationekunnen
The document discusses Grand Rapids Community College's implementation of a learning analytics program. It provides background on the college and outlines their session agenda. It then defines analytics and discusses where relevant data is stored. The rest of the document outlines GRCC's strategic focus areas for analytics like student success, early alert systems, and course quality. It discusses their implementation process, future goals of building capacity and engaging faculty, and provides examples of analytics reports on topics like login tracking, course sizes, and grade comparisons.
This document discusses learning analytics and the potential uses of various institutional data sources. It describes how combining data from student records, the virtual learning environment (VLE), library usage, attendance records, and other sources through a learning analytics service could help improve student retention and attainment, enhance teaching quality, enable personalized learning, and support student health and well-being. Specific opportunities mentioned include predicting at-risk students, analyzing factors related to student success and employability, and using activity data to support timely interventions. Engaging various stakeholders like students, teachers, and campus planners is presented as important for effective use of learning analytics.
Altis Webinar: Use Cases For The Modern Data PlatformAltis Consulting
This document discusses use cases for a modern data platform. It begins by outlining the agenda, then provides background on Altis, the consulting firm. The document defines a modern data platform and explains how it differs from traditional setups. It discusses three approaches for selecting initial use cases: lift and shift with a twist, hitting a roadmap milestone, and supporting an organizational strategy. Examples are provided of where each approach has worked and struggled. The document covers design patterns, managing costs, and identifying success criteria for use cases.
Open Data Initiatives – Empowering Students to Make More Informed Choices? - ...Terminalfour
Are the developments in the HEFCE and JISC XCRI XML standards finally giving students the information they need to compare one university against the other? By standardising the output of content about courses, results and post graduation success in the job market, are students better positioned to evaluate the right University for them. This presentation will answer this question and discuss how universities can utilize Web Content Management to deliver on the demands of these standards and maximise student engagement.
This document provides an overview of a presentation about business intelligence (BI) and the software InfoManager. The presentation covers the challenges companies face in providing timely information to meet business goals, and how BI solutions can help aggregate and deliver information to users. It includes an agenda that outlines foundational information, discussing BI solutions from InfoManager that are either software as a service or on-premise. The presentation demonstrates InfoManager's capabilities like dashboards, drilling down into data, exception reporting, and exporting reports to Excel. It also discusses best practices for BI adoption and how InfoManager can help more types of users access information.
Pam Muth and Lisa Bolton: Optimising QILT to improve the student experienceStudiosity.com
The document discusses optimizing the Quality Indicators for Learning and Teaching (QILT) program to improve the student experience. QILT administers the Student Experience Survey (SES) and Graduate Outcomes Survey (GOS) to measure student engagement, teaching quality, and graduate employment outcomes. The SES collects data from current students on their educational experience. Results are available on the QILT website to allow students to compare institutions. Institutions receive detailed SES results and can integrate QILT data into strategic planning to monitor performance indicators over time. Customizing QILT surveys allows institutions to address questions not covered and better evaluate specific strategic initiatives.
Emerging Services for Research Informatio Management (RIM) through Enterprise...OCLC
This document discusses research information management (RIM) systems in universities. RIM systems integrate information about a university's researchers and their scholarly outputs. The primary uses of RIM systems are to facilitate faculty reporting, integrate with institutional repositories, enable benchmarking and reporting, and create public profiles of researcher expertise. RIM systems draw data from internal university sources like human resources systems and external sources like publication databases. They support collaboration between various university departments and partners like libraries. Common RIM uses seen in case studies of universities include faculty activity reporting, integrating with institutional repositories, creating public researcher profiles, and compiling reports.
The Sixty Minute (Data Dashboard) Makeover!Marieke Guy
Workshop run at the Institutional Web Management Workshop (IWMW) 2017 at Univeristy of kent, Tuesday 11th July 2017. Facilitated with Jon Rathmill, University of kent
How to start an online school budget and staffingAndrew Saint
This document discusses funding and budgeting considerations for starting an online school. It covers sources of funding such as state funding, grants, tuition/fees and donations. The budget sections outlines operational costs including staffing, instruction/curriculum/testing, technology, and professional services. Staffing considerations include personnel, salaries, and professional development. The document provides details on specific budget and staffing areas like curriculum, technology, operations, and other expenses.
This document discusses the importance of libraries using data and metrics to inform decision making and communicate their value. It notes that while librarians are good at collecting statistics, they often lack the ability or willingness to analyze, interpret, and apply the data. Without using data to take action or inform strategies, it has little value beyond justifying budgets. The document provides examples of how libraries can select peer institutions for benchmarking, analyze trends over time, and use multiple data sets to understand user needs and behaviors. It emphasizes telling "stories" combined with data ("Stories + Stats") to communicate effectively with stakeholders.
Lifecycle Integration with the University of KentuckySalesforce.org
Presentation from Salesforce.org Higher Ed Summit 2018 by: Tyler Gayheart, Office of Strategic Communication.
The University of Kentucky is embarking on a lifecycle enterprise approach to our digital and constituency relationship management (CRM) by way of a Enterprise Level Agreement (ELA) with Salesforce.org with the intention to deploy Salesforce for prospect, current student, alumni and donor operations carrying out over a multi-year period. This session will cover the process for planning, acquiring and building a lifecycle approach to deploying Salesforce across the enterprise at the University of Kentucky. An overview of activities will be shared from the completed phases of the project and speak to how the institutions plans to transform the way they engage prospects, current students, donors, alumni of the University.
Watch a recording of this presentation: https://youtu.be/8vKmN0oyIDM
A CRIS (Current Research Information System) is used to manage an institution's research information and outputs. It acts as an academic CV for the whole institution. A CRIS integrates data from various systems, allows complex workflows, and provides services for researchers and administrators. It covers the full research lifecycle from funding to publications to impact. Content is standardized, connected, and can be analyzed, reused for various purposes, and transported to external systems. A CRIS aims to provide a single point of access to showcase an institution's research capabilities.
The document discusses gaining business intelligence from user activity data in libraries and higher education institutions. It outlines challenges in collecting and analyzing comprehensive user data from different systems. The Open University perspective is that most students do not visit physical libraries and sign up for individual courses rather than degrees. However, the university has significant online user traffic that could provide insights if integrated across various learning and library systems. Overcoming cultural, technical, and data challenges will be key to developing a comprehensive view of user activity data.
Lifecycle Integration with the University of KentuckyTyler Gayheart
This document summarizes the University of Kentucky's implementation of Salesforce across multiple phases to integrate lifecycle data and improve recruitment, enrollment, alumni engagement, and philanthropic operations. Some key points:
- UK conducted a market study and chose Salesforce for its flexibility and because it could integrate across existing systems.
- Phase 1 focused on recruitment and included building out email marketing. It is on track to complete in April 2018.
- Future phases will address graduate admissions and alumni/donor relationships.
- Over 111 users are active now after moving from separate CRM systems to a centralized Salesforce model.
- Integration of data from various sources like applications and transcripts is underway.
-
This document provides information about Haluk Demirkan's background and experience. It summarizes his educational and professional qualifications, including over 10 years of research and higher education experience, as well as over 15 years of consulting and executive education experience. It also lists some of his academic accomplishments such as over 150 publications and research funded by several major companies. Finally, it provides details on some of the education topics he teaches related to services, information technology, and project management.
The document discusses national learning analytics in the UK and Jisc's role in providing learning analytics services. It describes Jisc's learning analytics tools and products like the Data Explorer dashboards, Study Goal app, and Learning Data Hub. It outlines Jisc's onboarding process for institutions and examples of how they are working with universities and colleges to implement learning analytics.
This document discusses the vision and strategic priorities of consolidating information systems at a university under a single entity called "One I.S.". It identifies challenges such as multiple disjointed systems and a lack of coordination. The strategic priorities are outlined as creating a single administration system, unified teaching and learning ecosystem, and unified research computing. The document discusses how centralizing services can help realize economies of scale, reduce costs, and mitigate risks. It provides comparisons to other universities and outlines changes to organizational structure, planning processes, and projects to work towards the "One I.S." vision.
This document summarizes the results of a needs assessment survey conducted by UNC Greensboro Library to understand faculty research data management practices and needs. The survey found that the top research data formats were text, PDFs, and spreadsheets. Most faculty backed up their data to external drives but not automatically. Three quarters of respondents did not anticipate sharing their data. The greatest needs identified were assistance with storage, backup, and meeting data sharing requirements. The library collaborated with campus partners to address these needs through new storage services, training, and guidance on developing data management plans.
This document provides an overview of analytics for learning and discusses implementation at GRCC. It begins with definitions of analytics, business intelligence, academic analytics, and learning analytics. It then discusses GRCC's strategic needs in areas like access to data, early alert systems, and measuring outcomes. The document outlines GRCC's analytics implementation, including hiring a data warehouse architect and campus training. It shows sample student and instructor reports in Blackboard Analytics and discusses next steps like dedicating time, building capacity, and engaging culture. It provides additional analytics resources.
Open data in ubi systems research data management plan (part 4)Heli Väätäjä
This slideset motivates to creating a data management plan and gives initial advice. Slides are from the seminar on Open Data in Ubiquitous Systems Research aimed for doctoral students in HCI and CS.
Defining the Libraries' Role in Research: A Needs Assessment Case StudyKathryn Crowe
This document summarizes the results of a needs assessment survey conducted at UNC Greensboro to understand faculty research data management needs. Key findings include: the most common data formats are text, PDFs, and spreadsheets; most faculty back up data themselves but do not follow best practices; the top priorities for support are storage/backup, meeting sharing requirements, and assistance with data management plans. Barriers to sharing include large data sizes and lack of knowledge about requirements and options. The survey informed new research data services from the libraries and other campus units, including data storage, curation, and consultation on data management plans and sharing requirements.
BbWorld 2013 - Learning Analytics: A Journey to Implementationekunnen
The document discusses Grand Rapids Community College's implementation of a learning analytics program. It provides background on the college and outlines their session agenda. It then defines analytics and discusses where relevant data is stored. The rest of the document outlines GRCC's strategic focus areas for analytics like student success, early alert systems, and course quality. It discusses their implementation process, future goals of building capacity and engaging faculty, and provides examples of analytics reports on topics like login tracking, course sizes, and grade comparisons.
This document discusses learning analytics and the potential uses of various institutional data sources. It describes how combining data from student records, the virtual learning environment (VLE), library usage, attendance records, and other sources through a learning analytics service could help improve student retention and attainment, enhance teaching quality, enable personalized learning, and support student health and well-being. Specific opportunities mentioned include predicting at-risk students, analyzing factors related to student success and employability, and using activity data to support timely interventions. Engaging various stakeholders like students, teachers, and campus planners is presented as important for effective use of learning analytics.
Similar to Altis Webinar: How To Fast Track Your University Admissions Reporting & Analysis During COVID-19 - May 2020 (20)
Altis Webinar: Use Cases For The Modern Data PlatformAltis Consulting
This document discusses use cases for a modern data platform. It begins by outlining the agenda, then provides background on Altis, the consulting firm. The document defines a modern data platform and explains how it differs from traditional setups. It discusses three approaches for selecting initial use cases: lift and shift with a twist, hitting a roadmap milestone, and supporting an organizational strategy. Examples are provided of where each approach has worked and struggled. The document covers design patterns, managing costs, and identifying success criteria for use cases.
Altis Webinar: Transform The Way You Build Your Modern Day Data Analytics Pla...Altis Consulting
Learn how Altis can help you build a scalable, cost-effective and Serverless Data Analytics platform using our automated framework.
Discover how easily you can kick-start your next data platform and reduce the time-to-value by providing faster business insights
Research firm Gartner coined the term augmented analytics in its 2017 Hype Cycle for Emerging Technologies report and claimed it would be the “future of data analytics.”
Augmented analytics is set to become the dominant driver of new purchases and projects in the analytics and business intelligence space.
Join VIC Regional Manager, Andy Painter as you explore what this means for your organisation and how best to jump onboard this rapidly expanding trend.
This 45-minute session will look at the importance of data literacy in your organisation, sharing tips on how you can get a start on better understanding your data.
For those contemplating re-architecting or greenfields data lakes/data hubs/data warehouses in a cloud environment, talk to our Altis AWS Practice Lead - Guillaume Jaudouin about why you should be considering the "tour de force" combination of AWS and Snowflake.
We are pleased to share with you the latest VCOSA statistical report on the cotton and yarn industry for the month of March 2024.
Starting from January 2024, the full weekly and monthly reports will only be available for free to VCOSA members. To access the complete weekly report with figures, charts, and detailed analysis of the cotton fiber market in the past week, interested parties are kindly requested to contact VCOSA to subscribe to the newsletter.
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
Build applications with generative AI on Google CloudMárton Kodok
We will explore Vertex AI - Model Garden powered experiences, we are going to learn more about the integration of these generative AI APIs. We are going to see in action what the Gemini family of generative models are for developers to build and deploy AI-driven applications. Vertex AI includes a suite of foundation models, these are referred to as the PaLM and Gemini family of generative ai models, and they come in different versions. We are going to cover how to use via API to: - execute prompts in text and chat - cover multimodal use cases with image prompts. - finetune and distill to improve knowledge domains - run function calls with foundation models to optimize them for specific tasks. At the end of the session, developers will understand how to innovate with generative AI and develop apps using the generative ai industry trends.
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.
Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...Kaxil Naik
Navigating today's data landscape isn't just about managing workflows; it's about strategically propelling your business forward. Apache Airflow has stood out as the benchmark in this arena, driving data orchestration forward since its early days. As we dive into the complexities of our current data-rich environment, where the sheer volume of information and its timely, accurate processing are crucial for AI and ML applications, the role of Airflow has never been more critical.
In my journey as the Senior Engineering Director and a pivotal member of Apache Airflow's Project Management Committee (PMC), I've witnessed Airflow transform data handling, making agility and insight the norm in an ever-evolving digital space. At Astronomer, our collaboration with leading AI & ML teams worldwide has not only tested but also proven Airflow's mettle in delivering data reliably and efficiently—data that now powers not just insights but core business functions.
This session is a deep dive into the essence of Airflow's success. We'll trace its evolution from a budding project to the backbone of data orchestration it is today, constantly adapting to meet the next wave of data challenges, including those brought on by Generative AI. It's this forward-thinking adaptability that keeps Airflow at the forefront of innovation, ready for whatever comes next.
The ever-growing demands of AI and ML applications have ushered in an era where sophisticated data management isn't a luxury—it's a necessity. Airflow's innate flexibility and scalability are what makes it indispensable in managing the intricate workflows of today, especially those involving Large Language Models (LLMs).
This talk isn't just a rundown of Airflow's features; it's about harnessing these capabilities to turn your data workflows into a strategic asset. Together, we'll explore how Airflow remains at the cutting edge of data orchestration, ensuring your organization is not just keeping pace but setting the pace in a data-driven future.
Session in https://budapestdata.hu/2024/04/kaxil-naik-astronomer-io/ | https://dataml24.sessionize.com/session/667627
Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...
Altis Webinar: How To Fast Track Your University Admissions Reporting & Analysis During COVID-19 - May 2020
1. Fast track your University to
a single copy of truth for
reporting & analysis
1st March 2020
Peter Hopwood
Higher Education Practice Lead
peterh@altis.com.au
0475 458 448
3. 1. About Altis Consulting
2. What is Data & Analytics?
3. About “Paterson University” (PU)
4. PU’s current reporting & analysis solution
5. PU’s future state reporting & analysis solution
6. Demo of PU’s future state dashboards
7. How Altis can help you
8. Q&A
Agenda
Fast track your University to a single copy
of truth for reporting & analysis
5. Company
overview
• Established in 1998
• Offices in London,
Sydney, Melbourne,
Canberra & Auckland
• Vendor independent
• Data & Analytics specialists
• 40+ Universities in UK, AU & NZ
110+
Introduction
About Altis Consulting
10 consecutive years
since 2010
8. We build and maintain trusted relationships,
connecting with our clients through our:
courage to tell it like it is and step up to
every challenge
heart to care passionately about your
business
unique insight derived from our 100+
permanent staff
Connecting with courage,
heart and insight
11. What is Data & Analytics?
• Bringing together data from disparate sources &
structuring it to support institution-wide decision making
• And not forgetting… toolsets, governance, security, data
quality, introducing a data culture, etc.
13. About Paterson University
• Paterson University (PU) is a fictitious institution
• We’ve generated fictitious student data
• PU runs XX courses and had approximately 14,000
applicants from 2016/17 to 2018/19
• PU also recruits through a Pathway provider – Better
Knowledge which is a wholly owned subsidiary
Any
resemblance to
actual
university logos,
current or past,
is purely
coincidental!
15. PU’s current reporting & analysis solution
Mix of on premise & cloud data sources Master version(s) of the truth
Some with existing operational reporting Some 3rd party data sources and files
No consistent approach to data governance Known/unknown data quality issues
Data Sources
Sources On Premise
• Student Management system (inc.
• Admissions)
• Finance
• Grants & Contracts
• Research
• HR
• Fundraising (Alumni)
• Learning Management System
• Library Management System
• Facilities Management System
• Timetabling System
• Active Directory
• Other systems
Sources Cloud
• Payroll
• CRM
• QILT survey data
• Admissions Centres (UAC/VTAC/
QTAC/TISC/SATAC/UTAS)
• Rankings data
• Other 3rd
Party Data Sources
16. PU’s current reporting & analysis solution
Replicated source system databases Siloed data marts/data warehouses/data lake
Some auto data integration (most manual) Hidden data transformations/calculations
No single enterprise DW/copy of truth Proliferation of Excel data silos (“shadow”)
Data Integration
Replicated Source System
Databases
Reporting/ Staging
Databases
Data Lakes/ Swamps
Siloed Data Marts/ Data
Warehouses
Data Sources
Sources On Premise
• Student Management system (inc.
• Admissions)
• Finance
• Grants & Contracts
• Research
• HR
• Fundraising (Alumni)
• Learning Management System
• Library Management System
• Facilities Management System
• Timetabling System
• Active Directory
• Other systems
Sources Cloud
• Payroll
• CRM
• QILT survey data
• Admissions Centres (UAC/VTAC/
QTAC/TISC/SATAC/UTAS)
• Rankings data
• Other 3rd
Party Data Sources
17. PU’s current reporting & analysis solution
Multiple reporting tools (Reporting/Data Viz) A lot of manual report creation
Duplicated reporting silos Planning & IT are a bottleneck
Proliferation of Excel reporting (“shadow”) Hard answering questions like course viability
Data Integration Reporting
Replicated Source System
Databases
Reporting/ Staging
Databases
Data Lakes/ Swamps
BI Reporting Tools
BI Visualisation Tools
Siloed Data Marts/ Data
Warehouses
Data Sources
Sources On Premise
• Student Management system (inc.
• Admissions)
• Finance
• Grants & Contracts
• Research
• HR
• Fundraising (Alumni)
• Learning Management System
• Library Management System
• Facilities Management System
• Timetabling System
• Active Directory
• Other systems
Sources Cloud
• Payroll
• CRM
• QILT survey data
• Admissions Centres (UAC/VTAC/
QTAC/TISC/SATAC/UTAS)
• Rankings data
• Other 3rd
Party Data Sources
18. PU’s current reporting & analysis solution
Distrust of data/questions about data quality Request rather than self-service
Queue for new reports No single portal for reporting
No single data access/security policy No data dictionary/report index
Consumers
Internal
• Faculties
• Student & Academic
• Planning
• Finance
• Marketing & Recruitment
• Research & Innovation
• People & Performance
• Estates & Facilities
• Information Technology
• Alumni
• Others
External
• Admissions Centres
• HEPCAT/TCSI
• PRISMS (Visa & immigration)
• QILT survey data
• ARC Data Portal (ERA report)
• Office for Students
• Others
Data Integration Reporting
Replicated Source System
Databases
Reporting/ Staging
Databases
Data Lakes/ Swamps
BI Reporting Tools
BI Visualisation Tools
Siloed Data Marts/ Data
Warehouses
Data Sources
Sources On Premise
• Student Management system (inc.
• Admissions)
• Finance
• Grants & Contracts
• Research
• HR
• Fundraising (Alumni)
• Learning Management System
• Library Management System
• Facilities Management System
• Timetabling System
• Active Directory
• Other systems
Sources Cloud
• Payroll
• CRM
• QILT survey data
• Admissions Centres (UAC/VTAC/
QTAC/TISC/SATAC/UTAS)
• Rankings data
• Other 3rd
Party Data Sources
19. PU’s current reporting & analysis solution
Summary of challenges
• A lot of manual error prone & duplicated effort (Excel)
• No single copy of governed truth for reporting & analysis
• Difficult to answer questions such as course viability
Consumers
Internal
• Faculties
• Student & Academic
• Planning
• Finance
• Marketing & Recruitment
• Research & Innovation
• People & Performance
• Estates & Facilities
• Information Technology
• Alumni
• Others
External
• Admissions Centres
• HEPCAT/TCSI
• PRISMS (Visa & immigration)
• QILT survey data
• ARC Data Portal (ERA report)
• Office for Students
• Others
Data Integration Reporting
Replicated Source System
Databases
Reporting/ Staging
Databases
Data Lakes/ Swamps
BI Reporting Tools
BI Visualisation Tools
Siloed Data Marts/ Data
Warehouses
Data Sources
Sources On Premise
• Student Management system (inc.
• Admissions)
• Finance
• Grants & Contracts
• Research
• HR
• Fundraising (Alumni)
• Learning Management System
• Library Management System
• Facilities Management System
• Timetabling System
• Active Directory
• Other systems
Sources Cloud
• Payroll
• CRM
• QILT survey data
• Admissions Centres (UAC/VTAC/
QTAC/TISC/SATAC/UTAS)
• Rankings data
• Other 3rd
Party Data Sources
20. Consumers
Internal
• Faculties
• Student & Academic
• Planning
• Finance
• Marketing & Recruitment
• Research & Innovation
• People & Performance
• Estates & Facilities
• Information Technology
• Alumni
• Others
External
• Admissions Centres
• HEPCAT/TCSI
• PRISMS (Visa & immigration)
• QILT survey data
• ARC Data Portal (ERA report)
• Office for Students
• Others
Data Integration Reporting
Replicated Source System
Databases
Reporting/ Staging
Databases
Data Lakes/ Swamps
BI Reporting Tools
BI Visualisation Tools
Siloed Data Marts/ Data
Warehouses
Data Sources
Sources On Premise
• Student Management system (inc.
• Admissions)
• Finance
• Grants & Contracts
• Research
• HR
• Fundraising (Alumni)
• Learning Management System
• Library Management System
• Facilities Management System
• Timetabling System
• Active Directory
• Other systems
Sources Cloud
• Payroll
• CRM
• QILT survey data
• Admissions Centres (UAC/VTAC/
QTAC/TISC/SATAC/UTAS)
• Rankings data
• Other 3rd
Party Data Sources
PU’s current reporting & analysis solution
Admissions reporting & analysis
21. Consumers
Internal
• Faculties
• Student & Academic
• Planning
• Finance
• Marketing & Recruitment
• Research & Innovation
• People & Performance
• Estates & Facilities
• Information Technology
• Alumni
• Others
External
• Admissions Centres
• HEPCAT/TCSI
• PRISMS (Visa & immigration)
• QILT survey data
• ARC Data Portal (ERA report)
• Office for Students
• Others
Data Integration Reporting
Replicated Source System
Databases
Reporting/ Staging
Databases
Data Lakes/ Swamps
BI Reporting Tools
BI Visualisation Tools
Siloed Data Marts/ Data
Warehouses
Data Sources
Sources On Premise
• Student Management system (inc.
• Admissions)
• Finance
• Grants & Contracts
• Research
• HR
• Fundraising (Alumni)
• Learning Management System
• Library Management System
• Facilities Management System
• Timetabling System
• Active Directory
• Other systems
Sources Cloud
• Payroll
• CRM
• QILT survey data
• Admissions Centres (UAC/VTAC/
QTAC/TISC/SATAC/UTAS)
• Rankings data
• Other 3rd
Party Data Sources
PU’s current reporting & analysis solution
Admissions reporting & analysis
22. Consumers
Internal
• Faculties
• Student & Academic
• Planning
• Finance
• Marketing & Recruitment
• Research & Innovation
• People & Performance
• Estates & Facilities
• Information Technology
• Alumni
• Others
External
• Admissions Centres
• HEPCAT/TCSI
• PRISMS (Visa & immigration)
• QILT survey data
• ARC Data Portal (ERA report)
• Office for Students
• Others
Data Integration Reporting
Replicated Source System
Databases
Reporting/ Staging
Databases
Data Lakes/ Swamps
BI Reporting Tools
BI Visualisation Tools
Siloed Data Marts/ Data
Warehouses
Data Sources
Sources On Premise
• Student Management system (inc.
• Admissions)
• Finance
• Grants & Contracts
• Research
• HR
• Fundraising (Alumni)
• Learning Management System
• Library Management System
• Facilities Management System
• Timetabling System
• Active Directory
• Other systems
Sources Cloud
• Payroll
• CRM
• QILT survey data
• Admissions Centres (UAC/VTAC/
QTAC/TISC/SATAC/UTAS)
• Rankings data
• Other 3rd
Party Data Sources
LU’s current reporting & analysis solution
Admissions reporting & analysis
23. Consumers
Internal
• Faculties
• Student & Academic
• Planning
• Finance
• Marketing & Recruitment
• Research & Innovation
• People & Performance
• Estates & Facilities
• Information Technology
• Alumni
• Others
External
• Admissions Centres
• HEPCAT/TCSI
• PRISMS (Visa & immigration)
• QILT survey data
• ARC Data Portal (ERA report)
• Office for Students
• Others
Data Integration Reporting
Replicated Source System
Databases
Reporting/ Staging
Databases
Data Lakes/ Swamps
BI Reporting Tools
BI Visualisation Tools
Siloed Data Marts/ Data
Warehouses
Data Sources
Sources On Premise
• Student Management system (inc.
• Admissions)
• Finance
• Grants & Contracts
• Research
• HR
• Fundraising (Alumni)
• Learning Management System
• Library Management System
• Facilities Management System
• Timetabling System
• Active Directory
• Other systems
Sources Cloud
• Payroll
• CRM
• QILT survey data
• Admissions Centres (UAC/VTAC/
QTAC/TISC/SATAC/UTAS)
• Rankings data
• Other 3rd
Party Data Sources
LU’s current reporting & analysis solution
Admissions reporting & analysis
24. LU’s current reporting & analysis solution
Admissions reporting & analysis
Lots of moving parts. No single copy of the
truth for Admissions reporting & analysis
Consumers
Internal
• Faculties
• Student & Academic
• Planning
• Finance
• Marketing & Recruitment
• Research & Innovation
• People & Performance
• Estates & Facilities
• Information Technology
• Alumni
• Others
External
• Admissions Centres
• HEPCAT/TCSI
• PRISMS (Visa & immigration)
• QILT survey data
• ARC Data Portal (ERA report)
• Office for Students
• Others
Data Integration Reporting
Replicated Source System
Databases
Reporting/ Staging
Databases
Data Lakes/ Swamps
BI Reporting Tools
BI Visualisation Tools
Siloed Data Marts/ Data
Warehouses
Data Sources
Sources On Premise
• Student Management system (inc.
• Admissions)
• Finance
• Grants & Contracts
• Research
• HR
• Fundraising (Alumni)
• Learning Management System
• Library Management System
• Facilities Management System
• Timetabling System
• Active Directory
• Other systems
Sources Cloud
• Payroll
• CRM
• QILT survey data
• Admissions Centres (UAC/VTAC/
QTAC/TISC/SATAC/UTAS)
• Rankings data
• Other 3rd
Party Data Sources
26. LU’s future state reporting & analysis solution
Automated integration of disparate data Data formatted for university-wide reporting
Stores history including changes Data Dictionary describing sources/lineage
Data is governed/ DQ issues managed Single copy of truth for reporting & analysis
Data IntegrationData Sources
Sources On Premise
• Student Management system (inc.
• Admissions)
• Finance
• Grants & Contracts
• Research
• HR
• Fundraising (Alumni)
• Learning Management System
• Library Management System
• Facilities Management System
• Timetabling System
• Active Directory
• Other systems
Sources Cloud
• Payroll
• CRM
• QILT survey data
• Admissions Centres (UAC/VTAC/
QTAC/TISC/SATAC/UTAS)
• Rankings data
• Other 3rd
Party Data Sources
Azure SQL DB
Azure Data Factory
Data Platform
Data Platform can cater for:
• Batch & streaming data
• Structured data
• Semi-structured data
• Unstructured data
27. LU’s future state reporting & analysis solution
Single reporting tool & portal Governance for reports
Reporting SME’s throughout University Planning/IT freed to add more value
Data Dictionary describing reports Easier to determine course viability
Data Integration ReportingData Sources
Sources On Premise
• Student Management system (inc.
• Admissions)
• Finance
• Grants & Contracts
• Research
• HR
• Fundraising (Alumni)
• Learning Management System
• Library Management System
• Facilities Management System
• Timetabling System
• Active Directory
• Other systems
Sources Cloud
• Payroll
• CRM
• QILT survey data
• Admissions Centres (UAC/VTAC/
QTAC/TISC/SATAC/UTAS)
• Rankings data
• Other 3rd
Party Data Sources
Azure SQL DB
Azure Data Factory
Data Platform
Data Platform can cater for:
• Batch & streaming data
• Structured data
• Semi-structured data
• Unstructured data
28. PU’s future state reporting & analysis solution
Self-serve rather than queuing Report index to aid finding stuff
Access via any device Increased trust in data/reporting
Single support process for all Single report request process
ConsumersData Integration ReportingData Sources
Internal
• Faculties
• Student & Academic
• Planning
• Finance
• Marketing & Recruitment
• Research & Innovation
• People & Performance
• Estates & Facilities
• Information Technology
• Alumni
• Others
External
• Admissions Centres
• HEPCAT/TCSI
• PRISMS (Visa & immigration)
• QILT survey data
• ARC Data Portal (ERA report)
• Office for Students
• Others
Sources On Premise
• Student Management system (inc.
• Admissions)
• Finance
• Grants & Contracts
• Research
• HR
• Fundraising (Alumni)
• Learning Management System
• Library Management System
• Facilities Management System
• Timetabling System
• Active Directory
• Other systems
Sources Cloud
• Payroll
• CRM
• QILT survey data
• Admissions Centres (UAC/VTAC/
QTAC/TISC/SATAC/UTAS)
• Rankings data
• Other 3rd
Party Data Sources
Azure SQL DB
Azure Data Factory
Data Platform
Data Platform can cater for:
• Batch & streaming data
• Structured data
• Semi-structured data
• Unstructured data
29. LU’s future state reporting & analysis solution
Summary of benefits
• Vastly reduce manual & duplicated effort ➔ redeploy team
• Single copy of governed truth for reporting & analysis
• Easier to answer cross-department questions
ConsumersData Integration ReportingData Sources
Internal
• Faculties
• Student & Academic
• Planning
• Finance
• Marketing & Recruitment
• Research & Innovation
• People & Performance
• Estates & Facilities
• Information Technology
• Alumni
• Others
External
• Admissions Centres
• HEPCAT/TCSI
• PRISMS (Visa & immigration)
• QILT survey data
• ARC Data Portal (ERA report)
• Office for Students
• Others
Sources On Premise
• Student Management system (inc.
• Admissions)
• Finance
• Grants & Contracts
• Research
• HR
• Fundraising (Alumni)
• Learning Management System
• Library Management System
• Facilities Management System
• Timetabling System
• Active Directory
• Other systems
Sources Cloud
• Payroll
• CRM
• QILT survey data
• Admissions Centres (UAC/VTAC/
QTAC/TISC/SATAC/UTAS)
• Rankings data
• Other 3rd
Party Data Sources
Azure SQL DB
Azure Data Factory
Data Platform
Data Platform can cater for:
• Batch & streaming data
• Structured data
• Semi-structured data
• Unstructured data
30. ConsumersData Integration ReportingData Sources
Internal
• Faculties
• Student & Academic
• Planning
• Finance
• Marketing & Recruitment
• Research & Innovation
• People & Performance
• Estates & Facilities
• Information Technology
• Alumni
• Others
External
• Admissions Centres
• HEPCAT/TCSI
• PRISMS (Visa & immigration)
• QILT survey data
• ARC Data Portal (ERA report)
• Office for Students
• Others
Sources On Premise
• Student Management system (inc.
• Admissions)
• Finance
• Grants & Contracts
• Research
• HR
• Fundraising (Alumni)
• Learning Management System
• Library Management System
• Facilities Management System
• Timetabling System
• Active Directory
• Other systems
Sources Cloud
• Payroll
• CRM
• QILT survey data
• Admissions Centres (UAC/VTAC/
QTAC/TISC/SATAC/UTAS)
• Rankings data
• Other 3rd
Party Data Sources
Azure SQL DB
Azure Data Factory
Data Platform
Data Platform can cater for:
• Batch & streaming data
• Structured data
• Semi-structured data
• Unstructured data
LU’s future state reporting & analysis solution
Admissions reporting & analysis
31. ConsumersData Integration ReportingData Sources
Internal
• Faculties
• Student & Academic
• Planning
• Finance
• Marketing & Recruitment
• Research & Innovation
• People & Performance
• Estates & Facilities
• Information Technology
• Alumni
• Others
External
• Admissions Centres
• HEPCAT/TCSI
• PRISMS (Visa & immigration)
• QILT survey data
• ARC Data Portal (ERA report)
• Office for Students
• Others
Sources On Premise
• Student Management system (inc.
• Admissions)
• Finance
• Grants & Contracts
• Research
• HR
• Fundraising (Alumni)
• Learning Management System
• Library Management System
• Facilities Management System
• Timetabling System
• Active Directory
• Other systems
Sources Cloud
• Payroll
• CRM
• QILT survey data
• Admissions Centres (UAC/VTAC/
QTAC/TISC/SATAC/UTAS)
• Rankings data
• Other 3rd
Party Data Sources
Azure SQL DB
Azure Data Factory
Data Platform
Data Platform can cater for:
• Batch & streaming data
• Structured data
• Semi-structured data
• Unstructured data
LU’s future state reporting & analysis solution
Admissions reporting & analysis
32. ConsumersData Integration ReportingData Sources
Internal
• Faculties
• Student & Academic
• Planning
• Finance
• Marketing & Recruitment
• Research & Innovation
• People & Performance
• Estates & Facilities
• Information Technology
• Alumni
• Others
External
• Admissions Centres
• HEPCAT/TCSI
• PRISMS (Visa & immigration)
• QILT survey data
• ARC Data Portal (ERA report)
• Office for Students
• Others
Sources On Premise
• Student Management system (inc.
• Admissions)
• Finance
• Grants & Contracts
• Research
• HR
• Fundraising (Alumni)
• Learning Management System
• Library Management System
• Facilities Management System
• Timetabling System
• Active Directory
• Other systems
Sources Cloud
• Payroll
• CRM
• QILT survey data
• Admissions Centres (UAC/VTAC/
QTAC/TISC/SATAC/UTAS)
• Rankings data
• Other 3rd
Party Data Sources
Azure SQL DB
Azure Data Factory
Data Platform
Data Platform can cater for:
• Batch & streaming data
• Structured data
• Semi-structured data
• Unstructured data
LU’s future state reporting & analysis solution
Admissions reporting & analysis
33. ConsumersData Integration ReportingData Sources
Internal
• Faculties
• Student & Academic
• Planning
• Finance
• Marketing & Recruitment
• Research & Innovation
• People & Performance
• Estates & Facilities
• Information Technology
• Alumni
• Others
External
• Admissions Centres
• HEPCAT/TCSI
• PRISMS (Visa & immigration)
• QILT survey data
• ARC Data Portal (ERA report)
• Office for Students
• Others
Sources On Premise
• Student Management system (inc.
• Admissions)
• Finance
• Grants & Contracts
• Research
• HR
• Fundraising (Alumni)
• Learning Management System
• Library Management System
• Facilities Management System
• Timetabling System
• Active Directory
• Other systems
Sources Cloud
• Payroll
• CRM
• QILT survey data
• Admissions Centres (UAC/VTAC/
QTAC/TISC/SATAC/UTAS)
• Rankings data
• Other 3rd
Party Data Sources
Azure SQL DB
Azure Data Factory
Data Platform
Data Platform can cater for:
• Batch & streaming data
• Structured data
• Semi-structured data
• Unstructured data
LU’s future state reporting & analysis solution
Admissions reporting & analysis
34. ConsumersData Integration ReportingData Sources
Internal
• Faculties
• Student & Academic
• Planning
• Finance
• Marketing & Recruitment
• Research & Innovation
• People & Performance
• Estates & Facilities
• Information Technology
• Alumni
• Others
External
• Admissions Centres
• HEPCAT/TCSI
• PRISMS (Visa & immigration)
• QILT survey data
• ARC Data Portal (ERA report)
• Office for Students
• Others
Sources On Premise
• Student Management system (inc.
• Admissions)
• Finance
• Grants & Contracts
• Research
• HR
• Fundraising (Alumni)
• Learning Management System
• Library Management System
• Facilities Management System
• Timetabling System
• Active Directory
• Other systems
Sources Cloud
• Payroll
• CRM
• QILT survey data
• Admissions Centres (UAC/VTAC/
QTAC/TISC/SATAC/UTAS)
• Rankings data
• Other 3rd
Party Data Sources
Azure SQL DB
Azure Data Factory
Data Platform
Data Platform can cater for:
• Batch & streaming data
• Structured data
• Semi-structured data
• Unstructured data
LU’s future state reporting & analysis solution
Admissions reporting & analysis
Single copy of the truth for Admissions
reporting & analysis
Admissions
35. ConsumersData Integration ReportingData Sources
Internal
• Faculties
• Student & Academic
• Planning
• Finance
• Marketing & Recruitment
• Research & Innovation
• People & Performance
• Estates & Facilities
• Information Technology
• Alumni
• Others
External
• Admissions Centres
• HEPCAT/TCSI
• PRISMS (Visa & immigration)
• QILT survey data
• ARC Data Portal (ERA report)
• Office for Students
• Others
Sources On Premise
• Student Management system (inc.
• Admissions)
• Finance
• Grants & Contracts
• Research
• HR
• Fundraising (Alumni)
• Learning Management System
• Library Management System
• Facilities Management System
• Timetabling System
• Active Directory
• Other systems
Sources Cloud
• Payroll
• CRM
• QILT survey data
• Admissions Centres (UAC/VTAC/
QTAC/TISC/SATAC/UTAS)
• Rankings data
• Other 3rd
Party Data Sources
Azure SQL DB
Azure Data Factory
Data Platform
Data Platform can cater for:
• Batch & streaming data
• Structured data
• Semi-structured data
• Unstructured data
LU’s future state reporting & analysis solution
Deliver solution incrementally
Additional subject areas can be added with
business benefits incrementally achieved
Enrolments
Finance
HR
Facilities
Research
Etc.
Admissions
36. PU’s future state reporting & analysis solution
Can use any toolsets
ConsumersData Integration ReportingData Sources
Internal
• Faculties
• Student & Academic
• Planning
• Finance
• Marketing & Recruitment
• Research & Innovation
• People & Performance
• Estates & Facilities
• Information Technology
• Alumni
• Others
External
• Admissions Centres
• HEPCAT/TCSI
• PRISMS (Visa & immigration)
• QILT survey data
• ARC Data Portal (ERA report)
• Office for Students
• Others
Sources On Premise
• Student Management system (inc.
• Admissions)
• Finance
• Grants & Contracts
• Research
• HR
• Fundraising (Alumni)
• Learning Management System
• Library Management System
• Facilities Management System
• Timetabling System
• Active Directory
• Other systems
Sources Cloud
• Payroll
• CRM
• QILT survey data
• Admissions Centres (UAC/VTAC/
QTAC/TISC/SATAC/UTAS)
• Rankings data
• Other 3rd
Party Data Sources
Azure SQL DB
Azure Data Factory
Data Platform
Data Platform can cater for:
• Batch & streaming data
• Structured data
• Semi-structured data
• Unstructured data
37. ConsumersData Integration ReportingData Sources
Internal
• Faculties
• Student & Academic
• Planning
• Finance
• Marketing & Recruitment
• Research & Innovation
• People & Performance
• Estates & Facilities
• Information Technology
• Alumni
• Others
External
• Admissions Centres
• HEPCAT/TCSI
• PRISMS (Visa & immigration)
• QILT survey data
• ARC Data Portal (ERA report)
• Office for Students
• Others
Sources On Premise
• Student Management system (inc.
• Admissions)
• Finance
• Grants & Contracts
• Research
• HR
• Fundraising (Alumni)
• Learning Management System
• Library Management System
• Facilities Management System
• Timetabling System
• Active Directory
• Other systems
Sources Cloud
• Payroll
• CRM
• QILT survey data
• Admissions Centres (UAC/VTAC/
QTAC/TISC/SATAC/UTAS)
• Rankings data
• Other 3rd
Party Data Sources
Azure SQL DB
Azure Data Factory
Data Platform
Data Platform can cater for:
• Batch & streaming data
• Structured data
• Semi-structured data
• Unstructured data
LU’s future state reporting & analysis solution
Can use any toolsets
Use your existing toolsets or we can help
you choose new ones
38. 6. Demo of PU’s future state
Admissions reporting
39. Demo of LU’s future state Admissions reporting
Solution Diagram
Azure SQL DB
Azure Data Factory
Azure SQL DB
• Generate source
admissions data
• Loaded into tables
simulating Student
Management
System
Admissions
dasboards
Augmented data
sets (SEIFA,
Geocoding, Travel
API)
40. Demo of PU’s future state Admissions reporting
Admissions dashboard
41. Demo of PU’s future state Admissions reporting
Admissions dashboard
44. How Altis can help you
• Data & Analytics Maturity Assessment
• Data & Analytics Health Check
• Data & Analytics Strategy & Roadmap
• Data & Analytics Platform/Toolset Selection
45. How Altis can help you
• Designing and building Admissions reporting
solutions
• Creating reports/dashboards
• Designing and building Data Lakes, Data
Warehouses, Data Platforms
• Delivering toolset and best practices training
• Power BI
• Azure Data Factory
• Data Visualisation
• Data Storytelling
• Data Literacy
• Dimensional Modelling
46. How Altis can help you
• Providing proactive support and maintenance
for Data & Analytics solution
• Provide support for defined periods to cover
staff leave
• Provide support for specific sections of the
overall solution
47. Why Partner with Altis?
• Deep Higher Education experience
• Vendor independence – partner with all the key vendors
• Data & Analytics specialisation since 1998
• Our ethos: “Connecting with Courage, Heart and Insight”
• Focus on business outcomes
• Recognised Best Places to Work 10 years running
• Employer of choice
• Skill and depth of our team – average tenure of 5 years
• Altis Managed Services can proactively support solution
• Transparent about our fees and easy to work with
Key message: Gives you confidence in our
delivery capability