How To Get Business Value From Kuali Analytics Matt Newman
Analytics As A Business User How To Get Business Value From Kuali Analytics Matt Newman Data Analytics Engineer
About Me ❖ Technologist/futurist/geek ❖ Long background in databases, business intelligence, analytics at non-profit, insurance company, religious organization, and now Kuali ❖ Technical guy, but love the business side - help people run a datadriven business ❖ Three little girls, a wife, a fish, and a frog ❖ Contact me at [email protected]
2
What is Business Intelligence/Analytics? ❖ Business intelligence (BI) is a technology-driven process for analyzing data and presenting actionable information to help corporate executives, business managers and other end users make more informed business decisions. ❖ Common functions of business intelligence technologies are reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics and prescriptive analytics. ❖ Reporting is "the public reporting of operating and financial data by a business enterprise," or "the regular provision of information to decision-makers within an organisation to support them in their work." ❖ Analytics is the discovery and communication of meaningful patterns in data. Analytics often favors data visualization to communicate insight. Firms may commonly apply analytics to business data, to describe, predict, and improve business performance.
Data (Human and Machine Generated)
Information (Context)
Knowledge/Intelligence
Business Decisions/Strategy/Competit ive Edge
3
Why Do We Need Analytics? ❖ In general, it helps businesses to: ❖ Run more efficiently ❖ Identify and resolve problems ❖ Make decisions ❖ Predict the future and develop strategy around it ❖ In particular, it helps higher education institutions: ❖ Provide better outcomes for students, thus attracting more students/tuition/revenue/funding ❖ Standardize, especially across many disparate colleges/departments/etc. ❖ Function more efficiently ❖ Make better use of tax dollars ❖ Influence government and other research funding providers to give more research grants
4
Why Do We Need Analytics? Questions/Hypotheses Higher Education Institution Machine
Research Funding - Public Grants, Private Grants, etc.
Education Funding - Tuition, Endowments, Scholarships, State-Provided Funds, etc.
Research Findings, Knowledge
More Educated Students
Less Educated Students
5
Why Do We Need Analytics? Questions/Hypotheses Higher Education Institution Machine
Research Funding - Public Grants, Private Grants, etc.
Education Funding - Tuition, Endowments, Scholarships, State-Provided Funds, etc.
Research Findings
More Educated Students
Less Educated Students
6
A Brief History of BI ❖ 1960s - Birth of BI ❖ After WWII, IBM computer scientist Hans Peter Luhn, father of Business Intelligence - article, titled “A Business Intelligence System”, described “an automatic system…developed to disseminate information to the various sections of any industrial, scientific, or government organization ❖ 1970s and 1980s - Rise of the DBMS ❖ Decision support systems (DSS) and executive information systems (EIS) in vogue ❖ Information Builders and SAS are born ❖ 1990s - Rise of the Data Warehouse ❖ Specialized, centralized place aggregates data from all operational systems - all in one place ❖ Crystal Reports, MicroStrategy are born ❖ ETL tools, OLAP, etc. - transform data into information, but mostly operational decision-making ❖ Early 2000s - BI 1.0 ❖ Produce data and reports, organize and visualize it ❖ Complex and time-consuming so IT department owns it and tools required a lot of training ❖ TDWI and many BI companies are born
7
A Brief History of BI ❖ Mid 2000s - Business Intelligence 2.0 ❖ Shift to Analytics - based on Statistics ❖ BI becomes a requirement to stay competitive - Tom Davenport at Harvard Business School “Competing on Analytics: The New Science of Winning” - top-performing enterprises are using data-driven analytics to inform competitive strategies - “secret weapons.” ❖ Real-time updates ❖ Self-service so non-technical business users can gain insights from data (less bottleneck and more empowerment) ❖ 2010s - Business Analytics ❖ More self-service, better visualization, mobile BI - accessible to all users ❖ Big data - machine-generated, unstructured, much more user-generated ❖ Cloud BI, federated queries ❖ In-memory databases and analytics engines BI is growing up - what started as a back office function is now something consumers use every day
8
BI Culture Maturity Levels Creating a culture of business intelligence 1. Unaware 2. Reactive (tactical) - IT in charge, one-off report requests, data inconsistency, look at past and react now 3. Proactive (focused) - funding from business project-by-project, only some users benefit, data quality for some projects, look at past and make plans 4. Managed (strategic) - centralized, standardized, business performance management or BPM, clean data, look at past and present and develop strategy 5. Optimized (pervasive and predictive) - information is trusted across organization, business processes depend on data, information shared with partners, strategy depends on predictions, predict the future and develop strategy
9
BI Technology Maturity Levels Creating tools and technology for business intelligence, using human and machine data 1. 2. 3. 4. 5. 6.
Prenatal - few rudimentary management reports Infant - spreadsheets, one-off reports Child - data marts, standardized canned reports, table dumps, operational reporting Teenager - data warehouse, query and analysis, dynamic reports, OLAP, real-time reporting Adult - enterprise data warehouse, dashboard management, BPM, KPIs, Cloud BI, Mobile BI Sage - analytical services, data mining/science, predictive analytics, machine learning, complex event processing
My goal is to help build these tools and help higher education institutions mature their BI maturity levels
10
Kuali Analytics and Data Strategy API
CSV
Embedded Insights
Canned reports
Ad-hoc reporting
Hosted data
Data Export
11
How It Looks Consumers Subscribe Producers Push (Event)
Java App
MySQL DB
Publish
binlog
Node.js App
RethinkDB
change feeds
Node.js App
MongoDB
oplog
Data Warehouse (MPP) (Amazon Redshift, Snowflake, etc.)
BI Tool (Reports Dashboards, Ad-Hoc Queries)
Message Broker/Queue (Apache Kafka, RabbitMQ, Kinesis, Confluent)
External System (Ellucian Banner)
12
Kuali Analytics Offerings ❖ Kuali Analytics Basic ❖ A few (10-15) very simple canned reports/dashboards embedded in app ❖ Included with product at no cost (for on-premise customers too) ❖ Kuali Analytics Premium ❖ Many (20-50+) nice canned reports embedded in app ❖ Interactive dashboards (filters, drillthrough, export to PDF/CSV/PNG, etc.) ❖ Ad hoc query tool that lets you build and save your own reports and embed in the app for your school ❖ Set up jobs to send out emails ❖ Built with white-labeled commercial solution and custom tools ❖ Additional cost (talk to your account representative)
13
Kuali Analytics Database Options ❖ Primary database of application ❖ Pros - in real-time, no additional cost ❖ Cons - analytics load could impact production, not always relational ❖ Kuali data warehouse ❖ Pros - in real-time, analytics won’t impact production, relational and document formats ❖ Cons - medium cost ❖ External data warehouse or operational data system (ODS) ❖ Pros - analytics won’t impact production ❖ Cons - may not be in real-time as it depends on how customer does it, high cost (depends on how school implements but usually quite expensive)
14
Status of Offerings ❖ Student ❖ Basic - real-time reports available, 9 reports currently ❖ Premium - available ❖ Ready ❖ Basic - 3 reports available, not real-time, soon will have 15-20 (replacing current reports) ❖ Premium - will be available in 2-3 weeks ❖ Financials ❖ Basic - 2 reports available, not real-time or fully integrated, soon will have 20-25 (will replace current 7 reports) ❖ Premium - will be available in 2-3 months ❖ Research ❖ Basic - no reports available, will eventually replace Jasper, will be available in 2-3 months ❖ Premium - will be available in 3-4 months
15
Enabling Reports ❖ Enable Reports Using Feature Flag ❖ Reports will be updated in real-time
16
Student Scenarios Kuali Student Application
Kuali Data Warehouse
Emily, the Provost, wants to view a report of all the courses that have been approved in the last two months
17
Reporting Use Cases ❖ ❖ ❖ ❖ ❖ ❖
Course Counts Course Proposal Counts Program and Course Outcomes Changes to Learning Outcomes Courses Approved Over Time Course Dependencies
18
Financials Scenarios Kuali Financials Application
Kuali Data Warehouse
Mary wants a report where she can see information about available balances
19
Ready Scenarios Kuali Ready Application
Ad hoc query tool
Kuali Data Warehouse
Jim wants to build a report to see information about continuity plans
20
Kuali Analytics Premium Features ❖ Institution-Specific Reports ❖ Ad Hoc Query Tool ❖ Building, Saving, and Publishing Your Own Reports
21
Reports Security ❖ Locked down so institutions can only see their data, and it all requires authentication ❖ Soon there will be more user-level security so you can restrict data/reports to certain users/roles that is more relevant to users in that role ❖ Built on mature, secure commercial products ❖ Code audit from external third-party and more to come
22
Reporting Roadmap ❖ Real-time reporting for all applications (Ready, Financials, Research) ❖ More user-level access and security ❖ More features for Kuali Analytics Premium - better data sources, make it easier to build your own reports ❖ More historical/auditing/logging data - who change what when - common history tables for all data ❖ Revised reports for all apps
23
Conclusion ❖ Higher education institutions can make more data-driven decisions ❖ Kuali has many feature-rich, secure reporting tools today that can help business users ❖ Over time, reporting/dashboarding is getting more sophisticated and will be available in all applications ❖ There is a premium offering you may have interest in
24
Questions?
25
Notes ❖ Document with Scenarios ❖ Research Demo
26
About Me ❖ Technologist/futurist/geek ❖ Long background in databases, business intelligence, analytics at non-profit, insurance company, religious organization, and now Kuali ❖ Technical guy, but love the business side - help people run a datadriven business ❖ Three little girls, a wife, a fish, and a frog ❖ Contact me at [email protected]
2
What is Business Intelligence/Analytics? ❖ Business intelligence (BI) is a technology-driven process for analyzing data and presenting actionable information to help corporate executives, business managers and other end users make more informed business decisions. ❖ Common functions of business intelligence technologies are reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics and prescriptive analytics. ❖ Reporting is "the public reporting of operating and financial data by a business enterprise," or "the regular provision of information to decision-makers within an organisation to support them in their work." ❖ Analytics is the discovery and communication of meaningful patterns in data. Analytics often favors data visualization to communicate insight. Firms may commonly apply analytics to business data, to describe, predict, and improve business performance.
Data (Human and Machine Generated)
Information (Context)
Knowledge/Intelligence
Business Decisions/Strategy/Competit ive Edge
3
Why Do We Need Analytics? ❖ In general, it helps businesses to: ❖ Run more efficiently ❖ Identify and resolve problems ❖ Make decisions ❖ Predict the future and develop strategy around it ❖ In particular, it helps higher education institutions: ❖ Provide better outcomes for students, thus attracting more students/tuition/revenue/funding ❖ Standardize, especially across many disparate colleges/departments/etc. ❖ Function more efficiently ❖ Make better use of tax dollars ❖ Influence government and other research funding providers to give more research grants
4
Why Do We Need Analytics? Questions/Hypotheses Higher Education Institution Machine
Research Funding - Public Grants, Private Grants, etc.
Education Funding - Tuition, Endowments, Scholarships, State-Provided Funds, etc.
Research Findings, Knowledge
More Educated Students
Less Educated Students
5
Why Do We Need Analytics? Questions/Hypotheses Higher Education Institution Machine
Research Funding - Public Grants, Private Grants, etc.
Education Funding - Tuition, Endowments, Scholarships, State-Provided Funds, etc.
Research Findings
More Educated Students
Less Educated Students
6
A Brief History of BI ❖ 1960s - Birth of BI ❖ After WWII, IBM computer scientist Hans Peter Luhn, father of Business Intelligence - article, titled “A Business Intelligence System”, described “an automatic system…developed to disseminate information to the various sections of any industrial, scientific, or government organization ❖ 1970s and 1980s - Rise of the DBMS ❖ Decision support systems (DSS) and executive information systems (EIS) in vogue ❖ Information Builders and SAS are born ❖ 1990s - Rise of the Data Warehouse ❖ Specialized, centralized place aggregates data from all operational systems - all in one place ❖ Crystal Reports, MicroStrategy are born ❖ ETL tools, OLAP, etc. - transform data into information, but mostly operational decision-making ❖ Early 2000s - BI 1.0 ❖ Produce data and reports, organize and visualize it ❖ Complex and time-consuming so IT department owns it and tools required a lot of training ❖ TDWI and many BI companies are born
7
A Brief History of BI ❖ Mid 2000s - Business Intelligence 2.0 ❖ Shift to Analytics - based on Statistics ❖ BI becomes a requirement to stay competitive - Tom Davenport at Harvard Business School “Competing on Analytics: The New Science of Winning” - top-performing enterprises are using data-driven analytics to inform competitive strategies - “secret weapons.” ❖ Real-time updates ❖ Self-service so non-technical business users can gain insights from data (less bottleneck and more empowerment) ❖ 2010s - Business Analytics ❖ More self-service, better visualization, mobile BI - accessible to all users ❖ Big data - machine-generated, unstructured, much more user-generated ❖ Cloud BI, federated queries ❖ In-memory databases and analytics engines BI is growing up - what started as a back office function is now something consumers use every day
8
BI Culture Maturity Levels Creating a culture of business intelligence 1. Unaware 2. Reactive (tactical) - IT in charge, one-off report requests, data inconsistency, look at past and react now 3. Proactive (focused) - funding from business project-by-project, only some users benefit, data quality for some projects, look at past and make plans 4. Managed (strategic) - centralized, standardized, business performance management or BPM, clean data, look at past and present and develop strategy 5. Optimized (pervasive and predictive) - information is trusted across organization, business processes depend on data, information shared with partners, strategy depends on predictions, predict the future and develop strategy
9
BI Technology Maturity Levels Creating tools and technology for business intelligence, using human and machine data 1. 2. 3. 4. 5. 6.
Prenatal - few rudimentary management reports Infant - spreadsheets, one-off reports Child - data marts, standardized canned reports, table dumps, operational reporting Teenager - data warehouse, query and analysis, dynamic reports, OLAP, real-time reporting Adult - enterprise data warehouse, dashboard management, BPM, KPIs, Cloud BI, Mobile BI Sage - analytical services, data mining/science, predictive analytics, machine learning, complex event processing
My goal is to help build these tools and help higher education institutions mature their BI maturity levels
10
Kuali Analytics and Data Strategy API
CSV
Embedded Insights
Canned reports
Ad-hoc reporting
Hosted data
Data Export
11
How It Looks Consumers Subscribe Producers Push (Event)
Java App
MySQL DB
Publish
binlog
Node.js App
RethinkDB
change feeds
Node.js App
MongoDB
oplog
Data Warehouse (MPP) (Amazon Redshift, Snowflake, etc.)
BI Tool (Reports Dashboards, Ad-Hoc Queries)
Message Broker/Queue (Apache Kafka, RabbitMQ, Kinesis, Confluent)
External System (Ellucian Banner)
12
Kuali Analytics Offerings ❖ Kuali Analytics Basic ❖ A few (10-15) very simple canned reports/dashboards embedded in app ❖ Included with product at no cost (for on-premise customers too) ❖ Kuali Analytics Premium ❖ Many (20-50+) nice canned reports embedded in app ❖ Interactive dashboards (filters, drillthrough, export to PDF/CSV/PNG, etc.) ❖ Ad hoc query tool that lets you build and save your own reports and embed in the app for your school ❖ Set up jobs to send out emails ❖ Built with white-labeled commercial solution and custom tools ❖ Additional cost (talk to your account representative)
13
Kuali Analytics Database Options ❖ Primary database of application ❖ Pros - in real-time, no additional cost ❖ Cons - analytics load could impact production, not always relational ❖ Kuali data warehouse ❖ Pros - in real-time, analytics won’t impact production, relational and document formats ❖ Cons - medium cost ❖ External data warehouse or operational data system (ODS) ❖ Pros - analytics won’t impact production ❖ Cons - may not be in real-time as it depends on how customer does it, high cost (depends on how school implements but usually quite expensive)
14
Status of Offerings ❖ Student ❖ Basic - real-time reports available, 9 reports currently ❖ Premium - available ❖ Ready ❖ Basic - 3 reports available, not real-time, soon will have 15-20 (replacing current reports) ❖ Premium - will be available in 2-3 weeks ❖ Financials ❖ Basic - 2 reports available, not real-time or fully integrated, soon will have 20-25 (will replace current 7 reports) ❖ Premium - will be available in 2-3 months ❖ Research ❖ Basic - no reports available, will eventually replace Jasper, will be available in 2-3 months ❖ Premium - will be available in 3-4 months
15
Enabling Reports ❖ Enable Reports Using Feature Flag ❖ Reports will be updated in real-time
16
Student Scenarios Kuali Student Application
Kuali Data Warehouse
Emily, the Provost, wants to view a report of all the courses that have been approved in the last two months
17
Reporting Use Cases ❖ ❖ ❖ ❖ ❖ ❖
Course Counts Course Proposal Counts Program and Course Outcomes Changes to Learning Outcomes Courses Approved Over Time Course Dependencies
18
Financials Scenarios Kuali Financials Application
Kuali Data Warehouse
Mary wants a report where she can see information about available balances
19
Ready Scenarios Kuali Ready Application
Ad hoc query tool
Kuali Data Warehouse
Jim wants to build a report to see information about continuity plans
20
Kuali Analytics Premium Features ❖ Institution-Specific Reports ❖ Ad Hoc Query Tool ❖ Building, Saving, and Publishing Your Own Reports
21
Reports Security ❖ Locked down so institutions can only see their data, and it all requires authentication ❖ Soon there will be more user-level security so you can restrict data/reports to certain users/roles that is more relevant to users in that role ❖ Built on mature, secure commercial products ❖ Code audit from external third-party and more to come
22
Reporting Roadmap ❖ Real-time reporting for all applications (Ready, Financials, Research) ❖ More user-level access and security ❖ More features for Kuali Analytics Premium - better data sources, make it easier to build your own reports ❖ More historical/auditing/logging data - who change what when - common history tables for all data ❖ Revised reports for all apps
23
Conclusion ❖ Higher education institutions can make more data-driven decisions ❖ Kuali has many feature-rich, secure reporting tools today that can help business users ❖ Over time, reporting/dashboarding is getting more sophisticated and will be available in all applications ❖ There is a premium offering you may have interest in
24
Questions?
25
Notes ❖ Document with Scenarios ❖ Research Demo
26
