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Cloud Native
Computing, Services & Data
www.mdcloud.es
AGENDA
• What is UBEAT?
• What were the challenges of this project?
• What is the solution that we built?
• What are the results that we achieved?
• What’s ahead?
www.mdcloud.es
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Quisque tempus pretium nulla at dapibus. Vivamus venenatis nisi ut neque ultricies, vel iaculis
enim lobortis. In hac habitasse platea dictumst. Praesent aliquet a urna ut suscipit. Fusce elit augue, placerat nec nunc sit amet, sodales hendrerit
libero. Quisque ultrices ligula in leo elementum interdum. In hac habitasse platea dictumst. Quisque tristique eros at metus aliquet consequat.
Pellentesque fermentum gravida lacinia. Pellentesque vulputate lectus odio, et lobortis quam consequat at. Duis in odio viverra diam dictum pulvinar
eu ut ex. Ut sed bibendum est, nec dictum leo. Nulla gravida id neque non fringilla. Mauris in urna interdum, molestie mi at, faucibus quam.
What are eSports?
www.eurecat.org
www.mdcloud.es
www.mdcloud.es
Where does UBEAT fit
in this new ecosystem?
www.mdcloud.es
Broadcasting
Platform
www.mdcloud.es
The first Broadcasting platform
focused in creating
Added Value content for eSports
Interviews
Entertainment
Shows
Finals
Best Outplays
Replays
…
www.mdcloud.es
AGENDA
• What is UBEAT?
• What were the challenges of this project?
• What is the solution that we built?
• What are the results that we achieved?
• What’s ahead?
www.mdcloud.es
Objectives
Main project objectives and requirements
Extract data from several data
sources and consolidate it in a
central DWH
Central DWH
Provide a 360º customer view
Customer 360
Design new data architecture to
support high variability on data
volume
Cloud Architecture
Develop user friendly reports
for visual data analysis
Visual Reporting
Data aggregation and exporting
for external Marketing
Campaigns
Marketing Campaigns
Provide a suitable environment
to perform multi source
advanced analytics (Customer
segmentation, product
refinement, etc)
Advanced Analytics
www.mdcloud.es
Datasources
Overview of Project Datasources
Youbora
Video analytics. Registered user detailed video
consumption: VOD/LIVE, platform, device, session
monitoring, etc. Expected volume 5Gb/y. API
access
Each datasource is owned by different teams, so there is a big challenge for the project to manage everyone and get them aware of others
requirements. Basically, datasource owners must take into account that they are part of something bigger
Google Firebase – Big query
APP Analytics. Telemetry, user actions, user
behavior tracking, app interactions. Expected
volume 20GB/y. API access
Google Analytics
Web Analytics. Telemetry, user actions, user
behavior tracking, web interactions. Aggregated
data. Expected volume 1GB/y. API access
Adobe Campaign
Marketing campaigns. Campaign success
measurement, email metrics, response ratios, etc.
Both source and consumer. Expected volume
1GB/y. File data transfer
BackOffice
Platform internal data. Registered users and
master data. Expected volume 250MB/y. ODBC
access
AppsFlyer
APP market. APP downloads, installations and
uninstallations. Expected volume 100MB/y. API
access
www.mdcloud.es
Datasources
UBEAT Data Environment
Youbora
Google Analytics
BackOffice
Firebase
Adobe Campaign
AppsFlyer
Data Flow
Business Flow
www.mdcloud.es
AGENDA
• What is UBEAT?
• What were the challenges of this project?
• What is the solution that we built?
• What are the results that we achieved?
• What’s ahead?
www.mdcloud.es
Conceptual Architecture
DWH
Staging Area, Modeled Area and Master Data
Key Concepts
OLAP Analytics
Cube generation for performance purposes
Visual Analytics & Reporting
System edge for user data consumption and visual
analysis
Monitoring
Monitoring facilities for Operation team once in
production
Orchestrator
Automation of data ETL (Extract-Transform-Load)
processes
Data Security
Data encryption and secured communications
Data Governance
Data Quality, Processes and documentation
www.mdcloud.es
Physical Architecture
Main Components
Azure Datafactory
PAAS - Acting as orchestrator. Data extraction and
internal movement
Azure Storage (STAs)
PAAS - raw files stored for data ingestion and data
sending to 3rd Parties
Azure SQL (DWH)
PAAS - Microsoft SQL Server Cloud instance acting as
central data repository. Staging / Dimensions + Facts
Integration Runtime
IAAS - Virtual Machine Required for on-premise access
purposes
Key Vault
PAAS - Component for securely storing and accessing
platform, secrets (tokens, passwords, etc)
Azure Analysis Services
PAAS - enterprise-grade data models in the cloud. OLAP
High performance cubes
Excel & PowerBI
Data consumption is done by PowerBI cloud Service and
excel files
www.mdcloud.es
Solution highlights
Pay
per Use
Pay as you go
Azure Public cloud infrastructure enables minimum consumption
on money terms. Reduce infrastrcuture costs
Authomatic scalable on demand
Automatic system and infrastructure adaptation on high demand
periods or sudden increases of data flows. No data loss
Security compliance
Platform secrets, passwords and data encryption. Data movement
secured by product
PAAS Services
Major use of PAAS services – Minimum concern on infrastructure
on administration and maintenance. Focus on value
Security
ScalabilityPAAS
www.mdcloud.es
AGENDA
• What is UBEAT?
• What were the challenges of this project?
• What is the solution that we built?
• What are the results that we achieved?
• What’s ahead?
www.mdcloud.es
Visual Results - Reporting
www.mdcloud.es
Visual Results - Reporting
FAKE DATA
Only for explanation purpose
www.mdcloud.es
Visual Results - Reporting
FAKE DATA
Only for explanation purpose
www.mdcloud.es
Business Results
Goals achieved from business view
Data driven based decisions
Customer Segmentation
Product improvement
Trend detection
Customer 360
Data driven based decisions
Journey helper from: Raw disintegrated data ->
Information -> Knowledge -> Data Based decisions
Customer Segmentation
Significant success in customer targeting.
Higher success rate for marketing campaigns
Product improvement
Video scheduling accuracy -> Product Quality
improved -> Increase customer satisfaction
Trend detection
Aggregated user behavior trend detection ->
Better and quicker response for incoming or
underlying events
Customer 360
Customer (Fan) information completed. New
customer insights for business people (Video
cosumption, campaing response, APP usage, etc)
www.mdcloud.es
AGENDA
• What is UBEAT?
• What were the challenges of this project?
• What is the solution that we built?
• What are the results that we achieved?
• What’s ahead?
www.mdcloud.es
A.I.
COMES TO
eSPORTS
Audience behavior prediction
Realtime custom content enrichment
for individuals
Personalized add insertion
Chatbots
www.mdcloud.es
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Quisque tempus pretium nulla at dapibus. Vivamus venenatis nisi ut neque ultricies, vel iaculis
enim lobortis. In hac habitasse platea dictumst. Praesent aliquet a urna ut suscipit. Fusce elit augue, placerat nec nunc sit amet, sodales hendrerit
libero. Quisque ultrices ligula in leo elementum interdum. In hac habitasse platea dictumst. Quisque tristique eros at metus aliquet consequat.
Pellentesque fermentum gravida lacinia. Pellentesque vulputate lectus odio, et lobortis quam consequat at. Duis in odio viverra diam dictum pulvinar
eu ut ex. Ut sed bibendum est, nec dictum leo. Nulla gravida id neque non fringilla. Mauris in urna interdum, molestie mi at, faucibus quam.
?
Cloud Native Computing, Services & Data Insights

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Cloud Native Computing, Services & Data Insights

  • 2. www.mdcloud.es AGENDA • What is UBEAT? • What were the challenges of this project? • What is the solution that we built? • What are the results that we achieved? • What’s ahead?
  • 3. www.mdcloud.es Lorem ipsum dolor sit amet, consectetur adipiscing elit. Quisque tempus pretium nulla at dapibus. Vivamus venenatis nisi ut neque ultricies, vel iaculis enim lobortis. In hac habitasse platea dictumst. Praesent aliquet a urna ut suscipit. Fusce elit augue, placerat nec nunc sit amet, sodales hendrerit libero. Quisque ultrices ligula in leo elementum interdum. In hac habitasse platea dictumst. Quisque tristique eros at metus aliquet consequat. Pellentesque fermentum gravida lacinia. Pellentesque vulputate lectus odio, et lobortis quam consequat at. Duis in odio viverra diam dictum pulvinar eu ut ex. Ut sed bibendum est, nec dictum leo. Nulla gravida id neque non fringilla. Mauris in urna interdum, molestie mi at, faucibus quam. What are eSports?
  • 5. www.mdcloud.es Where does UBEAT fit in this new ecosystem?
  • 7. www.mdcloud.es The first Broadcasting platform focused in creating Added Value content for eSports Interviews Entertainment Shows Finals Best Outplays Replays …
  • 8. www.mdcloud.es AGENDA • What is UBEAT? • What were the challenges of this project? • What is the solution that we built? • What are the results that we achieved? • What’s ahead?
  • 9. www.mdcloud.es Objectives Main project objectives and requirements Extract data from several data sources and consolidate it in a central DWH Central DWH Provide a 360º customer view Customer 360 Design new data architecture to support high variability on data volume Cloud Architecture Develop user friendly reports for visual data analysis Visual Reporting Data aggregation and exporting for external Marketing Campaigns Marketing Campaigns Provide a suitable environment to perform multi source advanced analytics (Customer segmentation, product refinement, etc) Advanced Analytics
  • 10. www.mdcloud.es Datasources Overview of Project Datasources Youbora Video analytics. Registered user detailed video consumption: VOD/LIVE, platform, device, session monitoring, etc. Expected volume 5Gb/y. API access Each datasource is owned by different teams, so there is a big challenge for the project to manage everyone and get them aware of others requirements. Basically, datasource owners must take into account that they are part of something bigger Google Firebase – Big query APP Analytics. Telemetry, user actions, user behavior tracking, app interactions. Expected volume 20GB/y. API access Google Analytics Web Analytics. Telemetry, user actions, user behavior tracking, web interactions. Aggregated data. Expected volume 1GB/y. API access Adobe Campaign Marketing campaigns. Campaign success measurement, email metrics, response ratios, etc. Both source and consumer. Expected volume 1GB/y. File data transfer BackOffice Platform internal data. Registered users and master data. Expected volume 250MB/y. ODBC access AppsFlyer APP market. APP downloads, installations and uninstallations. Expected volume 100MB/y. API access
  • 11. www.mdcloud.es Datasources UBEAT Data Environment Youbora Google Analytics BackOffice Firebase Adobe Campaign AppsFlyer Data Flow Business Flow
  • 12. www.mdcloud.es AGENDA • What is UBEAT? • What were the challenges of this project? • What is the solution that we built? • What are the results that we achieved? • What’s ahead?
  • 13. www.mdcloud.es Conceptual Architecture DWH Staging Area, Modeled Area and Master Data Key Concepts OLAP Analytics Cube generation for performance purposes Visual Analytics & Reporting System edge for user data consumption and visual analysis Monitoring Monitoring facilities for Operation team once in production Orchestrator Automation of data ETL (Extract-Transform-Load) processes Data Security Data encryption and secured communications Data Governance Data Quality, Processes and documentation
  • 14. www.mdcloud.es Physical Architecture Main Components Azure Datafactory PAAS - Acting as orchestrator. Data extraction and internal movement Azure Storage (STAs) PAAS - raw files stored for data ingestion and data sending to 3rd Parties Azure SQL (DWH) PAAS - Microsoft SQL Server Cloud instance acting as central data repository. Staging / Dimensions + Facts Integration Runtime IAAS - Virtual Machine Required for on-premise access purposes Key Vault PAAS - Component for securely storing and accessing platform, secrets (tokens, passwords, etc) Azure Analysis Services PAAS - enterprise-grade data models in the cloud. OLAP High performance cubes Excel & PowerBI Data consumption is done by PowerBI cloud Service and excel files
  • 15. www.mdcloud.es Solution highlights Pay per Use Pay as you go Azure Public cloud infrastructure enables minimum consumption on money terms. Reduce infrastrcuture costs Authomatic scalable on demand Automatic system and infrastructure adaptation on high demand periods or sudden increases of data flows. No data loss Security compliance Platform secrets, passwords and data encryption. Data movement secured by product PAAS Services Major use of PAAS services – Minimum concern on infrastructure on administration and maintenance. Focus on value Security ScalabilityPAAS
  • 16. www.mdcloud.es AGENDA • What is UBEAT? • What were the challenges of this project? • What is the solution that we built? • What are the results that we achieved? • What’s ahead?
  • 18. www.mdcloud.es Visual Results - Reporting FAKE DATA Only for explanation purpose
  • 19. www.mdcloud.es Visual Results - Reporting FAKE DATA Only for explanation purpose
  • 20. www.mdcloud.es Business Results Goals achieved from business view Data driven based decisions Customer Segmentation Product improvement Trend detection Customer 360 Data driven based decisions Journey helper from: Raw disintegrated data -> Information -> Knowledge -> Data Based decisions Customer Segmentation Significant success in customer targeting. Higher success rate for marketing campaigns Product improvement Video scheduling accuracy -> Product Quality improved -> Increase customer satisfaction Trend detection Aggregated user behavior trend detection -> Better and quicker response for incoming or underlying events Customer 360 Customer (Fan) information completed. New customer insights for business people (Video cosumption, campaing response, APP usage, etc)
  • 21. www.mdcloud.es AGENDA • What is UBEAT? • What were the challenges of this project? • What is the solution that we built? • What are the results that we achieved? • What’s ahead?
  • 22. www.mdcloud.es A.I. COMES TO eSPORTS Audience behavior prediction Realtime custom content enrichment for individuals Personalized add insertion Chatbots
  • 23. www.mdcloud.es Lorem ipsum dolor sit amet, consectetur adipiscing elit. Quisque tempus pretium nulla at dapibus. Vivamus venenatis nisi ut neque ultricies, vel iaculis enim lobortis. In hac habitasse platea dictumst. Praesent aliquet a urna ut suscipit. Fusce elit augue, placerat nec nunc sit amet, sodales hendrerit libero. Quisque ultrices ligula in leo elementum interdum. In hac habitasse platea dictumst. Quisque tristique eros at metus aliquet consequat. Pellentesque fermentum gravida lacinia. Pellentesque vulputate lectus odio, et lobortis quam consequat at. Duis in odio viverra diam dictum pulvinar eu ut ex. Ut sed bibendum est, nec dictum leo. Nulla gravida id neque non fringilla. Mauris in urna interdum, molestie mi at, faucibus quam. ?

Notas del editor

  1. Datacleansing / ETL / Cloud - and auto scale-up-and-out
  2. Això pasa sempre, silos de coneixement
  3. Dades sensibles encriptades al DWH amb unes claus que estan al KeyVault Les conexions d'azure van encriptades Elements IR (Integration Runtime) Com que el postgre està protegit per IP, hem d'asegurar una IP estàtica (ADF es un motor al cloud amb les capacitats capades).El cloud està molt bé, pero necesites VMs (IAAS) Tenir una IP estàtica Correr un codi CSHARP (functions no ens val) Conexió ODBC (dll) - per exemple per encirptar (ADF no ho fa de natiu) STAs Guardem fitxers Raw (entrada i sortida) Per fer funcionar functions contra GA necesitem una STA Guardar token GA (s'hauria de guardar al KeyVault) SQL DWH Taules staging + dimensio/fets (modeled) ADF Orquestador de dades KeyVault Storage de secrets Claus d'encriptació, users de BBDD (ADF no té cap credencial) SSAS Cubos tabulars per l'excel Excel/PowerBI
  4. Dades sensibles encriptades al DWH amb unes claus que estan al KeyVault Les conexions d'azure van encriptades Elements IR (Integration Runtime) Com que el postgre està protegit per IP, hem d'asegurar una IP estàtica (ADF es un motor al cloud amb les capacitats capades).El cloud està molt bé, pero necesites VMs (IAAS) Tenir una IP estàtica Correr un codi CSHARP (functions no ens val) Conexió ODBC (dll) - per exemple per encirptar (ADF no ho fa de natiu) STAs Guardem fitxers Raw (entrada i sortida) Per fer funcionar functions contra GA necesitem una STA Guardar token GA (s'hauria de guardar al KeyVault) SQL DWH Taules staging + dimensio/fets (modeled) ADF Orquestador de dades KeyVault Storage de secrets Claus d'encriptació, users de BBDD (ADF no té cap credencial) SSAS Cubos tabulars per l'excel Excel/PowerBI
  5. Video? Informes amb powerBI/Informes amb excel Informes website: (Google Analytics) Captación Conversión Visitas Fuentes de registro Horas Perfil cliente visitante (edad, genero, provincia,…) Informes de campañas Datos de apertura, clicks, conversiones,…. Informes APP Descargas Geolocalización Dispositivos Informes Audiencias APP: Categorías (tags videos) Consumos (nº, horas/minutos) Geolocalización Canal app/web Franjas horarias Top videos (diario, semanal, mensual)
  6. Video? Informes amb powerBI/Informes amb excel Informes website: (Google Analytics) Captación Conversión Visitas Fuentes de registro Horas Perfil cliente visitante (edad, genero, provincia,…) Informes de campañas Datos de apertura, clicks, conversiones,…. Informes APP Descargas Geolocalización Dispositivos Informes Audiencias APP: Categorías (tags videos) Consumos (nº, horas/minutos) Geolocalización Canal app/web Franjas horarias Top videos (diario, semanal, mensual)
  7. Video? Informes amb powerBI/Informes amb excel Informes website: (Google Analytics) Captación Conversión Visitas Fuentes de registro Horas Perfil cliente visitante (edad, genero, provincia,…) Informes de campañas Datos de apertura, clicks, conversiones,…. Informes APP Descargas Geolocalización Dispositivos Informes Audiencias APP: Categorías (tags videos) Consumos (nº, horas/minutos) Geolocalización Canal app/web Franjas horarias Top videos (diario, semanal, mensual)
  8. Segmentació de clients Operational Costs/Eficiencia de videos/incrementar qualitat parrilla programació Uddate information accés Raw Data - Information - Knowledge - Desitions No more intuitive (not datadriven) desitions Cruzar info del fan entre los distintos sistemas (Fan360) - es pot fer diagrama Youbora te id de user (quins videos ha vist) Es pot creuar amb Backoffice Favoritos, Watchlist, etc Campaign (anada i tornada)