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GoodData - Towards a cloud-based BI Platform as a Service


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GoodData: Customer Analytics Through Cloud BI …

GoodData: Customer Analytics Through Cloud BI

Point of View: End-User Case Study
Session Track: Enterprise Ready Clouds: Realistic Strategies

Towards a cloud-based BI Platform as a Service

Burton Group Catalyst Conference Europe 2010, Prague, June 21 – 24 2010

Published in: Technology, Business
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  • This is now a part of history, for updated GoodData platform statistics, please see 'Software Engineering in the Age of SaaS and Cloud Computing' from August 2013.
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  • 1. Customer!Analytics!Through!Cloud!BI Towards!a!cloud"based!BI!Platform!as!a!Service Prague, June 21 – 24 2010 Jaroslav Gergic
  • 2. Jaroslav Gergic VP Engineering, GoodData @gooddata 2
  • 3. GoodData’s!Founding!Vision:!Customer!Analytics • The center of gravity is gradually shifting from ERP to CRM • The BI activities should be centered around Customer!Analytics as opposed to General Ledger • Customer Analytics use cases and data are fundamentally different than ERP data and use cases. 3
  • 4. Customer!Analytics:!Flexibility,!Versatility!and!People Customer Analytics use cases and data are fundamentally different ... • constant innovation – the dynamics of everchanging needs – ad hoc analysis, hypothesis testing • decentralization – driven by line of business or department – self-service, broad user base • disparate external data sources – impossible to enforce strict data quality – cross-source analysis is the key use case • variable lifespan – from perpetual to single purpose – low risk, time-to-value 4
  • 5. Customer!Analytics!vs.!Cloud!Architecture • “KPIs” of a Customer Analytics: – time to value – risk level (initial price + operating costs) – agility, flexibility, usability • Computing cloud – an ideal environment for a BI deployment because of the low-utilization vs. high- peak-performance-demand nature of BI – allows to increase HW resource utilization • BI Platform as a Service – tools and APIs reducing time-to-value from months and weeks to days or hours – takes care of all IT operations aspects – takes care of customer support 5
  • 6. Building!the!BI!Platform!as!a!Service!in!the!Cloud “Computing cloud is an ideal environment for a multi tenant BI deployment because of the low- utilization vs. high-peak-performance-demand nature of BI” • The traditional BI tools are not suitable for cloud deployments – they are too complex on the upstream side – they are not multi-tenant • Developing a complete generic cloud-ready BI stack from scratch is a substantial challenge due to the enormous breath and depth of the BI domain – ETL, modeling, metrics, reports, dashboards, collaboration, security – Large data volumes, unpredictable peak loads 6
  • 7. GoodData!Cloud!BI!Platform • Open standards-based APIs – HTTP, REST, FTP • Rich user experience – JavaScript, AJAX, interactive charts • Flexible application layer – a new release every two weeks • Robust ROLAP engine – MAQL (Multi-dimensional Analytical Query Language) – Fluid data model (Attributes, Facts, Metrics, Hierarchies) – highly efficient MAQL-to-SQL decomposition and caching – suits both operational reporting as well as ad-hoc analysis 7
  • 8. GoodData!Cloud!BI!Platform!–!Core!Concepts • Project = data mart – a unit of management and distribution – deployment: as easy as “New File” • User Information – security boundary – a “walled garden” • Project Data – raw data: numbers and classifications • Project Metadata – metrics, filters, reports, dashboards – LDM, PDM, operational state – event trace, audit log • Cached Data – pre-aggregated data – materialized slices and dices 8
  • 9. GoodData!Cloud!BI!Platform!–!Multi!Tenant • Multi-Tenant Platform – born on Amazon Web services – stateless web application layer – session-less processing layer – redundant storage • Horizontal Scaling – a pre-configured node type for each role – shared-nothing architecture between nodes of the same type – nodes of each type can be provisioned on!demand independently of others • Horizontal Partitioning – first-level driven by project separation – with columnar storage second-level partitioning not needed ~100M rows 9
  • 10. Operating!Cloud!BI!Platform!=!Continuous!Innovation Statistics as of June 2010: • 2,713 projects, 1,344 dashboards – 19,086 reports, 41,213 metrics • 3.5K+ reports run per business day – report calculations, incl. dashboards • 5M platform events a day – in the audit events trail While continuously innovating: • production release ~ 2 weeks – 10 releases so far in 2010 • without adverse impacts on uptime 10
  • 11. Thank!You 11