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Costs of getting involved in the data economy

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- Péter Csillag - Starschema and VirtDB co-founder, CEO -

IVSZ | EuDEco project
Data Economy Conference
Budapest, 2018. 01. 31.

Published in: Data & Analytics
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Costs of getting involved in the data economy

  1. 1. COSTS OF GETTING INVOLVED IN THE DATA ECONOMY.
  2. 2. In God we trust; all others bring data. W. Edwards Deming
  3. 3. STARSCHEMA’S DATA 0 20 40 60 80 100 120 140 160 180 200 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 0 500 1000 1500 2000 2500 3000 Growth Continues New HQ, strengthened back office functions, „Fastest 5000 in EU” by Inc.com. Founded Organic Growth Expanding customer- base in traditional BI Expanding Services New business model: SLA-based support and DevOps for BI Expanding Technologies Investment in new generation BI, Big Data technologies: Talend, Tableau, Greenplum Growth Accelerates Tech investments started to pay off as new gen techs becoming mainstream Overseas Expansion Broadened client base amongst Fortune 500 companies in the US.. Revenue Staff Q4 2017 The next big things Deloitte Fast 50 CE, AI, ML, Cloud, Dev. Projects
  4. 4. Image Monte Biz Company THE DECISIONS TO MAKE BECOME DATA DRIVEN „My actions will be compelled by insights gained from data” „I need solution to utilize (manage and analyze) data to make right decisions” COST: your time to think and discuss
  5. 5. DATA AUDIT DATA ASSETS, PROCESSES, COSTS, BENEFITS What is the practice of data management at your organisation? Who are the people managing or consuming data? What is the value they generate? Measure knowledge, experience, flexibility, maturity of culture. Technology Data Assets Highlights Cost of storing and processing Acceptable latency Variety of consumption Processes People & COST: 10-200k $ internal and external
  6. 6. INCREASE PROFIT RATIO Sell more, marketing effectively, spend less, increase effectiveness, improve satisfaction ENGAGE PEOPLE Align personal career goals with company needs, avoid personal-only benefits. BECOME TRENDSETTER Implementing best practices and improving processes of data utilization will show you the way. SET GOALS INCREASE revenue DECREASE cost Career in data analytics Gain Competitiveness I MEAN REAL GOALS COST: 5-25k $ internal and external consultants
  7. 7. CHOOSE SOLUTION Based on your current status, goals and capacities. Single-vendor vs best-of-breed Cloud vs on-premise (or hybrid) Emerging vs regnant Self-service vs IT dependent TECH. EVALUATION Evaluate vendor and technology Focus on team and culture fit Spend time & money RUN PoC-s COST: 25-75k $ internal and external
  8. 8. IMPLEMENT AND OPERATE Implied organizational, operational and regulatory changes will cost more than expected COST: 200-5000k $ internal and external, license, HW Buy or rent (pay-per-use) Educate, evangelize Run agile, stay focused Manage change (organisation, processes, goals) IMPLEMENT Set SLAs for support and maintenance Security, privacy, compliance (GDPR, SOX and their friends) Governance, quality Keep improving people, processes, technology OPERATE, GOVERN, IMPROVE COST: 50-500k $ / year
  9. 9. CONSIDER CLOUD You will never be that secure and scalable on-premise Platform Data Storage Data Processing Serverless applications Container management Hybrid infrastructure SERVICES TECHNOLOGIES COST: 15-30% less compared to on-premise TCO
  10. 10. Data Consumption EXAMPLE: REAL-TIME ANALYTICAL DATA LAKE Mirror Common model Speed layer Source systems Data Ingestion Data lake Visualization Data science ML / AI STREAM CDC & batch CDC & batch Billions Of Transactions processed daily 50k+ Users with 5K concurrent users 1PB+ Financial and operational data 99.99% Availability <2 mins Refresh cycle for all ERP/ES systems 100+ Data-centric application <2s Response time COST: ~1M $ Implemented in one year
  11. 11. EXAMPLE: DATA LAKE FOR FINANCIAL OPERATIONS AI-driven automation - based on horizontally integrated, real-time, financial data lake. Financial Scorecards AI-driven Reconciliation Automation Saving ~15FTE (1MM $/Year) Analytical Products Platform agnostic common financial data model (SAP, Oracle ERP, etc) Threading – Drill across ERPs Stream-line Financial Closing activities ERP Federation Single data store across Enterprise Financial (Planning, ERP, CRM, Treasury) and Operational data sources Single source of truth COST: ~1.5M $
  12. 12. CONTACT US info@starschema.net Starschema.net @starschemaLtd Facebook/starschema WE PLAY BIG DATA.

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