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How Can You Calculate the Cost of Your Data?


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Today, self-service, Cloud and big data technologies make new data preparation capabilities necessary…and possible. But, we've all been through the hype cycle and know the trough of disillusionment can come on hard and fast.
Organizations have been trying to solve the data quality problem and democratize insights for years spending millions of dollars and dedicating an increasing amount of resources to manage and govern the data.  The result? Everyone is still looking to solve the problem.
Data preparation offers a new paradigm, but how can you avoid another round of minimal business impact? We’ll review a true data ROI model that helps organizations understand the value of existing versus modern data management architectures.

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How Can You Calculate the Cost of Your Data?

  1. 1. How Can You Calculate The Cost Of Your Data? September 20, 2016 Data Prepared By Business, Scaled For Business
  2. 2. Maximize Revenue – Stay Competitive Airlines aggregate a variety of data to run and apply dynamic seat pricing. Allowed airlines to step out of pricing wars and link pricing to demand and flyer profiles. Image Source:
  3. 3. Are you able to demonstrate business ROI inhibiting data investment?
  4. 4. By 2017, 33% of the largest global companies will experience an information crisis due to their inability to adequately value, govern and trust their enterprise information. Source: Gartner
  5. 5. • Missed Revenue • Customer Churn • Inaccurate Forecasts • Hidden Fraud • Compliance Fines • Inaccurate Inventory • Inefficient Logistics and Fulfillment • Lack of Worker Productivity
  6. 6. “Too often, companies execute big data projects as bottom-up projects integrating data sources with no clear business objective or goal in mind. “ - Noel Yuhanna, Principal Analyst, Forrester Research
  7. 7. Lost time to business ROI Big box retailer stands up Hadoop distro to modernize data center and accelerate integration. Data lake created without business use cases and involvement Takes a year and a half to identify and run pilot scenario for for loyalty analytics.
  8. 8. Data pipelines are for systems, not people We start with rich data… Conversations Relationships Experiences We process data to fit systems… We lose all meaning. Data in the RawDeconstruct Disassociate Atomic
  9. 9. Does this sound like you? • Traditional tools requires a lot of installation and set up – slows down starting up a project • Cannot work on full/large volume of data – need to sample data • Based on SDLC process – write code, package and then run it. Not self-service. • Cannot see data easily while working on it • Cannot query fast enough • Cannot repeat my operations again and again • Cannot make changes easily and quickly Source: Paxata Financial Services Customer
  10. 10. What are your biggest challenges when preparing data?
  11. 11. Get a handle on your cost of data
  12. 12. Right Fit Your Data Management Strategy Prescriptive Analytics Competitive BI Informed Transactions Collect Exploration / Discovery Democratized 0% 100% %DataUsed Time to First Value HighPeriodic Data Interaction Months <Week Accountability IT Driven Business Driven
  13. 13. Model Your Return On Data Business Outcomes • Time to first business value – upside or de-risk • Increased productivity – go deeper with data • Expanded capabilities – scale intelligence Metrics to track • % data used • Time to understanding • Data lake adoption • Decrease/Increase resources • Responsiveness • Retire or decrease technology service
  14. 14. Measure Your Return On Data – Auditing Firm • Over 1000 analysts who spent over 50% of their time cleaning, organizing, and merging data so that the company could complete audits. • Missed Opportunity: Concentrating on data cleansing rather than increasing the number of audits that could be performed cut into additional revenue potential. • Measure: Assumption - move 40% off data cleansing • Result: 27% increase in revenue generating capacity
  15. 15. Calculate ROI
  16. 16. ROI – Resource Hours
  17. 17. ROI – Added Resources
  18. 18. ROI - Productivity
  19. 19. “Prior to Paxata, we struggled with cumbersome data prep processes that were impossible for us to audit or automate – our only approach was to just throw more bodies at the problem.” - Chief Data Officer, Financial Services Firm
  20. 20. Business Analyst Chief Analytics Officer Chief Data Officer You know good data when you see it Engage with data yourself Access data anywhere Understand the meaning of the data Prepare data for analysis Collaborate with your team Share your data You deliver meaningful information to drive business outcomes Power an insight driven business Unlock data value quickly Understand what data works Make data actionable Capture data hygiene Enable collaboration You enable the business to get value from all the data Scale data to the enterprise Get faster return on data investment Deliver a comprehensive service Scale up and out Deploy data and pipelines faster Govern and secure data The Paxata Difference
  21. 21. Data Prepared By Business, Scaled for Business Value Agility Business IT Repeatable Iterative/Discovery IT Analyst Data prep tools IM Solutions Business Information Platform BI Solutions Intelligence At Scale Paxata connects information to business at scale
  22. 22. Integration Quality Enrichment Governance Semantic Catalog* and Library Consumer Experience, Exploration & Collaboration Connectivity Framework In-memory, parallel, pipelined, columnar, distributed data transformation engine Automation Administration Security DATA 3rd partyPackaged Apps Databases/EDW Flat filesHadoop/Big Data *: Roadmap USE CASES Custom AppsBI & Analytics Transactions Data-as-a-ServiceData Markets Developers Data Scientists Analysts Information Workers Collaboration Paxata Business Information Platform™
  23. 23. Key Takeaways • Build an ROI model tuned to strategic, growth, efficiency and risk • Model metrics on data accessibility, interaction, accountability and time to value • Address business outcomes that are personal, operational, and organizational • Build an information platform that translates tribal knowledge into organizational IP
  24. 24. Visit Request a demo and get a free data prep value assessment!