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Data Powered - meetup intro
- 1. Becoming Data Powered Achieving success with data
- 2. Business, 800: This type of companies grows exponentially year over year, by leveraging information gathered in existing verticals, to rapidly enter and become dominant in unrelated verticals...
- 3. What’s a DATA COMPANY? Data is the fuel for hypergrowth
- 4. Data is the world’s most valuable resource Be as them... and prosper. What does it takes?
- 5. DATA AWARE collects and uses data to power some app features and to inform business decisions Data is the fuel of hypergrowth DATA DRIVEN systematically uses quantitative methods to drive business decisions and key app features DATA POWERED prioritizes growing the value of its data, managed as a core asset that apps are simply a mean to monetize APPS DATA
- 6. What makes a data company? Data readiness, democratization and maturity
- 8. Data Validation Data Collection Data Engineering Perf & Cost Management Process ManagementConfig Management Monitoring Access & Serving Infra Analysis Tools Data Validation Data Collection Data Engineering Perf & Cost Management Process ManagementConfig Management Monitoring Access & Serving Infra Analysis Tools Application / Technology
- 10. Organization Teams with the necessary skill sets, structure, culture and accountability model Monetization A concrete, committed-to plan to derive business advantage from data Data quality Data that is discoverable, structured, documented and trustworthy Technology Environments, tools and processes enabling scaling up to more datasets and more data users Protection Processes and defences to minimize the legal, compliance and competitive risk of data Data maturity dimensions
- 11. Become...
Editor's Notes
- It’s an $800 billions question...
- From The Economist, June 2017: “The world’s most valuable resource is no longer oil, but data”
- This is what data activities, conceptually, looks like for many. Source data, code smart analytics or algorithms, get business insight or valuable features. When it comes to a real data application, however, there is a lot more to it...
- You have to add a number of data reformation, preparation and quality management work for data to start being valuable. Then infrastructure need to be built to actually deliver the expected value to the business or the customer. And finally the whole architecture needs to be operated at quality and scale to ensure consistent and economical delivery. But in reality, even all this technology remains a small part of creating a successful business with data... [Framing from D. Sculley & al., Hidden Technical Debt in Machine Learning Systems, NIPS 2015]
- Building a robust product and experience structure, that understands the nature and needs of a data product, is needed to ensure the continued quality and fit for purpose of the application. Monetizing its value proposition takes a good understanding of (and alignment with) the market for such value, as well as day to day product and business operation capabilities that know how to use data and manage its value. And finally none of that can happen without the right organizational structure and talent, as well as a precise and risk-aware data protection methodology.
- [Framing drawn from Thomas C. Redman, HBR: https://hbr.org/2018/10/5-ways-your-data-strategy-can-fail]