IRB CIO MEETING 7 IRB IT HEAD OFFICE

IRB CIO MEETING #7 IRB IT HEAD OFFICE 18/05/2018

Data Stream – YTD Assessment & 2019 Objectives YTD Assessment 2019 Objectives • • To setup dedicated data team specialists in each entities • To put in place data hub foundations everywhere • To bootstrap use cases implementations with data hub Achievements • • • 3+ data ring session 6+ data Workgroups (mainly on data science, data model, data architecture, data management) Data manifesto Data blog to share content (accessible from all sites) Common project list in progress Next data ring seminar in TEB in June 18 (TBC) Impediments • • Creation of a ring of various skilled data members 10+ data meetings inside the ring since Feb 18 Agreement to work together but ring activities need higher local priority compared to BAU (best effort today). Need to enlarge number of members to create "channels" by "industry" (data science, architecture…) to facilitate exchanges by network of peers. Tooling: Visio not accessible everywhere, Slack / Web. Ex blocked in some entities, Skype not effective… Belief • • • Necessity to change scale to accelerate transformation Need to have a strongest local positive directionality Need to raise significantly priority by having dedicated budget (and dedicated FTE) in each entities – to be done in 2019 budget request.

For 2019, a dedicated 15 FTE core team to bootstrap data hub implementation and protected via a dedicated budget is required in each entities Resources progressively ramp-up (15 FTE/Y 18) Technology Training n n n n n 1 PM 2 Data Architect 3 Data Engineer 2 Banking / Analytics SME 2 Platform manager 1 Data Controller 1 Release Manager 1 Data Viz Engineer 2 Data Scientist Business (Tbd) n License n Tools n Hardware n € 2 M n Training & Travel expenses n TBD Digital Cloud 3000 MD Data 15 FTE The 2019 budget we required is the minimum we estimate needed to initiate data hub activities in each countries. Role PM Business Analyst SME 15 FTE of which 4 to 5 can be shared in a core foundation team between Data, Cloud and Digital (15 FTE total). Activities • • Operation and management of the program, budget, roadmap, issues, communications, escalations Gathers requirements, identify and document the data sources as required for loading into the Raw layer of the target environment. Assist in the mapping process by identifying the correct source data and associated rules for mapping raw data to the normalized layer Data Viz Engineer • Integrate people responsible for the design and development of traditional BI dashboards enriched by new analytics capabilities Data Scientist • Perform data analysis on data stored in data hub to solve a variety of business problems, optimize performance or reduce risks via statistical technics (e. g. Machine Learning…). Data Engineer • Responsible for the development of detailed design of data and integration flows in batch mode and real time Data Architect • Responsible for the design of the model components which are used in the normalized and data access layers and creation of code (SQL and other languages on HDFS) which is used in the integration of data from the raw to normalized layer of the architecture, and from the normalized to the data access layer Provide architecture guidance for solution implementation. Specializes in big data technologies • Data Controller • Tests components of the delivered solution to ensure that the component meets requirements, is robust, stable and produces expected results Release Manager • Coordination and scheduling of code /product releases into testing and production environments. Ensures that there are no conflicts in deployment. Platform Manager • Responsible for optimal configuration of platform, network components to meet security and performance requirements IRB & BOW - Data Strategy Deck | March 2018 |

Fintech Mobile Front Customer Journey Transv. Capabilities Data Science API Stream Data Hub Data Lake Data Management Digital Platform Data Dev. Ops Cloud Asset migration SLA Obsol. Hosting Ops

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