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Big Data and Cloud Compu0ng technologies applied to the energy sector: from buzzwords to market
op0miza0on through an SaaS solu0on
Dogma Enterprise project
Data Philosophy. Best prac0ces.
Presenter Alessandro Piacen0ni, Cer0fied FRM Email: firstname.lastname@example.org Mobile: +39 3926788834
Defini0ons from Wikipedia, the free encyclopedia
§ So#ware as a Service
SaaS is a soSware licensing and delivery model in which soSware is licensed on a subscrip0on basis and is centrally hosted. It is some0mes referred to as "on-‐demand soSware”. SaaS is typically accessed by users using a thin client via a web browser.
§ Big Data Big data is a term for data sets that are so large or complex that tradi0onal data processing applica0on soSware is inadequate to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualiza0on, querying, upda0ng and informa0on privacy.
§ Cloud Compu7ng Cloud compu0ng is an informa0on technology paradigm, a model for enabling ubiquitous access to shared pools of configurable resources (such as computer networks, servers, storage, applica0ons and services), which can be rapidly provisioned with minimal management effort.
§ Electricity and Gas deregulated marketplaces
In economic terms, electricity is a commodity capable of being bought, sold, and traded. An electricity market is a system enabling purchases, through bids to buy; sales, through offers to sell; and short-‐term trades, generally in the form of financial or obliga0on swaps. Long-‐term trades are contracts similar to power purchase agreements and generally considered private bi-‐lateral transac0ons between counterpar0es.
§ Hybrid Cloud A hybrid cloud is an infrastructure that includes links between one cloud managed by the user (typically called “private cloud”) and at least one cloud managed by a third party (typically called “public cloud”). Some hybrid clouds offer only a connec0on between the on premise and public clouds.
§ Microservices architecture
Microservices is a variant of the service-‐oriented architecture (SOA) architectural style that structures an applica0on as a collec0on of loosely coupled services. The benefit of decomposing an applica0on into different smaller services is that it improves modularity and makes the applica0on easier to understand, develop and test. Microservices-‐based architectures enable con0nuous delivery and deployment.
Secng the scenes
How many Trading & Risk professionals?
How many power & gas SMB
How many forecas7ng experts?
How many data scien7sts?
The Dogma project
The Dogma project began with the intui0on from a pool of professionals with outstanding experience in consul0ng and delivering advanced IT solu0ons for Energy and U0li0es top 0er players. Problem Regulatory and business pressures are squeezing all the margins available for small and medium par0cipants in the Electricity and Gas marketplace. Opportuni7es -‐ various na0onal and interna0onal regulatory authori0es push for Trading and Risk Management processes
standardiza0on and improvement -‐ Cloud Compu0ng and Big Data informa0on technology spaces during the last 5 years undergo a wondrous
The idea -‐ Inves0gate on the possibility to serve small and medium businesses releasing a Cloud based, data driven, best prac7ce tailored So#ware-‐as-‐a-‐Service solu0on to support their Trading & Risk Management and Forecas7ng processes
-‐ Provide the various services providers (for example market data, forecasted prices, forecas0ng algorithms providers) with a standardized solu7on to “plug in” their solu7ons and easily serve their audience
Electricity market challenges…an extract
§ Increasing regulatory pressure
§ Imminent release of disrup7ve technologies
§ Need for real-‐7me analy7cs on massive amount of structured and unstructured data
§ Fragmented services providers environment
Aiming to increase market stability and secure power and gas ecosystems, both na0onal and interna0onal regulators intensified pressure on market par0cipants to consistently manage and disclose exposure and physical
§ Power accumulators, IoT, electric vehicles § Big players investments place to develop on in-‐
house solu0ons leveraging the latest technologies
§ Structured and unstructured business data advanced management
§ Real 0me data, measurement and informa0on needed to strive the business
The market arena consists of plenty medium, small and very small businesses providing customers news feeds, market data, prices forecas0ng, forecas0ng algorithms, pricing models and other similar services in an unstructured and decontextualized manner
§ SMB are required to quickly adapt business processes and underlying technologies to con0nuous changes to the business/regulatory framework
§ Disrup0ve technologies (i.e. power accumulators, IoT, electric vehicles) need advanced automa0on to be governed
§ Investment is in-‐house solu0ons going to increase the digital divide between big players and small/medium businesses
§ Manual collec0on of market data, measurements and business informa0on must be replaced by fully automated solu0on to focus on core business
Each market par0cipant is requested to setup and maintain costly processes to integrate this services while collect, histories and normalize business relevant data
Dogma Enterprise: SaaS solu0on with embedded analy0cs
Dogma Enterprise: SaaS solu0on with embedded analy0cs
Dogma Enterprise: target func0onal coverage
§ Minimal implementa7on effort and upfront costs
ü Shortened ini0aliza0on 0me (4/6 weeks) ü Reduced ini0al investment cost compared with similar On-‐premises ü IT infrastructure managed remotely ü Minor IT involvement required ü …
§ Minimal on-‐going cos