{"id":2592,"date":"2019-10-23T07:45:08","date_gmt":"2019-10-23T05:45:08","guid":{"rendered":"https:\/\/beta.forwardkeys.com\/handbook-terminology\/"},"modified":"2024-12-04T13:06:11","modified_gmt":"2024-12-04T12:06:11","slug":"handbook-terminology","status":"publish","type":"post","link":"https:\/\/forwardkeys.com\/es\/handbook-terminology\/","title":{"rendered":"Handbook – Terminology page"},"content":{"rendered":"
\n

This page aims at defining main concepts we all manipulate internally, within the company. You are required to make
\nyour best effort to use this nomenclature when interacting internally (written documents but also orally).<\/p>\n

Solution concepts<\/h3>\n\n\n\n\n\n\n
a product<\/td>\nA well-defined item offered off-the-shelf to our clients through a license. It can be a
\ngeneric product<\/strong><\/em> (Ex.: current Gen1 application, the FK travel API, \u2026) or a
\nfocus product<\/strong><\/em> (Ex.: DMO product)\u00a0we build to address a specific segment (DMO).In order to be proficiently developed, a product requires a Product Owner (PO).<\/em><\/td>\n<\/tr>\n
a focus product<\/td>\nA product, offered off-the-shelf to our clients of a specific sector<\/strong><\/u >, through a license, that consists of a dedicated web application to address their specific business needs. <\/u><\/td>\n<\/tr>\n
an ad hoc solution<\/td>\nSomething built specifically for a client or a group of clients.<\/p>\n
    \n
  • Most of these solutions will be implemented by our data scientists, in autonomy, using the data factory.<\/li>\n
  • Standardized generic solutions should be preferred vs bespoke since they can scale to a wider audience of
    \nclients.<\/li>\n
  • According to our strategy, these ad hoc solutions are considered as necessary to better understand a
    \nsegment business needs. But they should not be considered the default solution to address our clients\u2019
    \ndemands.<\/li>\n
  • Namely: data exports, reports, simple custom dashboards, alerts and custom API.<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n
a service (or professional service)<\/td>\nA client consisting of experts-days, which could be researcher-days, analysts-days or insights team-days.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Behind-the-scene concepts<\/h3>\n\n\n\n\n\n\n\n\n\n
a business capability<\/td>\nA functionality offered to clients through one of our product or ad hoc solution (Ex.: TAM forecasts,
\ncapacity) Currently, our main business capability is made of TAM+TAMFOR.<\/td>\n<\/tr>\n
an operational capability<\/td>\nA capability provided to internal teams to enhance our operational excellence (Ex.: continuous integration,
\ninfrastructure virtualization).<\/td>\n<\/tr>\n
a data nugget<\/td>\nA piece of our data, coupled with expert algorithms, which helps build an answer to a business question<\/p>\n
    \n
  • It leverages our business capabilities and data we have sourced and makes the most of our business
    \nexpertise and data science capabilities. Once implemented, the data nugget is delivered through one of our
    \nproducts and\/or an ad hoc solution that fits clients\u2019 business needs and consumption habits.<\/li>\n
  • An example of a data nugget would be: \u201cForecasted number of Chinese that will be transiting through AMS
    \nairport for more than 2 hours between dateA and dateB, and will fly back directly to China\u201d.<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n
a component<\/td>\nA part of the technical architecture that allows the delivery of products, ad hoc solutions and services
\nExamples of components include the reusable pieces of UI that enables us to build custom interfaces, the
\nmicro-service framework that allows backend agility or the data lake which is the data storage layer of our
\nplatform.<\/td>\n<\/tr>\n
a module<\/td>\nA subset of a component (Ex.: Data governance is a module of the Data lake).<\/td>\n<\/tr>\n
a data source<\/td>\nA set of raw data provided by a FK business partner that will enable our business capabilities (Ex.: MIDT
\ndataset).<\/p>\n
    \n
  • Data sources include \u201cstandard\u201d travel datasets and any dataset provided by clients or third parties (Ex.:
    \nsocial media, \u2026).<\/li>\n
  • Can be provided to us through a file, a feed or any other technical mean<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n
an enabler<\/td>\nan operational capability which is a foundation for agility \/ performance \/ \u2026 --> (Ex.: Continuous
\nIntegration)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

The Gen2 platform concept<\/h3>\n\n\n\n
(Gen2) platform<\/td>\nThe (Gen2) platform\u00a0is the way we will deliver our value to our clients.<\/p>\n

It is made of different components and products, aiming at serving our clients in a versatile, adapted and
\nevolutive manner.<\/p>\n

It unleashes our data science capacities by providing ubiquitous access to data, enables us to fully
\nleverage cloud technologies insofar it makes sense, and provides a modern underlying technology stack both
\nat front-end and back-end levels, with specific focus on quality, scalability and time-to-market.<\/p>\n

Unlike Gen2, Gen1 is the current power application, built over the last 8 to 10 years, that brought
\nForwardKeys to where it is today. It essentially consists in \u201cThe FK application\u201d and \u201cThe FK API\u201d.<\/div>\n

Main users of\u00a0the platform are:<\/p>\n

    \n
  • Of course our clients, through various products, or because they are provided with ad hoc solutions.<\/li>\n
  • Market analysts, who use the data factory to build and deliver ad hoc solutions to our clients.<\/li>\n
  • Data scientists, who design and test new models to extract value from data and enhance both our products
    \nand ad hoc solutions accuracy.<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    Focus Products of the Gen2 platform<\/h3>\n\n\n\n\n\n
    DMO<\/td>\nThe focus product, offered off-the-shelf to our DMO clients through a license, that consists in a dedicated
    \nweb application to address destinations specific business needs.<\/td>\n<\/tr>\n
    Travel Retail<\/td>\nSame as above for Travel Retail clients. Yet to be defined.<\/td>\n<\/tr>\n
    Hospitality<\/td>\nSame as above for Hospitality clients. Yet to be defined.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    Generic Products of the Gen2 platform<\/h3>\n\n\n\n\n
    the FK power application<\/td>\nThe product, offered off-the-shelf to our clients through a license, that consists in the BI power tool
    \nenabling them to navigate and analyze our data Note: currently, this is what is referred as \u201cGen1\u201d, and would
    \nevolve in the future.<\/td>\n<\/tr>\n
    the FK travel API<\/td>\n-shelf to our clients through a license, that consists in a standard API, exposed --> with a dedicated
    \ngovernance.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    Architecture macro-concepts<\/h3>\n\n\n\n\n\n\n\n\n\n\n\n\n
    the front-end<\/td>\nPart of the software architecture that consists in interfaces exposed to users (Ex.: the DMO product user
    \ninterface).<\/td>\n<\/tr>\n
    the back-end<\/td>\nPart of the software architecture that consists in all components laying behind the scene and essentially
    \nserving the front-end (Ex.: the query engine).<\/td>\n<\/tr>\n
    the data hub<\/td>\nThe layer enabling both data scientists and products \/ ad hoc solutions to make the most of data<\/p>\n
      \n
    • It unifies distributed storage locations, including cloud storage, on-premise, etc.<\/li>\n
    • The data hub encompasses the data lake, the data factory and the data lab.<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n
    the data lake<\/td>\nThe component providing Big Data storage and distributed computing capabilities, that will enable both data
    \nscientists and products \/ ad hoc solutions to access and make use of the data.<\/td>\n<\/tr>\n
    the data factory<\/td>\nThe component enabling our applied data scientists to deliver ad hoc solutions.<\/td>\n<\/tr>\n
    the data lab<\/td>\nThe component enabling our data scientists to test and train models to enhance our business capabilities.<\/td>\n<\/tr>\n
    raw data<\/td>\nData sources made available \u201cas-is\u201d in the data lake (Ex.: MIDT data)<\/td>\n<\/tr>\n
    blue data<\/td>\nThe enrichment of data sources that makes them consistent from a business standpoint (Ex.: on-the-book data)<\/p>\n
      \n
    • It is pre-processed raw data which are then stored in the data lake and made available to data scientists
      \nfor either R&D or ad hoc solutions building.<\/li>\n
    • Depending on the raw data, blue data may require more or less layers of processing, enrichment and
      \ntransformation.<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n
    micro-services<\/td>\nThe small pieces of the application layer in charge of certain processes used by front-ends (Ex.: back-office
    \n\u201cservice order\u201d micro-service).<\/p>\n
      \n
    • Some micro-services only expose internal services to other micro-services, rather than to front-ends.<\/li>\n
    • Micro-services are typically deployed independently and can easily accommodate scalability requirements.
      \nMicro-services are typically packaged and deployed as a container and typically require the use of an
      \norchestrator.<\/li>\n
    • As independent pieces of software, micro-services contribute to better quality (testable independently)
      \nand a more agile\/devops software life-cycle.<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n
    API<\/td>\nApplication Programming Interface: the\u00a0upper layer of the back-end that exposes some data and processes of the
    \nplatform, in the shape of micro-services, for front-ends and clients The FK Travel API is only a subset of
    \nthis API, open to clients and partners, sold as a product through a license, and subject to proper governance.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    Advanced terms and concepts<\/h3>\n

    This list features more advanced terms that product people will be likely to use:<\/p>\n\n\n\n\n
    (data) views<\/td>\nProcessed data, stored in dedicated databases, that will serve specific needs of data scientists, insights
    \nanalysts and products \/ ad hoc solutions(Ex.: pre-processed capacity data for Venice departing origin).<\/td>\n<\/tr>\n
    an ETL<\/td>\nStands for Extract-Transform-Load. A generic term used to describe processes used to process data within the
    \ndata lake and prepare views. Those processes can be strictly ETL, but also variants or other kinds of
    \nprocesses such as ELT. Nevertheless, we will collectively name those \u201cETL\u201d. Amongst other features, ETL
    \nencompass data quality control to make sure computed data is reliable.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

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