MINING CRM & DATA ANALYSIS STRATEGIC CONSULTING QUALITY ASSURANCE MEDIA PLANNING & BUYING UX RESEARCH & DESIGN WEBSITE HOSTING & OPERATION SOCIAL MEDIA MANAGEMENT CONCEPT CREATION CONCEPT CREATION DEVELOPMENT FRONT-END & BACK- END DEVELOPMENT FRONT-END & BACK-END GRAPHIC DESIGN CONTENT CREATION SEO & SEM DATA MINING CRM & DATA ANALYSIS STRATEGIC CONSULTANCY QUALITY ASSURANCE MEDIA PLANNING & BUYING UX RESEARCH & DESIGN ATL PRODUCTION ATL PRODUCTION WEBSITE HOSTING & MAINTENANCE SOCIAL MEDIA MANAGEMENT MITO DEVELOPMENT FRONT-END & BACK-END MOBILE DEVELOPMENT Downloadable exercises: https://github.com/bfaludi/mETL-tutorials/archive/master.zip
warehouse specialist, IT project manager, Python expert. Built databases for Nissan, led IT development for Union Insurance, Central European University, Procter & Gamble and Profession.hu. Organizer of the Budapest Database Meetup and creator of the mETL business intelligence tool. ! Bence has more than 9 years of experience in development and project management. ! email: firstname.lastname@example.org twitter: @bfaludi Positions * Senior Database Manager @ Mito Europe * Organizer @ Budapest Database Meetup Responsibilities * Data warehouse design * Mathematical predictions * Data Cleansing & Analytics * Data Consulting * ETL & Python/Go Development * IT Project Management Downloadable exercises: https://github.com/bfaludi/mETL-tutorials/archive/master.zip
to load elective data. ‣ Inspiration coming from Brewery and Kettle. ‣ Founded by the European Union. ‣ ETL with mini-programming. ‣ Versatile loader with easy conﬁguration. ‣ Written in Python language.
new features ‣ get new users May - v0.1.4 alpha, ﬁrst public release Jun - v0.1.5 alpha, minor ﬁxes Jun - v0.1.6 beta, ﬁxes and new features Sep - v0.1.7 beta, running time reduction Jan - v0.1.8 beta, adding Jul - v1.0 stable, english documentation reached 1k downloads / month reached 1.5k downloads / month
which the data are retrieved. There are unique types, which all have their own settings. After the data is read from the source, and the transformations are completed, the ﬁnalized record gets to the Target which will write and create the ﬁle with the ﬁnal data.
of the ﬁle containing the data. ‣ Data retrieval from CSV, Database, Fixed Width Text, Google Spreadsheet, JSON, XLS, XML, Yaml. ‣ Deﬁnition of the selected type’s own settings. (e.g.: delimiter, quote for CSV, etc.)
ﬁeld possesses an unique name and a type. (e.g.: Boolean, Date, Float, Integer, String, …) ‣ Each ﬁeld describes transformations. (e.g.: Title, UpperCase, Homogenize, Map, …) Hint: If any of the ﬁelds is not necessary for the process, it does not have to be included unless we want it to appear in the output. Those ﬁelds in which we would like to write values must be listed, as during the process there is no possibility to add new ﬁelds.
a possibility to deﬁne a migration ﬁle and to generate a new migration ﬁle. ! The metl-diﬀerences script is able to compare migration ﬁles and write out the keys of those elements that are to be deleted / updated / added / unchanged during the migration. !