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z8Cl2vcMkc#)&(>a7*8b`skx~T66_Xq1ElJ**Ln*xGMs2+M{`CVu!RjY02D#cfC5uk zO?kIUYuzkvMux*{Sb@nG8N4@Q1esEtkyw2!VCt6#V$+?=wmeKx>5VR$hzy@k#xg)!RXr2yCw(&q`kmiK Date: Sat, 19 Sep 2020 12:20:04 -0500 Subject: [PATCH 02/57] Update README.md --- README.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 57872d1..e175a3a 100644 --- a/README.md +++ b/README.md @@ -35,7 +35,8 @@ ### Опросы - [Предварительный опросник](https://docs.google.com/forms/d/e/1FAIpQLSdf2jXxfyBTcvJEJz072qKXLYhj_0x5kYbws03OeQzVSyN19A/viewform). - [Опросник после занятия 1](https://docs.google.com/forms/d/e/1FAIpQLSe1tHiqGt066XDz_sq4xy3yLCzG-lgjPP9Cw5QCeQWH6UcJQw/viewform). -- [Опросник после занятия 2](https://docs.google.com/forms/d/e/1FAIpQLScd0K3BG_5EIkvGm_CLSD8fu59UMbA6mZWtmCTRHJeUhfvS0g/viewform). +- [Опросник после занятия 2](https://docs.google.com/forms/d/e/1FAIpQLScd0K3BG_5EIkvGm_CLSD8fu59UMbA6mZWtmCTRHJeUhfvS0g/viewform). +- [Опросник после занятия 2](https://docs.google.com/forms/d/e/1FAIpQLScUyN2mpESKogCZe0VimZ3MVTAi7-D_jnZwVbgCLw5diyGxNQ/viewform). ### Оценка за курc From e6a84394eba4ddb5589a0b90158e905d574e70bd Mon Sep 17 00:00:00 2001 From: Irina Radchenko Date: Sat, 19 Sep 2020 12:20:50 -0500 Subject: [PATCH 03/57] Fix a typo --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index e175a3a..aa2c22d 100644 --- a/README.md +++ b/README.md @@ -36,7 +36,7 @@ - [Предварительный опросник](https://docs.google.com/forms/d/e/1FAIpQLSdf2jXxfyBTcvJEJz072qKXLYhj_0x5kYbws03OeQzVSyN19A/viewform). - [Опросник после занятия 1](https://docs.google.com/forms/d/e/1FAIpQLSe1tHiqGt066XDz_sq4xy3yLCzG-lgjPP9Cw5QCeQWH6UcJQw/viewform). - [Опросник после занятия 2](https://docs.google.com/forms/d/e/1FAIpQLScd0K3BG_5EIkvGm_CLSD8fu59UMbA6mZWtmCTRHJeUhfvS0g/viewform). -- [Опросник после занятия 2](https://docs.google.com/forms/d/e/1FAIpQLScUyN2mpESKogCZe0VimZ3MVTAi7-D_jnZwVbgCLw5diyGxNQ/viewform). +- [Опросник после занятия 3](https://docs.google.com/forms/d/e/1FAIpQLScUyN2mpESKogCZe0VimZ3MVTAi7-D_jnZwVbgCLw5diyGxNQ/viewform). ### Оценка за курc From a02b7429b90af9b0ff2765e394437995e7261ab5 Mon Sep 17 00:00:00 2001 From: Irina Radchenko Date: Thu, 24 Sep 2020 19:42:25 -0500 Subject: [PATCH 04/57] Update README.md --- tasks/README.md | 10 ++++++++-- 1 file changed, 8 insertions(+), 2 deletions(-) diff --git a/tasks/README.md b/tasks/README.md index 0f27176..6a05265 100644 --- a/tasks/README.md +++ b/tasks/README.md @@ -1,3 +1,9 @@ -#### Здесь лежат описания всех заданий по Адаптационному курсу +Здесь лежат описания всех заданий по Адаптационному курсу. -Оценка за курc: +### Оценка за курc +[Задание 1 (GitHub)](https://github.com/iradche/Data-Intro-2020-course/blob/master/tasks/task01.md) = 1 балл +[Задание 2 (Поиск данных)](https://github.com/iradche/Data-Intro-2020-course/blob/master/tasks/task02.md) = 2 балла +[Задание * (_Задание со звездочкой_)](https://github.com/iradche/Data-Intro-2020-course/blob/master/tasks/task02_.md) = 1 балл +[Задание 3 (OpenRefine)](https://github.com/iradche/Data-Intro-2020-course/blob/master/tasks/task03.md) = 2 балла +[Задание 4 (Processing)](https://github.com/iradche/Data-Intro-2020-course/blob/master/tasks/task04.md) = 2 балла +[Задание 5 (Курс “Введение в алгоритмы”)](https://github.com/iradche/Data-Intro-2020-course/blob/master/tasks/task05.md) = 2 балла From 8dfcb2c2104380196d921cf0195b5d96946d27fa Mon Sep 17 00:00:00 2001 From: Irina Radchenko Date: Thu, 24 Sep 2020 19:56:46 -0500 Subject: [PATCH 05/57] Update lec02.md --- lectures/lec02.md | 124 +++++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 123 insertions(+), 1 deletion(-) diff --git a/lectures/lec02.md b/lectures/lec02.md index 83a0bcc..b6de89c 100644 --- a/lectures/lec02.md +++ b/lectures/lec02.md @@ -1 +1,123 @@ -### Жизненный цикл данных и жизненный цикл метаданных +## Жизненный цикл данных и жизненный цикл метаданных + +### Жизненный цикл данных + +**Жизненный цикл данных** – это последовательность этапов, которую конкретная порция данных проходит от начального этапа создания или получения до момента архивации или удаления. +#### Основные этапы жизненного цикла данных + +##### 1. Создание данных (Data Generation/Data Capture) +На этом этапе данные генерируются или захватываются. +Этот этап обычно еще делят на три типа получения данных: +1. Приобретение данных (Data Acquisition) +Получение организацией данных, уже сгенерированных вне предприятия. +2. Запись данных (Data Entry) + Создание новых данных оператором или компьютером. Данные имеют ценность для предприятия. +3. Регистрация сигналов (Signal Reception) + +Захват данных устройствами. Особенно важно в системах управления, но в последнее время особенно ценно при использовании такого подхода, как Интернет вещей. +Все три варианта получения данных очень важны в рамках рассмотрения процесса управления данными. +##### 2. Обслуживание данных (Data Maintenance) +После того, как данные были созданы, необходимо их хранить и обслуживать. +Необходимо осуществлять доставку данных в точку, где их будут использовать или производить над ними манипуляции (например, операции синтеза). + +Можно говорить о том, что **обслуживание данных** – это обработка данных без получения из извлечения из них полезной информации для предприятия. Зачастую обслуживание данных включает в себя такие действия с данными, как перемещение, интеграция, очистка, обогащение и ETL-процессы (Extract, Transform, Load). +Обслуживание данных обычно подразумевает применение широкого спектра методов из области управления данными (Data Management). + +##### 3. Синтез данных (Data Synthesis) +Это сравнительно недавно появившаяся стадия в жизненном цикле данных. Используется не во всех моделях жизненных циклах данных. +**Синтез данных** – это процесс получения дополнительной ценности из данных при помощи использования индуктивной логики и сторонних информационных источников. +Это стадия, на которой с данными работаю аналитики, причем они могут использовать в своей работы методы моделирования рисков, актуарного моделирования, моделирования для принятия инвестиционных решений и др. + +На этой стадии используется индуктивная логика, не дедуктивная. Индуктивная логика требует использования экспертного мнения, т.к. именно компетенции экспертов необходимы для построения моделей скоринга и др. + +##### 4. Использование данных (Data Usage) +До сих пор шла речь об использовании данных внутри одного предприятия, которые возможно были подвержены очистке и обогащению на стадии обслуживания данных и использовались совместно с дополнительным третьими источниками данных на стадии синтеза данных. + +На стадии использования данных они применяются в качестве полезной информации для задач, которые должны выполняться и управляться на основе данных. +Эти задачи могут быть вне жизненного цикла данных. Тем не менее, данные становятся все более значимой частью бизнес-процессов предприятий. Данные сами могут быть продуктом или услугой (или быть частью продукта или услуги), предлагаемой предприятием. + +Использование данных имеет специальные задачи в рамках управления данными (Data Governance). Одна из задач заключается в законном использовании данных в требуемом виде. Это называется “разрешенное использование данных” (permitted use of data). Могут существовать регулирующие или договорные ограничения на то, как фактически можно использовать данные, а часть роли управления данными (Data Governance) заключается в обеспечении соблюдения этих ограничений. + +##### 5. Публикация данных (Data Publication) +При использовании данных возможна ситуация, когда данные отправляются за пределы предприятия. В этом случае говорят о публикации данных. **Публикация данных** – это вынос данных за пределы предприятия. + +Примером этого процесса может быть маклер, рассылающий ежемесячные отчеты клиентам. Все данные, которые были разосланы, уже не могут быть отозваны. Если были разосланы данные с неверными значениям, то такие данные не могут быть исправлены, поскольку они уже становятся недоступны для предприятия. Управление данными (Data Governance) может потребоваться, чтобы помочь принять решение о том, как будут обрабатываться неверные данные, которые были отправлены из предприятия. + +##### 6. Архивация данных (Data Archival) +Данные могут быть использованы как однократно, так и несколько раз. Но затем рано или поздно жизненный цикл данных начинает подходить к концу. +Первая стадия этого состояния заключается в архивации данных. + +**Архивация данных** – это копирование данных в пассивную среду, в которой они хранится, для тех случаев, когда они понадобятся снова в активной производственной среде, и удаление этих данных из всех активных производственных сред. + +**Архив данных** – это просто место, где хранятся данные, без их обслуживания, использования или публикации. В случае необходимости данные могут быть восстановлены из архива. + +##### 7. Уничтожение данных (Data Purging) +**Уничтожение данных** – это последовательность операций для выполнения необратимого удаления данных, делающая невозможным как восстановление данных, так и получение остаточной информации (Data Remanence) о них. Это одна из самых сложно реализуемых процедур управления данными. +Даже с теоретической точки зрения существует команда записи значения в ячейку памяти, но команды стирания значения как таковой нет. Для уничтожения данных необходимо изготовить высокопроизводительный источник случайных чисел и перезаписать ими весь носитель информации (перезаписи области хранения недостаточно, так как сохраняется информация об исходном количестве данных). + +Иначе говоря, при уничтожении данных необходимо не только сделать недоступными от восстановления на физическом уровне сами данные, но и связанную с ними информацию в других наборах данных. Уничтожение данных регламентируется в ГОСТ Р 50735 , причём классы защищенности данных и протоколы работы устанавливаются на уровне руководящих документов гостехкомиссии (ФСТЭК, Федеральной службы по техническому и экспортному контролю). + +В настоящее время в РФ предусмотрено семь классов защиты информации. Согласно действующему на настоящему моменту пункту 19.2 приказа ФСТЭК N17 от 11.02.2013 “При выводе из эксплуатации машинных носителей информации, на которых осуществлялись хранение и обработка информации, осуществляется физическое уничтожение этих машинных носителей информации”. + + +### Жизненный цикл метаданных +Жизненный цикл метаданных можно разделить на четыре стадии. +1. Оценка требований и анализ контента. +2. Спецификация системных требований. +3. Система метаданных. +4. Сервис и оценка. +Рассмотрим эти стадии подробнее. + +##### 1. Оценка требований и анализ контента +Этот этап состоит из четырех частей. +1. Выявление и получение базовых требований к метаданным. +2. Обзор релевантных стандартов и проектов по метаданным. +3. Исследование требований к глубоким метаданным. +4. Идентификация стратегий для схем метаданных. + +###### Выявление и получение базовых требований к метаданным +На этом этапе жизненного цикла метаданных проводится опрос экспертов и специалистов по предметной области на тему требований к метаданным в конкретном проекте и анализ атрибутов. Целью опроса или интервьюирования экспертов является получение предварительной информации о проекте и установление контакта между специалистами по метаданным и провайдерами данных (или контента). На этой стадии должны быть уточнены и разъяснена и уточнена область метаданных, контекст метаданных, действующая система метаданных, роль и функция метаданных. + +###### Обзор релевантных стандартов и проектов по метаданным +Этот этап включает определение стандартов метаданных, потенциально полезных для проекта, изучение существующих схем метаданных и вариантов их использования. Этот этап нужен для того, чтобы можно было лучше узнать, какие различия существуют среди других аналогичных проектов, а также пересмотреть цели проекта. + +###### Исследование требований к глубоким метаданным +На этом этапе определяются требования к метаданным более детально и глубоко. Для этого используется концепция контент-анализа. Здесь важно уточнить область и контент метаданных, а также проработан вопрос планируемых в работе СУБД и информационных систем, в которых планируется использовать метаданные. В дальнейшем эти наработки могут быть использованы в качестве методики для масштабирования. + +###### Идентификация стратегий для схем метаданных +На этом этапе формулируется стратегия использования метаданных на основе всех имеющих предыдущих результатов. Стратегия включает принятие одного или нескольких существующих стандартов метаданных и разработку на основе этих стандартов схемы метаданных. + +##### 2. Спецификация системных требований +Этот этап состоит из двух частей. +1. Подготовка спецификации требований к метаданным +2. Оценка систем метаданных + +###### Подготовка спецификации требований к метаданным +Спецификация требований к метаданным (Metadata Requirement Specification, MRS) является связующим звеном между участниками проекта, специалистами по метаданным и разработчиками систем. + +###### Оценка систем метаданных +На этом этапе производится оценка систем метаданных, которые потенциально могут использоваться в проекте в дальнейшем. Участники проекта могут выбрать из существующих систем метаданных. + +##### 3. Система метаданных +Этот этап состоит из двух частей. +1. Подготовка руководства по лучшей практике. +2. Разработка системы метаданных. + +###### Подготовка руководства по лучшей практике +Этот этап включает в себя создание документации и разработку руководящих принципов “лучшей практики” для отдельных элементов метаданных. Руководство может использоваться как контрольный список или как средство обеспечения контроля качества записей метаданных в проекте. + +###### Разработка системы метаданных +Разработчики системы разрабатывают инструменты и системы метаданных на основе спецификации требований к метаданным. + +##### 4. Сервис и оценка +Этот этап состоит из двух частей. +1. Поддержка службы метаданных. +2. Оценка качества метаданных. + +###### Поддержка службы метаданных +Цель разработки служб метаданных – гарантировать качество метаданных и механизмов работы с ними. Модель сервиса метаданных состоит из трех основных элементов: служебный механизм, роли и отношения между ролями. + +###### Оценка эффективности метаданных +Последний этап жизненного цикла метаданных направлен на рассмотрение результатов всего процесса работы с метаданными и качества самих метаданных. Интегральная оценка состоит из оценки качества метаданных, оценки эффективности работы схемы метаданных, оценки результатов использования инструментов создания метаданных и оценки применения модели жизненного цикла метаданных на каждом этапе. + + From 12f3add40dbd85a2664351c09a66605135630a9d Mon Sep 17 00:00:00 2001 From: Irina Radchenko Date: Fri, 25 Sep 2020 09:01:34 -0500 Subject: [PATCH 06/57] Update README.md --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index aa2c22d..c3a288f 100644 --- a/README.md +++ b/README.md @@ -25,8 +25,8 @@ 2. [Определения данных, метаданных и больших данных](https://github.com/iradche/Data-Intro-2020-course/blob/master/lectures/lec01.md). 3. [Жизненный цикл данных и жизненный цикл метаданных](https://github.com/iradche/Data-Intro-2020-course/blob/master/lectures/lec02.md). 4. [Большие данные: технологии и архитектура систем больших данных](https://github.com/iradche/Data-Intro-2020-course/blob/master/lectures/lec03.md). -5. [Работа с данными](https://github.com/iradche/Data-Intro-2020-course/blob/master/lectures/lec04.md). -6. [Поиск и обработка данных](https://github.com/iradche/Data-Intro-2020-course/blob/master/lectures/lec05.md). +5. [Поиск данных](https://github.com/iradche/Data-Intro-2020-course/blob/master/lectures/lec04.md). +6. [Обработка данных](https://github.com/iradche/Data-Intro-2020-course/blob/master/lectures/lec05.md). 7. [Что такое компьютерная программа и программное обеспечение](https://github.com/iradche/Data-Intro-2020-course/blob/master/lectures/lec06.md). 8. [История языков программирования](https://github.com/iradche/Data-Intro-2020-course/blob/master/lectures/lec07.md). 9. [Что такое алгоритмы](https://github.com/iradche/Data-Intro-2020-course/blob/master/lectures/lec08.md). 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