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Search results “Statistics system oracle” for the 2017
Oracle System Statistics und I/O Calibrate - jetzt aber Richtig
 
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Obwohl System Statistiken und I/O Calibration schon sehr lange ein integraler Bestandteil der Oracle Datenbank und des Optimizers ist, werden diese beide Funktionalitäten kaum oder falsch behandelt.
Views: 101 DBMasters
Oracle Performance - DBMS_STATS
 
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Oracle Performance - DBMS_STATS
Views: 4227 The Silent DBA
PL/SQL tutorial : Trigger in Oracle Database 11g Complete guide
 
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Learn in depth about trigger in oracle database 11g, and usage of trigger in Database, different types of trigger with syntax for various events along with writing advance trigger and capturing all details regarding authentication. Explained Instead of trigger. Trigger in Oracle, Trigger in PL/SQL, Oracle Trigger, PL/SQL Trigger, What is Trigger in pl/sql, How to use Trigger in pl/sql, How to write a Trigger in oracle, How to design Trigger in pl/sql, DDL trigger, DML trigger, Instead of trigger, Compound trigger, Logon trigger, Introduction to Triggers You can write triggers that fire whenever one of the following operations occurs: DML statements (INSERT, UPDATE, DELETE) on a particular table or view, issued by any user DDL statements (CREATE or ALTER primarily) issued either by a particular schema/user or by any schema/user in the database Database events, such as logon/logoff, errors, or startup/shutdown, also issued either by a particular schema/user or by any schema/user in the database Triggers are similar to stored procedures. A trigger stored in the database can include SQL and PL/SQL or Java statements to run as a unit and can invoke stored procedures. However, procedures and triggers differ in the way that they are invoked. A procedure is explicitly run by a user, application, or trigger. Triggers are implicitly fired by Oracle when a triggering event occurs, no matter which user is connected or which application is being used. How Triggers Are Used Triggers supplement the standard capabilities of Oracle to provide a highly customized database management system. For example, a trigger can restrict DML operations against a table to those issued during regular business hours. You can also use triggers to: Automatically generate derived column values Prevent invalid transactions Enforce complex security authorizations Enforce referential integrity across nodes in a distributed database Enforce complex business rules Provide transparent event logging Provide auditing Maintain synchronous table replicates Gather statistics on table access Modify table data when DML statements are issued against views Publish information about database events, user events, and SQL statements to subscribing applications Linkedin: https://www.linkedin.com/in/aditya-kumar-roy-b3673368/ Facebook: https://www.facebook.com/SpecializeAutomation/
Views: 9737 Specialize Automation
AskTOM TV - The TOP-FREQUENCY histogram in 12c
 
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blog: https://connor-mcdonald.com A video to help you understand the "thought process" behind answering AskTom questions. In this episode, how does the optimizer deal with the 12c in-database archiving feature ========================================­­­­============== Copyright © 2017 Oracle and/or its affiliates. Oracle is a registered trademark of Oracle and/or its affiliates. All rights reserved. Other names may be registered trademarks of their respective owners. Oracle disclaims any warranties or representations as to the accuracy or completeness of this recording, demonstration, and/or written materials (the “Materials”). The Materials are provided “as is” without any warranty of any kind, either express or implied, including without limitation warranties or merchantability, fitness for a particular purpose, and non-infringement.
Views: 687 Connor McDonald
Move Data Between Apache Hadoop and Oracle Database for Customer 360 Degree Analytics
 
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Melliyal Annamalai, Oracle Krishna Gayatri Kuchimanchi, Oracle Shelvanarayana Aghalayam, Principal SC - SCC Solutions - Big Data, Oracle Customer 360-degree views require data from mobile device feeds, online community logs, social media feeds (often processed with Apache Hadoop), and a wealth of information stored in the database. Tools for data movement between big data platforms and Oracle Database are necessary for machine learning and complex analytics using all this data. In this session, step through using some of these tools with direct path load, SQL, and custom Hive SerDes and understand how they work with big data and database services in Oracle Cloud Infrastructure.
Views: 665 Oracle Developers
Top 10 Certifications For 2018 | Highest Paying IT Certifications 2018 | Edureka
 
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** Get Edureka Certified in Trending Technologies : https://www.edureka.co ** UPDATED 2019 Top 10 Certification video: http://bit.ly/2QemVtN In this highly competitive IT industry, acquiring a globally-recognized professional certification is the best way to not only learn a technology/tool, but to also back it up with authoritative validation. So, we at Edureka have prepared a list of Top 10 Certifications for 2018 that will help you to boost your career and have a good salary hike. Subscribe to our channel to get video updates. Hit the subscribe button above. #edureka #TopCertification #ITCertification #Certifications ----------------------------------------------------------------- For Online Training and Certification, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free) for more information. Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 559436 edureka!
Machine Learning with Oracle
 
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Introduction - 0:00 Overview Machine Learning in Oracle - 1:31 Machine Learning theory - 6:04 Demonstration: preparation and building the model - 11:52 Demonstration: run the prediction and adapt the application - 26:24 How to get started - 33:33 Without a doubt Machine Learning / Artificial Intelligence is an incredibly powerful technology with a huge potential. It brings benefits across many industries and business functions: From better targeting in the marketing/sales domain to predictive maintenance in manufacturing. This video-webinar is a kickstart to Machine Learning. You will learn the required theoretical knowledge and then we'll go through a real-life example: intelligent sales with ML. We'll create our very first ML model, and use it to make an existing application intelligent with sales recommendations. After this webinar you will have the basic ingredients to apply ML to your own business cases! Note that you don't require any previous knowledge of ML to be able to understand this session. Powerpoint and background material can be found here: https://ptdrv.linkedin.com/cmaj4xt
Views: 5421 Jeroen
WORDPRESS DISPLAY DATA FROM DATABASE IN TABLES
 
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WORDPRESS DISPLAY DATA FROM DATABASE IN TABLES
Views: 70310 Martins Hacks
Oracle Database  | Bangla Tutorials 16  :: Sql Set Operator
 
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www.facebook.com/oracle.shohag Email : [email protected] Website : www.oraclebangla.com Topics : Sql Set Operator
Views: 1431 Oracle Bangla
Top 10 High Paying Software Jobs - Check Out What It takes ?
 
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Top 10 High Paying Software Jobs - Check Out What It takes ? Watch this video to find out highest paying software jobs. If you're a software engineer, database admin, a data scientist, fronted developer, designer or a mobile developer, find how much is the average annual pay for your skill sets. #10 .Net Developer - $84,000 What It takes ? Programming expe in ASP .NET MVC Basic knowledge in Html,CSS Jquery/Java Scripts, Bootstrap Working knowledge of Databases MS SQL, Oracle, NoSql, mongoDB Creating setups and exe. # 09 Database Admin - $87,000 What It takes ? Understanding of structured query language (SQL) Experience with RDBMS Assist in database design Manage Databases Maritain security and integrity of databases Database Security Upgrades and Installs Deployment strategies, failure protection #08 Fronted Developer - $92,000 What It takes ? Programming in HTML5 CSS3, JavaScript, Node.js Browser Developer Tools(Firefox, Chrome) Experience with Data Formats (e.g., JSON, XML) Content Management Systems(word-press, Blogger, Joomla etc..) Front End Frameworks RESTful Services and APIs Testing and Debugging Version Control Systems # 07 Mobile Developer - $96,000 What It takes ? Cross-platform Development,iOS, Android BlackBerry, Windows etc Good UX/UI Design Skills Programming knowledge Java, C#, Objective C /Swift, HTML5, PHP etc. Knowledge of Cross Platform Mobile Development Tools # 06 Java Developer - $96,500 What It takes ? OOPs Concepts Design Patterns Data Structures JVM Multi-threading and Synchronization Domain Knowledge Networking, Multi Media, Automobile, Finance JUnit testing, debugging, ANT Source Control (GIT, SVN, CVS etc..) Database Programming (SQL) #05 Software Engineer - $98,000 What It takes ? Programming Skills, C/C++, JAVA, PHP, Python, HTML5/CSS3, Ruby etc Knowledge of Source control Debugging skills problem solving Attention to Detail Teamwork Unit testing #04 DevOps Engineer - $106,000 What It takes ? Linux/Unix Administration coding and scripting in Python, PHP, Perl,Ruby Knowledge of opensource tools Experience with systems and IT operations Continuous Improvement (CI) Continuous Deployment, tools like Jenkins collaboration, open communication automation/configuration management # 03 Data Scientist - $115,000 What It takes ? Data mining methods Processing, cleansing, and verifying of data Great communication skills statistical programming language R or Python Database Querying language SQL, mongoDB Statistics, Multi variable Calculus and Linear algebra # 02 Software Architect - $128,500 What it takes ? Knowledge of various software architectures Resolve technical problems Technically competent Strong communicator Knowledge of core frameworks high level guidance and direction on project work Strong design experience # 01 Software Development Manager -$132,000 What it takes ? Managing Relationships Project Planning Process Control Negotiation Skills Vendor Management Presentation Skills Problem solving and decision making Knowledge of Domain,Development Cycles,Automation process, Quality Assurance,Release Management Team Staffing Administrative functions
Views: 780984 eaZyTips
6. Базы данных. Оптимизация запросов. Оптимизация структуры данных | Технострим
 
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Слайды лекции: https://bozaro.github.io/tech-db-lectures/06/ ► Другие лекции курса: https://www.youtube.com/playlist?list=PLrCZzMib1e9oOFQbuOgjKYbRUoA8zGKnj Подробнее о курсе: https://park.mail.ru/curriculum/program/discipline/218/ Лекция читается в рамках образовательного проекта "Технопарк Mail.ru Group" при МГТУ им.Баумана. КРАТКОЕ СОДЕРЖАНИЕ: Лекция посвящена производительности (оптимизации работы с БД). Рассматриваются следующие темы: — Нормализация и денормализация данных; — Оптимизация запросов конкретных типов; — Разница между актуальными и историческими данными; — Секционирование; — Оптимизация на уровне приложения; — Примеры эффективного массового изменения данных. Хронометраж: 00:00:03 О теме лекции 00:00:54 Нормализация и денормализация данных (на примере тестовой БД из прошлой лекции) 00:02:43 Вопрос залу: о приоритете применения того или метода построения запроса 00:04:10 Повторение пройденного материала: о покрывающем индексе 00:04:45 Повторение пройденного материала: про подзапросы (SUBQUERIES) 00:07:47 Повторение пройденного материала: краткий итог 00:11:01 Вопрос залу: в каком случае не нужны индексы для внешних ключей (FOREIGN KEY)? 00:12:44 Продолжение рассмотрения примера из тестовой БД: Заменим 'Zombie%' на 'Comedy%' 00:13:12 Оптимизируйте доступ к данным (Модификация запросов) 00:17:45 Нормализация (плюсы нормализации данных) 00:18:56 Денормализация (методы денормализации данных) 00:22:04 Нормализация/денормализация: пример 00:25:18 Оптимизация запросов конкретных типов 00:25:33 Оптимизация DELETE: очистка таблицы 00:28:07 Оптимизация COUNT(*): получение кол-ва записей в таблице 00:31:28 Оптимизация COUNT(*): получение кол-ва записей после выполнения запроса 00:33:20 Оптимизация LIMIT со смещением 00:40:46 Оптимизация: случай из практики 00:44:21 Исторические и актуальные данные (Настоящее vs Прошлое) 00:46:44 Актуальные данные (особенности и проблемы) 00:49:12 Исторические данные (особенности и проблемы) 00:57:47 Вопрос из зала по пройденному материалу 00:58:17 Ответ и уточняющие вопросы 01:00:36 Исторические данные (особенности и проблемы) - продолжение 01:02:03 Цитата о "биг дата" 01:02:49 Секционирование (англ. partitioning) 01:06:48 Секционирование: наследование 01:16:13 Секционирование: наследование (плюсы и минусы) 01:19:46 Секционирование: pg_pathman (плюсы и минусы) 01:22:11 Секционирование: PostgreSQL 10 (плюсы и минусы) 01:23:45 Оптимизация на уровне приложения (Уменьшение времени блокировок) 01:26:56 Разбиение запроса на более мелкие 01:31:09 Модификация схемы 01:39:50 Группировка UPDATE 01:45:54 Массовая вставка данных 01:53:08 Загрузка данных через COPY 01:55:11 Блокировки (Пессимистичная / Оптимистичная) 01:59:54 Ограничение времени ожидания (Долгий / Ждущий / Срочный запрос) 02:04:42 CREATE INDEX (Блокирующее / Неблокирующее создание индекса) 02:05:36 ALTER TABLE (Классический / Сокращенный вариант) О КАНАЛЕ: Официальный канал образовательных проектов Mail.Ru Group ► Нажмите здесь для подписки ‣ http://www.youtube.com/TPMGTU?sub_confirmation=1 Актуальные лекции и мастер-классы о программировании от лучших IT-специалистов. Если вы увлечены мобильной и веб-разработкой, присоединяйтесь! Наши проекты: Технопарк при МГТУ им. Баумана ‣ https://park.mail.ru Техносфера при МГУ им. Ломоносова ‣ https://sphere.mail.ru Технотрек при МФТИ ‣ https://track.mail.ru Техноатом при МИФИ - https://atom.mail.ru Технополис при СПбПУ - https://polis.mail.ru ------------------------ МЫ В СЕТИ: Технопарк в ВК | http://vk.com/tpmailru Техносфера в ВК | https://vk.com/tsmailru Технотрек в ВК | https://vk.com/trackmailru Техноатом в ВК | https://vk.com/technoatom Технополис в ОК: https://www.ok.ru/technopolis Технополис в ВК: https://vk.com/technopolis_ok Блог на Хабре | http://habrahabr.ru/company/mailru
HR Reporting & Analytics
 
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HR analytic solutions enable you to gain insights into your workforce, providing an understanding of how your employees are creating value by looking at the cause and effect relationships between data sets. An effective HR reporting and analytic solution leads to better understanding and informed decision making. This webcast takes you through the journey from simple HR reporting to driving insights and analysis out of your employee data.
Views: 15009 ThorogoodBI
5. Базы данных. Индексы и производительность | Технострим
 
02:40:56
Слайды лекции: https://bozaro.github.io/tech-db-lectures/05/ ► Другие лекции курса: https://www.youtube.com/playlist?list=PLrCZzMib1e9oOFQbuOgjKYbRUoA8zGKnj Подробнее о курсе: https://park.mail.ru/curriculum/program/discipline/218/ Лекция читается в рамках образовательного проекта "Технопарк Mail.ru Group" при МГТУ им.Баумана. КРАТКОЕ СОДЕРЖАНИЕ: Лекция посвящена индексам и производительности. А так же: протоколированию запросов, плану запросов EXPLAIN, стратегиям запросов и JOINS. Хронометраж: 00:00:04 О теме лекции 00:00:47 Индексирование. Введение в индексы БД 00:01:55 Варианты индексов. btree - сбалансированное дерево 00:03:56 Индексирование btree (особенности) 00:06:27 hash-индексы 00:08:29 Индексирование hash (особенности). Коллизии hash-индексов 00:11:12 Некоторые типы данных с которыми ни btree, ни hash не работают 00:12:17 Индексирование GiST (R-Tree) 00:13:36 Индексирование GIN (инвертированный) 00:14:39 Индексирование: битовый индекс 00:17:20 Частичный индекс 00:20:35 Функциональный индекс 00:22:19 Кластерный индекс 00:25:45 Покрывающий индекс 00:28:35 Индексирование. "Расплата" 00:30:34 Как создается индекс? 00:32:59 Индексирование. Итог ("подытоживание") 00:35:25 Вопрос из зала по hash-индексам 00:38:07 Большой выигрыш при использовании покрывающих индексов 00:38:44 Ответы на вопросы по индексированию 00:48:30 Тестовая БД для рассмотрения работы индексов 00:54:08 Как выполняется простой запрос? (Тестовая БД) 00:59:44 Как выполняется запрос? (Два условия и два индекса) 01:07:00 Как выполняется запрос? (Сортировка и индексы) 01:09:59 JOIN-стратегии 01:17:10 Профилирование 01:19:16 Несколько вариантов поиска запросов, которые создают основную нагрузку на сервер 01:19:23 Вариант 1 - Статистика запросов 01:22:44 Вариант 2 - Протоколирование запросов 01:25:50 Логирование в CSV 01:27:15 Протоколирование запросов (нюансы) 01:28:41 На что важно обратить внимание при чтении отчетов 01:32:03 EXPLAIN 01:36:08 Параметр ANALYZE (важная ремарка) 01:36:37 EXPLAIN: Некоторые особенности работы 01:37:57 EXPLAIN: Начало 01:39:09 Что такое стоимость? О единицах времени 01:40:37 EXPLAIN: Статистика 01:42:20 EXPLAIN: ANALYZE 01:45:17 EXPLAIN: WHERE 01:48:46 EXPLAIN: TEXT 01:56:52 EXPLAIN: ORDER BY 02:00:40 EXPLAIN: JOIN 02:05:34 EXPLAIN: На что обратить внимание? 02:07:20 EXPLAIN: Разбор примера из тестовой БД 02:08:06 EXPLAIN: Графическое представление 02:09:32 EXPLAIN: Текстовое представление 02:10:31 EXPLAIN: Добавляем индексы 02:21:03 Чем плохи подзапросы? 02:29:02 По поводу производительности 02:36:45 Покрывающий индекс (Продолжение разбора примера из тестовой БД) ------------------------ О КАНАЛЕ: Официальный канал образовательных проектов Mail.Ru Group ► Нажмите здесь для подписки ‣ http://www.youtube.com/TPMGTU?sub_confirmation=1 Актуальные лекции и мастер-классы о программировании от лучших IT-специалистов. Если вы увлечены мобильной и веб-разработкой, присоединяйтесь! Наши проекты: Технопарк при МГТУ им. Баумана ‣ https://park.mail.ru Техносфера при МГУ им. Ломоносова ‣ https://sphere.mail.ru Технотрек при МФТИ ‣ https://track.mail.ru Техноатом при МИФИ - https://atom.mail.ru Технополис при СПбПУ - https://polis.mail.ru ------------------------ МЫ В СЕТИ: Технопарк в ВК | http://vk.com/tpmailru Техносфера в ВК | https://vk.com/tsmailru Технотрек в ВК | https://vk.com/trackmailru Техноатом в ВК | https://vk.com/technoatom Технополис в ОК: https://www.ok.ru/technopolis Технополис в ВК: https://vk.com/technopolis_ok Блог на Хабре | http://habrahabr.ru/company/mailru
Difference between hadoop and relational databases
 
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This video highlights some basic differences between hadoop and relational database management systems. It talks about what operations are best performed in hadoop and what operations are best performed in relational databases. structured vs unstructured data. high vs low cost. open source vs licensed.
Views: 1701 SelfReflex
Tour Oracle's State of the Art Data Centers
 
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Take a tour and tour Oracle's data center.
Views: 51921 Oracle
Making an SQL query from a C++ application (Visual Studio tutorial)
 
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Dr. Carlo Cappello (University of Trento, Italy) presents how to make an SQL query from a C++ application. Code: https://drive.google.com/open?id=1mSMV1OdekXh3mUqL5Cs74H0NHRSGr9ZS
Views: 8862 Carlo Cappello
AskTOM TV - SQL trace, SQL plus, SQL developer
 
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A video to help you understand the "thought process" behind answering AskTom questions. In this episode, we look at how we can use SQL trace to diagnose what autotrace privileges we need in SQL Developer blog: https://connor-mcdonald.com ========================================­­­­============== Copyright © 2017 Oracle and/or its affiliates. Oracle is a registered trademark of Oracle and/or its affiliates. All rights reserved. Other names may be registered trademarks of their respective owners. Oracle disclaims any warranties or representations as to the accuracy or completeness of this recording, demonstration, and/or written materials (the “Materials”). The Materials are provided “as is” without any warranty of any kind, either express or implied, including without limitation warranties or merchantability, fitness for a particular purpose, and non-infringement.
Views: 1094 Connor McDonald
Driving up Student Retention Rates with Oracle Big Data
 
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Here's how one school was able to increase it competitive advantage by driving up students retention rates with Oracle's integrated Big Data Appliance and visual analytics tools.
Views: 159 Oracle Big Data
How to create Virtual Columns in Oracle Database
 
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How to create Virtual Columns in Oracle Database 12c When queried, virtual columns appear to be normal table columns, but their values are derived rather than being stored on disc. The syntax for defining a virtual column is listed below. column_name [datatype] [GENERATED ALWAYS] AS (expression) [VIRTUAL] If the datatype is omitted, it is determined based on the result of the expression. The GENERATED ALWAYS and VIRTUAL keywords are provided for clarity only. The script below creates and populates an employees table with two levels of commission. It includes two virtual columns to display the commission-based salary. The first uses the most abbreviated syntax while the second uses the most verbose form. CREATE TABLE employees ( id NUMBER, first_name VARCHAR2(10), last_name VARCHAR2(10), salary NUMBER(9,2), comm1 NUMBER(3), comm2 NUMBER(3), salary1 AS (ROUND(salary*(1+comm1/100),2)), salary2 NUMBER GENERATED ALWAYS AS (ROUND(salary*(1+comm2/100),2)) VIRTUAL, CONSTRAINT employees_pk PRIMARY KEY (id) ); INSERT INTO employees (id, first_name, last_name, salary, comm1, comm2) VALUES (1, 'JOHN', 'DOE', 100, 5, 10); INSERT INTO employees (id, first_name, last_name, salary, comm1, comm2) VALUES (2, 'JAYNE', 'DOE', 200, 10, 20); COMMIT; Querying the table shows the inserted data plus the derived commission-based salaries. SELECT * FROM employees; ID FIRST_NAME LAST_NAME SALARY COMM1 COMM2 SALARY1 SALARY2 ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- 1 JOHN DOE 100 5 10 105 110 2 JAYNE DOE 200 10 20 220 240 2 rows selected. SQL The expression used to generate the virtual column is listed in the DATA_DEFAULT column of the [DBA|ALL|USER]_TAB_COLUMNS views. COLUMN data_default FORMAT A50 SELECT column_name, data_default FROM user_tab_columns WHERE table_name = 'EMPLOYEES'; COLUMN_NAME DATA_DEFAULT ------------------------------ -------------------------------------------------- ID FIRST_NAME LAST_NAME SALARY COMM1 COMM2 SALARY1 ROUND("SALARY"*(1+"COMM1"/100),2) SALARY2 ROUND("SALARY"*(1+"COMM2"/100),2) 8 rows selected. SQL Notes and restrictions on virtual columns include: 1)Indexes defined against virtual columns are equivalent to function-based indexes. 2)Virtual columns can be referenced in the WHERE clause of updates and deletes, but they cannot be manipulated by DML. 3)Tables containing virtual columns can still be eligible for result caching. 4)Functions in expressions must be deterministic at the time of table creation, but can subsequently be recompiled and made non-deterministic without invalidating the virtual column. In such cases the following steps must be taken after the function is recompiled: a)Constraint on the virtual column must be disabled and re-enabled. b)Indexes on the virtual column must be rebuilt. c)Materialized views that access the virtual column must be fully refreshed. d)The result cache must be flushed if cached queries have accessed the virtual column. e)Table statistics must be regathered. 5)Virtual columns are not supported for index-organized, external, object, cluster, or temporary tables. 6)The expression used in the virtual column definition has the following restrictions: a.It cannot refer to another virtual column by name. b.It can only refer to columns defined in the same table. c.If it refers to a deterministic user-defined function, it cannot be used as a partitioning key column. e.The output of the expression must be a scalar value. It cannot return an Oracle supplied datatype, a user-defined type, or LOB or LONG RAW.
Views: 456 OracleDBA
Тс снайпер 3.0 финальная версия скачать
 
03:13
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Views: 561 Alex Alex
Get Started with Analyses and Dashboards
 
02:38
Create an analysis and a dashboard. Add the analysis to the dashboard. ================================= To improve the video quality, click the gear icon and set the Quality to 1080p/720p HD. For documentation, see the following Oracle Help Center pages: * BI Cloud Service: http://docs.oracle.com/cloud/latest/reportingcs_use/reportingcs_use.htm * BI Enterprise Edition: http://docs.oracle.com/middleware/12212/biee/biee-devreports.htm ================================= For more information, see http://www.oracle.com/goto/oll Copyright © 2017 Oracle and/or its affiliates. Oracle is a registered trademark of Oracle and/or its affiliates. All rights reserved. Other names may be registered trademarks of their respective owners. Oracle disclaims any warranties or representations as to the accuracy or completeness of this recording, demonstration, and/or written materials (the “Materials”). The Materials are provided “as is” without any warranty of any kind, either express or implied, including without limitation warranties or merchantability, fitness for a particular purpose, and non-infringement.
03 01 Introduction
 
04:56
ORACLE
Views: 17 oracle ocm
Oracle Modern Business Tour
 
01:05
Are you ready to lead the 21st century, now? Oracle Modern Business Tour, register now: http://oracle.com/modernbusinessforum
Views: 5669 Oracle
ADRCI, Log- und Tracefile Managment
 
28:05
Housekeeping von Oracle Log und Tracefiles - viele nutzen die Möglichkeiten, das ADR bietet nicht aus. In diesem Vortrag wird das ADR, dessen Aufbau und die Nutzung von ADRCI behandelt.
Views: 298 DBMasters
Analyzing Big Data in less time with Google BigQuery
 
29:14
Most experienced data analysts and programmers already have the skills to get started. BigQuery is fully managed and lets you search through terabytes of data in seconds. It’s also cost effective: you can store gigabytes, terabytes, or even petabytes of data with no upfront payment, no administrative costs, and no licensing fees. In this webinar, we will: - Build several highly-effective analytics solutions with Google BigQuery - Provide a clear road map of BigQuery capabilities - Explain how to quickly find answers and examples online - Share how to best evaluate BigQuery for your use cases - Answer your questions about BigQuery
Views: 62743 Google Cloud Platform
Oracle Taleo Recruitment Cloud Service- Demonstration
 
57:11
Oracle Taleo Recruitment Cloud Service- Live Demonstration by JUPITEC
Views: 7984 JUPITEC, AUSTRALIA
C_TADM51_74 Certification - System Administration (Oracle DB) SAP NetWeaver 7.4
 
02:26
C_TADM51_74 Certification: https://www.dumpssheet.com/braindumps/C_TADM51_74 Preparation Method For Certified Application Associate C_TADM51_74 examinations: The preparation of Certified Application Associate C_TADM51_74 System Administration (Oracle DB) with SAP NetWeaver 7.4 may be undertaken by the candidates using the subsequent preparation resources: • Study Guides • Video Tutorials Firstly, the SAP Certified Application Associate C_TADM51_74 test could be prepared by using study guides. Study guides give deep, weighty materials on each exam topic. This makes study guides rather wearisome and unengaging for the students preparing for Certified Application Associate C_TADM51_74 System Administration (Oracle DB) with SAP NetWeaver 7.4. In comparison to review guides, video lessons and discussions are less pain-staking and more intriguing for the pupils. Since each of the two planning signifies has its pros and cons; benefit out of their mutual benefits and pupils are recommended to utilize both methods. Students often commit the blunder of not taking the problem of going through the practice exams, throughout their Certified Application Associate C_TADM51_74 exam planning. Statistics have demonstrated a bad preparation isn't the cause of failure, in the majority of the cases. A bulk of pupils who are unable to clear the Certified Application Associate C_TADM51_74 exam exhibit high levels of anxiety, which pushes them towards failure. Anxiety exists among the candidates of Certified Application Associate C_TADM51_74 exams, predominantly because they are oblivious to they might be confronted by while attempting their Certified Application Associate C_TADM51_74 exam. By heading going right through the practice tests, the pupils can, eliminate anxiety, as the cause of failure. Why SAP Certified Application Associate C_TADM51_74 exams are essential? The SAP Certified Application Associate C_TADM51_74 examinations may be exceptionally essential and required in terms of the accomplishment of an appropriate, exciting career is involved. These SAP Certified Application Associate C_TADM51_74 examinations are perplexing and tough to obvious and get; but one cannot question their importance. Recommendations for the Preparation of SAP Certified Application Associate C_TADM51_74 exams • The candidates must make one thing specific: the SAP Certified Application Associate C_TADM51_74 examination preparing requires them to be acquainted with all the exam syllabus. Selecting a Website The candidates significantly show shrewdness while picking a site. Info in relation to the DumpsSheet The content on the DumpsSheet is exceedingly informative and comprehensive. Excellent preparation material is offered by the DumpsSheet to the candidates. A SAP Certified Application Associate C_TADM51_74 exam replication is also offered. This enables the candidates to carefully practice for the SAP Certified Application Associate C_TADM51_74 exam using the format of the real exam. This replication also enables candidates to become aware of their own efficiencies and inefficiencies. The layout of this (site) has been created by the SAP, fantastically. The DumpsSheet’s lay-out was designed so as to make it easy to use. Other essential characteristics of the DumpsSheet are: • The site offers complete flexibility in relation to the search of any kind of SAP Certified Application Associate C_TADM51_74 examination. • The consumers of the site usually stay acquainted with the upto-day knowledge as the DumpsSheet is recurrently updated. • The McAfee anti-virus performs the job of safety of the customer’s bio data. • The DumpsSheet permits candidates to become members of the DumpsSheet and discuss their experience with the DumpsSheet’s brand; along with viewing the remarks of these customers who have previously acquired knowledge of the DumpsSheet’s manufacturer. • If considered necessary, the site makes use of the feedback provided by customers to make variations to the DumpsSheet’s product. The DumpsSheet’s efficacy The following points emphasize the site’s efficacy: • The unsuccessful candidates are came ultimately back their funds paid as SAP Certified Application Associate C_TADM51_74 exam fee. The reimbursement of the examination payment by the site wholly depends on whether the candidate has informed the DumpsSheet within a month and also a half, about such occurring. • The DumpsSheet offers efficient professional support and information to the candidates. • The DumpsSheet gives its regular customers fabulous value cuts or more to 30% discount.
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Integrating Chart.js with Angular 5 with Data from an API
 
18:58
Written tutorial: https://goo.gl/v1dC9o Subscribe here and check out https://coursetro.com In this tutorial, we're going to connect to a public API to retrieve weather data, and then chart it out using Chart.js The github repo for this project: https://github.com/designcourse/angular-chartjs - - - - - - - - - - - - - - - - - - - - - - Subscribe for NEW VIDEOS weekly! My site: https://coursetro.com My personal FB account: http://fb.com/logodesigner Coursetro FB: http://fb.com/coursetro Coursetro's Twitter: http://twitter.com/designcoursecom Join my Discord! https://discord.gg/a27CKAF ^-Chat with me and others - - - - - - - - - - - - - - - - - - - - - - Who is Gary Simon? Well, I'm a full stack developer with 2+ decades experience and I teach people how to design and code. I've created around 100+ courses for big brands like LinkedIn, Lynda.com, Pluralsight and Envato Network. Now, I focus all of my time and energy on this channel and my website Coursetro.com. Come to my discord server or add me on social media and say Hi!
Views: 79712 DesignCourse
Oracle 12c Release 2 - How to get SQL Plus command history
 
01:36
blog: https://connor-mcdonald.com Want to go retrieve and edit previous commands in SQL Plus without using things like rlwrap ? easy in 12.2 ========================================­­­­============== Copyright © 2017 Oracle and/or its affiliates. Oracle is a registered trademark of Oracle and/or its affiliates. All rights reserved. Other names may be registered trademarks of their respective owners. Oracle disclaims any warranties or representations as to the accuracy or completeness of this recording, demonstration, and/or written materials (the “Materials”). The Materials are provided “as is” without any warranty of any kind, either express or implied, including without limitation warranties or merchantability, fitness for a particular purpose, and non-infringement.
Views: 1176 Connor McDonald
ATUM - Features - Dashboard Statistics
 
10:01
ATUM - Inventory Management for WooCommerce
Getting started with Toad for DB2: Chapter 5 - Database Explorer Filtering
 
03:29
https://www.quest.com/products/toad-for-ibm-db2/ Learn about database explorer filtering in Toad for DB2, the solution from Quest that simplifies database management.
Views: 219 Quest
AskTOM TV - not null... I mean *really* not null
 
04:09
A short video to help you understand the "thought process" behind answering AskTom questions. blog: https://connor-mcdonald.com ========================================­­­­============== Copyright © 2017 Oracle and/or its affiliates. Oracle is a registered trademark of Oracle and/or its affiliates. All rights reserved. Other names may be registered trademarks of their respective owners. Oracle disclaims any warranties or representations as to the accuracy or completeness of this recording, demonstration, and/or written materials (the “Materials”). The Materials are provided “as is” without any warranty of any kind, either express or implied, including without limitation warranties or merchantability, fitness for a particular purpose, and non-infringement.
Views: 709 Connor McDonald
Update Statistics of All the Databases or Single Database in SQL Server
 
05:01
Update Statistics of All the Databases or Single Database in SQL Server SQL server DBA SQL server DBA tutorial SQL server DBA 2016 SQL server DBA 2016 tutorial sql server SQL server tutorial SQL server beginner tutorial SQL server tutorial 2016 SQL server interview SQL server interview question SQL server tutorial beginner to advance sql server 2016 tutorial for beginners sql server 2016 sql server interview questions and answer sql tutorial sql tutorial for beginners sql queries tutorial sql server management studio 2016
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08 08 Invisible Indexes
 
03:27
ORACLE
Views: 111 oracle ocm
1Z0-453 Dumps - OPN Certified Specialist 1Z0-453 Dumps
 
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1Z0-453 Dumps https://www.dumpssheet.com/braindumps/1Z0-453 Preparation Method For Oracle Industries 1Z0-453 examinations: The preparation of Oracle Industries 1Z0-453 Oracle Retail Merchandising System 13.2 Foundation Functional Implementer Essentials may be undertaken by the candidates using the subsequent preparation resources: 1Z0-453 Study Guides 1Z0-453 Video Tutorials Firstly, the Oracle Industries 1Z0-453 test could be prepared by using 1Z0-453 study guides. 1Z0-453 Study guides give deep, weighty materials on each exam topic. This makes 1Z0-453 study guides rather wearisome and unengaging for the students preparing for Oracle Industries 1Z0-453 examinations. In comparison to review guides, 1Z0-453 video lessons and discussions are less pain-staking and more intriguing for the pupils. Since each of the two planning signifies has its pros and cons; benefit out of their mutual benefits and pupils are recommended to utilize both methods. Students often commit the blunder of not taking the problem of going through the 1Z0-453 practice exams, throughout their 1Z0-453 Oracle Retail Merchandising System 13.2 Foundation Functional Implementer Essentials planning. Statistics have demonstrated a bad preparation isn't the cause of failure, in the majority of the cases. A bulk of pupils who are unable to clear the Oracle Industries 1Z0-453 Oracle Retail Merchandising System 13.2 Foundation Functional Implementer Essentials exhibit high levels of anxiety, which pushes them towards failure. Anxiety exists among the candidates of 1Z0-453 exams, predominantly because they are oblivious to they might be confronted by while attempting their Oracle Industries 1Z0-453 Oracle Retail Merchandising System 13.2 Foundation Functional Implementer Essentials. By heading going right through the 1Z0-453 practice tests, the pupils can, eliminate anxiety, as the cause of failure. Why Oracle Industries 1Z0-453 exams are essential? The Oracle 1Z0-453 examinations may be exceptionally essential and required in terms of the accomplishment of an appropriate, exciting career is involved. These Oracle 1Z0-453 examinations are perplexing and tough to obvious and get; but one cannot question their importance. Recommendations for the Preparation of Oracle Industries 1Z0-453 exams The candidates must make one thing specific: the Oracle 1Z0-453 examination preparing requires them to be acquainted with all the 1Z0-453 exam syllabus. Selecting a Dumpssheet The candidates significantly show shrewdness while picking a Dumpssheet. Info in relation to the Dumpssheet The content on the Dumpssheet’s 1Z0-453 exam questions are exceedingly informative and comprehensive. Excellent 1Z0-453 dumps are offered by the Dumpssheet to the candidates. A Oracle Industries 1Z0-453 exam replication is also offered. This enables the candidates to carefully practice for the Oracle 1Z0-453 exam using the format of the real exam. This replication also enables candidates to become aware of their own efficiencies and inefficiencies. The layout of this Dumpssheet has been created by the Oracle, fantastically. The Dumpssheet’s lay-out was designed so as to make it easy to use. Other essential characteristics of the Dumpssheet are: The Dumpssheet offers complete flexibility in relation to the search of any kind of Oracle 1Z0-453 examination. The consumers of the Dumpssheet usually stay acquainted with the upto-day knowledge as the Dumpssheet is recurrently updated. The McAfee anti-virus performs the job of safety of the customer’s bio data. The Dumpssheet permits candidates to become members of the Dumpssheet and discuss their experience with the Dumpssheet’s 1Z0-453 pdf dumps; along with viewing the remarks of these customers who have previously acquired knowledge of the Dumpssheet’s 1Z0-453 exam questions. If considered necessary, the Dumpssheet makes use of the feedback provided by customers to make variations to the Dumpssheet’s 1Z0-453 pdf. The Dumpssheet’s efficacy The following points emphasize the Dumpssheet’s efficacy: The unsuccessful candidates are came ultimately back their funds paid as Oracle Industries 1Z0-453 exam fee. The reimbursement of the examination payment by the Dumpssheet wholly depends on whether the candidate has informed the Dumpssheet within a month and also a half, about such occurring. The Dumpssheet offers efficient professional support and information to the candidates. The Dumpssheet gives its regular customers fabulous value cuts or more to 35% discount.
Views: 4 Aba Lukano
Database in hindi/Urdu Lecture 1 Introduction for beginner Vcomsats
 
01:07:41
Database in hindi|Urdu Database Management System or DBMS in short refers to the technology of storing and retrieving users’ data with utmost efficiency along with appropriate security measures. This tutorial explains the basics of DBMS such as its architecture, data models, data schemas, data independence, E-R model, relation model, relational database design, and storage and file structure and much more. Audience This tutorial will especially help computer science graduates in understanding the basic-to-advanced concepts related to Database Management Systems. Prerequisites Before you start proceeding with this tutorial, it is recommended that you have a good understanding of basic computer concepts such as primary memory, secondary memory, and data structures and algorithms. http://www.vcomsats.edu.pk/ Like, Comments, Share and SUBSCRIBE
Views: 11243 Virtual Comsats
What is ANOMALY DETECTION? What does ANOMALY DETECTION mean? ANOMALY DETECTION meaning
 
02:18
What is ANOMALY DETECTION? What does ANOMALY DETECTION mean? ANOMALY DETECTION meaning - ANOMALY DETECTION definition - ANOMALY DETECTION explanation. Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. In data mining, anomaly detection (also outlier detection) is the identification of items, events or observations which do not conform to an expected pattern or other items in a dataset.[1] Typically the anomalous items will translate to some kind of problem such as bank fraud, a structural defect, medical problems or errors in a text. Anomalies are also referred to as outliers, novelties, noise, deviations and exceptions.[2] In particular in the context of abuse and network intrusion detection, the interesting objects are often not rare objects, but unexpected bursts in activity. This pattern does not adhere to the common statistical definition of an outlier as a rare object, and many outlier detection methods (in particular unsupervised methods) will fail on such data, unless it has been aggregated appropriately. Instead, a cluster analysis algorithm may be able to detect the micro clusters formed by these patterns.[3] Three broad categories of anomaly detection techniques exist.[1] Unsupervised anomaly detection techniques detect anomalies in an unlabeled test data set under the assumption that the majority of the instances in the data set are normal by looking for instances that seem to fit least to the remainder of the data set. Supervised anomaly detection techniques require a data set that has been labeled as "normal" and "abnormal" and involves training a classifier (the key difference to many other statistical classification problems is the inherent unbalanced nature of outlier detection). Semi-supervised anomaly detection techniques construct a model representing normal behavior from a given normal training data set, and then testing the likelihood of a test instance to be generated by the learnt model.
Views: 5595 The Audiopedia
SSIS : Aggregate Calculation in Data Transformation and storage at Destination System
 
20:25
Calculation of Aggregate from extracted data from source and then store the aggregated data at the destination system
Views: 137 Data Science Center
Utility Industry - Outlier Detection
 
22:42
In the world of Utilities, the ability to monitor Outlier usage activity on the power network has become a major requirement. This ensures that the power generator companies can easily determine the dwellings across city or town districts that are consuming the most power, and can dynamically adjust the power network accordingly to satisfy demand or price charging rates. See this video to understand how this is done using Oracle Stream Analytics. ================================= To improve the video quality, click the gear icon and set the Quality to 1080p/720p HD. For more information, see http://www.oracle.com/goto/oll and http://docs.oracle.com Copyright © 2017 Oracle and/or its affiliates. Oracle is a registered trademark of Oracle and/or its affiliates. All rights reserved. Other names may be registered trademarks of their respective owners. Oracle disclaims any warranties or representations as to the accuracy or completeness of this recording, demonstration, and/or written materials (the “Materials”). The Materials are provided “as is” without any warranty of any kind, either express or implied, including without limitation warranties or merchantability, fitness for a particular purpose, and non-infringement.
Create Data Flows in Oracle Data Visualization
 
02:10
Create a data flow to transform data for use in reports. ================================= To improve the video quality, click the gear icon and set the Quality to 1080p/720p HD. ================================= To improve the video quality, click the gear icon and set the Quality to 1080p/720p HD. For documentation, see the following Oracle Help Center pages: * Analytics Cloud: http://docs.oracle.com/cloud/latest/analytics-cloud/analytics-cloud-visualize.htm * Data Visualization Cloud Service: http://docs.oracle.com/cloud/latest/data-visualization-cloud/data-viz-cloud_manage.htm * DV Desktop: http://docs.oracle.com/middleware/bidv1221/desktop/data-viz-onprem-manage.htm ================================= For more information, see http://www.oracle.com/goto/oll Copyright © 2017 Oracle and/or its affiliates. Oracle is a registered trademark of Oracle and/or its affiliates. All rights reserved. Other names may be registered trademarks of their respective owners. Oracle disclaims any warranties or representations as to the accuracy or completeness of this recording, demonstration, and/or written materials (the “Materials”). The Materials are provided “as is” without any warranty of any kind, either express or implied, including without limitation warranties or merchantability, fitness for a particular purpose, and non-infringement.
Test Data Generation in SQL with in 1 minute
 
21:26
This tutorial explains how can you generate test data for tables with in 1 minute using only sql queries. It explains the 3 components used in data generation. 1.Dual table 2.DBMS_RANDOM 3.Connect by level and how you can combine them easily to generate huge amount of data with in seconds. The video touches on how to handle constraints but doesn't go in depth. If all of you find it useful and give me a thumbs like. I will prepare a detailed video explaining everything in simple manner with real projects examples. If you require any clarifications for the video content.Drop a comment and I will try to resolve asap. Please don't forget to like the video and do subscribe to my channel
Views: 2121 Tech Coach
FIX :ORA-01017: invalid username/password; logon denied
 
03:49
copy and paste - sqlplus "/as sysdba" COPY PASTE BELOW LINE ALTER USER user_name IDENTIFIED BY new_password; ** user_name - example SYSTEM new_password - ENTER NEW PASSWORD Blog - maheshkarandeprojects.wordpress.com MUSIC : You're free to use this song and monetize your video, but you must include the following in your video description: Essence by Audionautix is licensed under a Creative Commons Attribution license (https://creativecommons.org/licenses/by/4.0/) Artist: http://audionautix.com/ Keywords: ora-01017 invalid username/password logon denied,ora-01017 invalid username/password logon denied 12c,ora-01017 invalid username/password logon denied oracle 12c,ora-01017 invalid username/password logon denied sap,ora-01017 invalid username/password logon denied ora-02063 preceding line from,ora-01017 invalid username/password logon denied rman,ora-01017 invalid username/password logon denied oracle 10g,ora-01017 invalid username/password logon denied standby database,ora-01017 invalid username/password logon denied (dbd error ocisessionbegin),ora-01017 invalid username/password logon denied dblink,ora-01017 invalid username/password logon denied brtools,ora-01017 invalid username/password logon denied brconnect,ora-01017 invalid username/password logon denied brbackup,ora-01017 invalid username/password logon denied bi publisher,ora-01017 invalid username/password logon denied burleson,ora-01017 invalid username/password logon denied sap backup,br0301e ora-01017 invalid username/password logon denied,log by0= ora-01017 invalid username/password logon denied,sap brtools ora-01017 invalid username/password logon denied,dg broker ora-01017 invalid username/password logon denied,ora-01017 invalid username/password logon denied c#,ora-01017 invalid username/password logon denied change password,ora-01017 invalid username/password logon denied connection string,ora-01017 invalid username/password logon denied cloud control,ora-01017 invalid username/password logon denied config tool,ora-01017 invalid username/password logon denied the connect descriptor was,ora-01017 invalid username/password logon denied oracle client,ora 01017 invalid username password logon denied error code 1017,ora-01017 invalid username/password logon denied system copy,ora-01017 invalid username/password logon denied at oci call ocisessionbegin,ora-01017 invalid username/password logon denied dgmgrl,ora-01017 invalid username/password logon denied db13,ora-01017 invalid username/password logon denied during switchover,data guard ora-01017 invalid username/password logon denied,ora-01017 invalid username/password logon denied discoverer,ora-01017 invalid username/password logon denied dbca,ora-01017 invalid username/password logon denied dbsnmp,ora-01017 invalid username/password logon denied switchover data guard,ora 01017 invalid username password logon denied enterprise manager,ora-01017 invalid username/password logon denied external user,ora-01017 invalid username/password logon denied emca,ora-01017 invalid username/password logon denied expdp,ora-01017 invalid username/password logon denied error,ora-01017 invalid username/password logon denied expired,ora 01017 invalid username password logon denied identified externally,ora-01017 invalid username/password logon denied in eclipse,ora-01017 invalid username/password logon denied for sys user,ora-01017 invalid username/password logon denied for sys,ora-01017 invalid username/password logon denied forms,ora-01017 invalid username/password logon denied for dblink,ora 01017 invalid username password logon denied oracle forms,failed ora-01017 invalid username/password logon denied,test failed ora-01017 invalid username/password logon denied jdeveloper,authentication failed ora-01017 invalid username/password logon denied,brconnect failed ora-01017 invalid username/password logon denied,failure test failed ora 01017 invalid username password logon denied,ora-01017 invalid username/password logon denied data guard,error ora-01017 invalid username/password logon denied dataguard,glassfish ora-01017 invalid username/password logon denied,oracle data guard ora-01017 invalid username/password logon denied,data guard switchover ora-01017 invalid username/password logon denied,ora-01017 invalid username/password logon denied hibernate,ora-01017 invalid username/password logon denied hr,how to resolve ora-01017 invalid username/password logon denied,how to solve ora-01017 invalid username/password logon denied,ora-28001 the password has expired ora-01017 invalid username/password logon denied,ora-01017 invalid username/password logon denied in 12c,ora-01017 invalid username/password logon denied in sql developer,ora-01017 invalid username/password logon denied in sap,ora-01017 invalid
Views: 13985 Mahesh Karande
"Why We Built Our Own Distributed Column Store" by Sam Stokes
 
42:41
How do you understand the behaviour of complex distributed systems in production? Distributed systems can fail in unpredictable, hard-to-detect ways. To track down problems quickly, you need to look for patterns and correlations in your data, trying different ways of breaking it down. "Does the problem occur on just one host, or one partition, or for particular customers?" Sub-second complex queries over large data volumes in real time: sounds like a tall order. The Scuba paper from Facebook describes an architecture that can do it: a low-latency, distributed, schemaless database. Scuba achieves fast queries by storing all data in memory. It stores the raw events, and fans out queries to multiple nodes, so it can support complex queries including aggregates (like mean and percentile statistics) and breakdowns by fields of arbitrary cardinality. Building Honeycomb, we needed a database with these properties, but we had additional constraints: multi-tenancy, cost to serve, and the limited resources of a startup. This talk describes Retriever, a custom-built database inspired by Scuba. Retriever ingests events from Kafka, and chooses disk over memory, using an efficient column-oriented storage model. I'll discuss interesting aspects of the implementation, and lessons learned from operating a hand-rolled database at production scale with paying customers. Sam Stokes HONEYCOMB Sam Stokes is a software engineer who can't leave well enough alone. He's compelled to fix broken things, whether they are software systems, engineering processes or cultures. After watching too many systems catch fire, he's building better smoke detectors at Honeycomb; in a past life he cofounded Rapportive and built recommendation systems at LinkedIn.
Views: 5143 Strange Loop
SESSION: Statistics, Heuristics and Row Estimations - Gail Shaw
 
01:16:13
Recorded on 2014-11-07 - Captured Live on Ustream at http://www.ustream.tv/channel/sqlpass
Views: 234 PASStv
What is a Database - Data Science Jargon for Beginners
 
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In this video I am going to explain what a database is for beginners in the data science industry. There are alot of terms , like databases, that are hard to understand in data analytics. ► Full Playlist Explaining Data Jargon ( https://www.youtube.com/playlist?list=PL_9qmWdi19yDhnzqVCAhA4ALqDoqjeUOr ) ► http://jobsinthefuture.com/index.php/2017/11/27/what-is-a-database-data-science-jargon-for-beginners/ A database is one of the most important aspects of the data science industry. This is where all the data is collected and stored for data analysts/scientists to explore sets upon sets of data. It is a collection of schemas, tables, queries, views, and reports. When someone refers to a database they are referring to a specific set of related data and the way it is organized. A database systems allow one to search through a database in an organized fashion to discover data patterns and insights. These are known more technically as Database Management Systems (DBMS). They include: MySQL MongoDB Oracle IBM's DB2 etc... Using these tools allows a data analyst/scientist to explore a specific sets of data or the entire database depending on the settings he/she applies. Because Database Management Systems and Databases share such close relations they are often casually related as one in the same. To Clarify: Database is the collection of data. Database Management System allows data analysts to access, explore, understand and utilize the data for analytical purposes. You can pull data from the database using a coding language known as SQL, but let's save that for the next article: Click here to learn about SQL: https://www.youtube.com/watch?v=9chhSN71DyQ&feature=youtu.be ------- SOCIAL Twitter ► @jobsinthefuture Facebook ►/jobsinthefuture Instagram ►@Jobsinthefuture WHERE I LEARN: (affiliate links) Lynda.com ► http://bit.ly/2rQB2u4 edX.org ► http://fxo.co/4y00 MY FAVORITE GEAR: (affiliate links) Camera ► http://amzn.to/2BWvE9o CamStand ► http://amzn.to/2BWsv9M Compute ► http://amzn.to/2zPeLvs Mouse ► http://amzn.to/2C0T9hq TubeBuddy ► https://www.tubebuddy.com/bengkaiser ► Download the Ultimate Guide Now! ( https://www.getdrip.com/forms/883303253/submissions/new ) Thanks for Supporting Our Channel! DISCLAIMER: This video and description contains affiliate links, which means that if you click on one of the product links, I’ll receive a small commission. This help support the channel and allows us to continue to make videos like this. Thank you for the support!
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