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70-768 Developing SQL Data Models

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70-768 exam Dumps Source : Developing SQL Data Models

Test Code : 70-768
Test designation : Developing SQL Data Models
Vendor designation : Microsoft
free pdf : 37 actual Questions

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Microsoft Developing SQL Data Models

developing customized reply templates in Azure statistics manufacturing unit | actual Questions and Pass4sure dumps

(2019-Feb-eleven) Azure facts factory (ADF) provides you with a framework for developing statistics transformation solutions in the Microsoft cloud ambiance. these days added Template Gallery for ADF pipelines can pace up this construction procedure and provide you with valuable guidance to create further exercise projects for your pipelines. They naturally lengthy to are looking for if whatever common will also be extra adjusted. That customized design is fancy ordering an everyday pizza and then hitting the "personalize" button with the purpose to add just a few toppings of their alternative. it might be very wonderful then to withhold this custom-made "introduction" for future ordering. And Azure facts manufacturing facility has a similar option to shop your customized records transformation solutions (pipelines) as templates and reuse them later. when you open your statistics manufacturing facility UI, the preference to view and create your personal templates is obtainable for you. reside manufacturing unit mode does not assist you add customized solution templates into the gallery. This "Templates" office is simply attainable for you in Azure statistics manufacturing facility GIT integrated mode. 


right here is how i was able to verify this: Step 1: Saving pipeline as a template I've modified a pipeline that become initially produced from the "replica multiple data containers between File retailers" ADF template and brought my customized internet email Notification endeavor assignment at the conclusion of the workflow. I possess also made some extra changes to the identify and contour of this novel "replica information with electronic mail Notification" pipeline. Then i will be able to hit the "save as template" button on the Pipeline tab so as to add this present reply to the ADF Gallery. a novel window will demonstrate up with an overview of the entire recreation projects and Git Place for the brand novel template. In my case, this template became saved to my own GitHub. Step 2: Verifying your custom solution in the Template GalleryAfter efficaciously saving your ADF pipeline to the Template Gallery its designation will seem beneath the Template on the left-hand facet of the Azure statistics factory UI. in case you should change this template which you could either add these code changes in the GitHub template JSON files without laggard or drop and recreate it from the current pipeline once more. I additionally become able to descry my custom ADF pipeline reply "copy File with e-mail Notification" within the Template Gallery. Which grabs your consideration to peer your personal designation together with the Microsoft among the listing of template contributors. notwithstanding your introduction simplest exists within your personal facts factory workspace. Step 3: the utilize of your customized reply template you can both hit the ellipsis button beside the Pipelines and elect the "Pipeline from template" with the purpose to open the Gallery Template or proceed preempt to the "Templates" and determine your novel consumer pipeline solution. it will open up a window and give you to set linked features, or in a case of your own customized solution template, those options may additionally fluctuate.  incompatibility between a consumer reply ADF template and a cloned pipeline:which you can always clone an existing pipeline in ADF and deal with it as a template on your future building, youngsters, there are some changes between this fashion and pipeline from the Template gallery.1) You customized solution template will be saved in a divide "/template" Git region and it'll also be coupled with the happen.json file.2) A cloned pipeline will withhold the entire household settings from its guardian pipeline vs. interactive UI event to select/create further settings (e.g. linked capabilities) if you occur to add a novel pipeline from a template. in my view, I really liked this option of saving my customized ADF pipeline reply as a template. It helps me to deem for you to now create an entire novel statistics manufacturing unit as a template :-) official Microsoft documentation for reply templates in Azure facts factory: https://medical facility/solution-templates-introduction  My custom "replica File with email Notification" solution template in my own GitHub:

Microsoft is not The best strategy to slit back Wrap SQL Server In Containers | actual Questions and Pass4sure dumps

Going ahead, there's exiguous question that containers possess become firmly centered because the technology of preference for software deployment – as a minimum unless this sort of time as option techniques fancy serverless computing outgrow them in recognition. here's as actual these days within the industry as it was ten years ago when hyperscalers fancy Google first created usable and scalable containers

but organisations relent other concerns anyway scaling out, such as the want for containers to combine with their latest purposes and infrastructure. For an excellent many businesses, this skill wrapping containers round their windows Server techniques application and functions, as a minimum for on-premise deployments. although, Docker containers – which sparked the current commercial enterprise craze for using containers to aid developers circulate to a more quick release cadence – possess been designed round Linux. Seeing which passage the wind changed into blowing, Microsoft partnered with Docker returned in 2014 to port the Docker Engine to shun on windows Server, which also involved including some underlying mechanisms to assist containers into the working device.

we now possess covered Microsoft’s container advocate in additional ingredient earlier than, however the crux of it's that windows containers must be constructed from a restrained variety of ground pictures offered by using Microsoft that accommodate some or flagrant the windows services layer that functions muster upon to function. The upshot of here is that windows containers are a lot higher than these running on Linux, often several gigabytes in size.

This isn’t the best issue on home windows containers. A container will simplest shun if it is deployed on a server working the identical version of home windows because the ground lifelike from which it became created, that means that companies must rebuild their containers every time there is an up to date release of home windows Server. home windows containers are additionally most efficient supported on home windows Server 2016 and later, which aptitude that the numerous commercial enterprise firms which possess yet to migrate from prior releases of windows Server can't elect scholarship of containers. And the rub is placing ancient releases in novel containers is precisely what a lot of them would fancy to accomplish that they can assist legacy applications.

Microsoft isn't, youngsters, the simplest game on the town as far as containers on windows are concerned, and different platforms exist. One, Windocks, grew out of a port of Docker’s personal open source mission geared toward home windows, and uses a divide set of constructs to create and office containers that enables it to operate on both windows Server 2012 and home windows Server 2016.

First releases in 2016, Windocks has on the grounds that developed a spotlight on assisting industry customers that requisite to shun SQL Server interior containers, together with types from SQL Server 2008 onwards. As fraction of this slant, the platform now not best comprises the commonplace materiel that developers can utilize to create novel containers, but additionally automates the fashion of adding database copies to the container or mounting of a remote database, which can be a clone of the production database that the developer can toil with flagrant the passage through trying out before their code is promoted to construction repute.

according to Windocks, it has taken this fashion as a result of clients want a solution that wholly supports SQL Server databases apart from allowing them to modernise their utility stack with containers, and their aptitude to offer this has viewed the enterprise prefer up a few economic functions consumers such as John Hancock, Liberty Mutual, and Franklin Templeton Investments.

“The customers that we’re working with wish to modernise their plenary stack application birth, they requisite an reply that helps containers, because containers are the long run, they want a solution that comprises facts beginning, but they additionally crave an reply that works with their present techniques and infrastructure and isn’t constrained to containers, so in case you’ve bought builders engaged on a shared SQL server example, they want that to be supportable,” Windocks vice chairman Paul Stanton tells The subsequent Platform.

And one of the most key differences between the Windocks container technology and Microsoft’s official container advocate for windows turns out to be fairly superb: compatibility with existing purposes and methods.

“It isn't commonly mentioned, however SQL Server containers on the Microsoft home windows design don't even usher windows Authentication, which out of the gate suggestions it out for the vast majority of industry clients. And within the SQL server world, quantity shadow capabilities in SQL are the basis for most backup functions – these execute not operate with Microsoft’s SQL Containers,” Stanton claims.

This interestingly comes flagrant the passage down to the passage that Microsoft carried out containers on windows Server, copying the Linux mannequin where the containers are mostly remoted from the host operating system, which is why applications deserve to possess the code libraries they depend on inside the container with them. In distinction, Windocks applied a container mechanism whereby the container includes just the application, running as a windows service however created and managed with the Docker commands and API. (there's just a exiguous more to it than that, equivalent to resource management controls, but Windocks is coy about giving out plenary details).

The upshot of this is that SQL Server inside a Windocks container capabilities precisely fancy a traditional SQL Server instance, as a result of it really is practically what it is, however may also be deployed and managed by means of Docker as a relaxed “SQL Server sandbox”, in line with the firm.

There are further implications of this: whereas Microsoft’s containers require each and every container to be licensed as a virtual laptop (with a minimal four core license for each and every container), Windocks containers are not treated as a container beneath Microsoft licensing, as they execute not encompass any parts of the operating materiel code. As Windocks containers are clones of an installed/licensed SQL Server example, the containers are considered additional named instances, and flagrant SQL Server licenses enable for unlimited named circumstances on a licensed host.

meanwhile, the database cloning advocate that Windocks brought in 2017 offers users with the capacity to clone a quantity the usage of both windows virtual arduous Drives (VHDs) or with the aid of tapping into the photo capabilities built into commercial enterprise SAN arrays, and afterwards connect it to a SQL Server image when a container is provisioned at runtime.

within the case of VHDs, the father or mother VHD is a plenary reproduction replica of the facts volume, with “differencing disks” that deliver any changes, providing one or more writable cloned databases. Scripts are shun prerogative through the dad or mum VHD build, in response to Windocks, growing an “immutable artifact that contains user permissions, data protecting, and different preparations for regulatory and policy compliance”.

the Place a storage array is concerned, Windocks automates and manages the advent of a image of a extent, which is then mounted to the windows Server, and the databases in that extent uncovered to the person on the passage to opt for which of them they should toil with. flagrant of here's accomplished via household Dockerfile instructions and helps a big purview of industry SAN arrays – Windocks claims it has yet to find one that it cannot assist.

“We’ve bought purchasers that shun simple Storage, other shoppers working NetApp, others with EMC or Cohesity, and we’ve obtained customers that are using this technique to carry 25 TB facts warehouses to their developers. So, on-demand, we’ve bought a gadget at one customer that offers as much as 50 independent containers, and each can be running a 25 TB records warehouse, and so it’s literally over a petabyte of data online. They’re the usage of a simple Storage array with Windocks managing the records lifecycle of this dynamic information for construction and test,” Stanton says.

the most fresh supplant to the Windocks platform became the addition of assist for SQL Server Reporting functions (SSRS), Microsoft’s file producing device it's used by passage of many organisations to generate internet-based mostly and printed document-fashion reviews from records held in SQL Server databases, as well as other sources. This is available in the form of a brand novel Windocks SQL Server lifelike that includes the database engine and SSRS running inside a container.

based on Windocks, its valued clientele are the usage of this means to add SSRS aid to SQL Azure, which lacks this capacity, and Microsoft as a substitute touts power BI as its cloud-based reporting platform. firms would understandably opt to be in a position to continue to utilize the reviews that they've already gathered, each on premises and in the cloud.

general, Windocks does not issue to be trying to displace Microsoft’s home windows container expertise, which after flagrant has the foremost advantage in that it's baked into the working device from windows Server 2016 onwards. in its place, Windocks has concentrated on a number of key areas where Microsoft’s container aid falls short of enterprise requirements, comparable to when modernising functions that utilize SQL Server, whereas .web and Java, and different photos are also obtainable.

Windocks licenses start with a free community version that is limited to two simultaneous containers. Paid-for licenses delivery at $499 per thirty days for a server that supports 20 simultaneous containers.

Microsoft Azure SQL Database | actual Questions and Pass4sure dumps

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Microsoft Azure SQL Database (whose pricing varies) is a totally managed and neatly designed, relational cloud database with vast SQL engine compatibility and greater than a splash of desktop gaining scholarship of (ML). a powerful savor of familiarity stems partially from an effortlessly recognizable dashboard corresponding to flagrant things Microsoft. That feeling additionally partly rises from the convenience in the usage of favourite applications with out altering the code and the usage of your entire favorite SQL tools with out so much as taking pause. ML can provide automated advice in performance (such as counseled indexing), reliability, and security. builders and company analysts will likely esteem this Database-as-a-carrier (DBaaS) for flagrant of those causes. it truly is additionally why this providing earns an Editors' alternative in their DBaaS options review roundup, along with MongoDB Atlas.

Competitor IBM Db2 on Cloud is smooth to set up however Microsoft Azure SQL Database is benchmark to navigate. that is peculiarly so if you possess spent any time on Microsoft products in regularly occurring or on Microsoft Azure in specific which, I dare say, a pretty salubrious variety of individuals have. eventually count number, there are four.1 million databases, bringing the entire measurement to 154 petabytes (PB). There are 421,000 subscriptions pouring out 3 trillion batch requests per day. If a SQL database isn't what you're trying to find, then Microsoft presents alternatives in other cloud-primarily based products, similar to Azure Cosmos DB, a dispensed multi-model database; desk Storage, a NoSQL key-cost withhold for rapid pile the usage of semi-structured big information; and, Redis Cache, for top-throughput and low-latency, entry to scale Azure apps. Microsoft Azure capabilities also assist the MariaDB, MySQL, and PostgreSQL (aka Postgres) databases.

Pricing model

Microsoft Azure SQL Database pricing is staged throughout Elastic Pool, Managed illustration, and unique Database models. you'll find a customizable permeate calculator prerogative here for flagrant three alternatives. as an example, I used the calculator to compute the prices of a unique database in the South imperative u.s., calculated in the vCore buy mannequin on the regular direct Tier, in US greenbacks and priced by passage of the hour.

The vCore pricing mannequin is presently in preview and lets you scale compute, reminiscence, and storage one by one. One vCore equals one actual imperative processing unit (CPU), so I selected four in the permeate equation, which gave me 28 gigabytes (GB) reminiscence at $1.13 per hour. Likewise, storage is scalable and can be configured between 5 GB and four terabytes (TB) at 1GB increments. The permeate for that is $0.138 per GB per 30 days. Backup storage is free while vCore is in preview. Ditto for inputs/outputs (I/O). commemorate that the company essential Tier pricing is significantly greater. 4 CPUs can permeate $2.9613 per hour and storage expenses $0.30 GB per 30 days, but backup storage and information I/O are noiseless free while VCore pricing remains in preview. A Database Transaction Unit purchase mannequin incorporates a bundle of 2GB compute and 2GB storage for $4.89 per month.

Azure Hybrid utilize profit for SQL Server allows you to utilize your on-premises windows Server licenses to shun windows digital machines (VMs) on Azure for less funds. as an example, it saves you as much as 30 percent on each the only database and elastic pool alternate options in the vCore mannequin.

Database Transaction Unit (DTU) is the leading pricing mannequin, that means Microsoft bundles compute, memory, and storage. as an example, within the household tier, 10 DTUs, which involve 250 GB of storage, prices $0.0202 per hour. added facts storage above it really is priced at $0.085 per GB per 30 days, whereas lengthy-term backup storage is an extra $0.046 per GB per 30 days. that you can proceed tremendous affordable through identifying the basic five DTUs, so as to cost you $5 monthly.

guide plans start at $29 per month. SQL Database possibility Detection prices the equal as the Azure safety middle accustomed tier at $15 per node per thirty days; both are also integrated. A node is defined as one SQL database server.

little by little

The Microsoft Azure SQL Database portal is brilliantly designed. you can entry a big variety of points without laggard from the browser. The setup manner is simple and takes only a minute or two. There is no requisite to installation anything however, fancy Amazon Relational Database provider and Google BigQuery, you execute want a mothership account first. You won't want a Microsoft Outlook electronic mail address, despite the fact, to set up a Microsoft account.

after you possess a Microsoft account id and password, that you would be able to create an SQL Database with a free Microsoft Azure trial account. or you can buy an account or utilize your latest account. symptom in together with your Microsoft account. the entire settings you are going to want are on the left-hand facet of the monitor in the portal.

once on the portal, utilize Connection Libraries to opt for the language and operating system drivers you want to utilize to combine with Azure SQL Database or Microsoft SQL Server. click novel to spin up a brand novel database during the Azure market. There you are going to elect the pricing tier, identify the database, establish a supply and the fancy to installation the database in the cloud. you might be now not in reality establishing infrastructure so or not it's painless to do.

you can populate it with current records units obtainable through the portal, or create a immaculate database and load your own statistics. if you are migrating facts from Microsoft excel to SQL Database, then that you would be able to execute it in a unique step through the utilize of the SQL Server Import and Export Wizard, SQL Server Integration features (SSIS), or the OPENROWSET function. you are going to want to utilize Managed illustration if you are migrating a Big number of latest SQL Server databases or relocating legacy purposes from on-premises or VMs to SQL Database. if you locate any of this overwhelming or perplexing, then query your database administrator (DBA) to assist you establish it up. but clients with as a minimum some adventure with databases will probably locate this fashion handy to observe. If flagrant you possess completed before is utilize spreadsheets, even though, then you definately'll workable requisite a hand along the manner, both out of your DBA or from Microsoft guide.

As to my testing event, once on the portal, I clicked "All supplies" on the left-hand side of the divulge to rep to the test account Microsoft supplied me. From the substances list, I clicked "SiteEE," one of the Azure SQL databases. The next monitor presented me with an inventory of Quickstart tutorials, which can be value your time to explore. however, the gadget is intuitive, and many clients will with no distress be able to find their fashion on their own. you could additionally promptly launch an app by clicking the "Create a DevOps project" button on this reveal.

but returned to my verify database. My SiteEE dashboard puts everything at my fingertips from the endeavor log, query Editor, and a list of characteristic settings, to lots of efficiency visualizations, database properties and danger alerts.

In a few clicks, I deploy a geo-replicated secondary in case my fundamental suffers an outage. This lets me exploit failovers so I live in compliance with rules and inner guidelines. You can Make as lots of these as you desire, however be cautious as it will possess an consequence on your prices.

It changed into simply as handy for me to execute every exiguous thing else from viewing vulnerability assessments to scaling up or down with a slide bar to manage my useful resource utilize and fees. there's a value calculator there, too, similar to the one IBM Db2 on Cloud has, so i will descry funds possess an impact on from my scaling alterations immediately.

The Toolbox

that you may utilize flagrant your favourite SQL materiel with this database. App features makes it smooth to convey alongside apps devoid of altering the repose within the code. machine researching in Azure SQL Database can insinuate records indexing and other efficiency advancements.

facts Clarification characteristic and Dynamic information covering are each efficient in making sure your data is compliant with strict privacy laws, such as compliance with the time-honored facts protection rules (GDPR) and in proposing an audit trail. The Geo-replication feature even lets you exploit vicinity of failovers and to fix in the equal belt because the simple.

extra, SQL Server management Studio is a standalone application app used to configure and exploit flagrant Azure SQL Database add-ons. And the free device, Microsoft SQL Operations Studio, can be used to manage Azure SQL Database on macOS and Linux.

Microsoft Azure has 50 regions world wide and a hundred and forty nation areas. That closely outnumbers most cloud suppliers. It potential users will locate it effortless to belt apps near to their statistics and their customers to enrich performance and reduce lag, and to be in stronger compliance with regional regulations.

which you could try the complete SLA for Azure SQL Database, but in a nutshell, they guarantee at least ninety nine.ninety nine percent uptime. lots of advocate plans are available, ranging from $29 per month to a $1,000 per month.

SQL Database instantly performs full, differential, and transaction log backups for aspect-in-time restores (PITRs) at no additional cost. the primary plenary backup is scheduled automatically after a database is created. Then plenary database backups are weekly, differential database backups elect Place each few hours, and transaction log backups are performed each 5 to 10 minutes. clients can examine geographical areas for backup and restore data copies.

ordinary, Microsoft Azure SQL Database is one of the easiest cloud databases to Make utilize of. or not it's additionally outstanding in assisting you with GDPR compliance and lag controls through providing more Place offerings than any of its competitors.

Microsoft Azure SQL Database


final analysis: Microsoft Azure SQL Database is a brilliant Database-as-a-provider (DBaaS) reply for developers, enterprise analysts, and database directors given its ease of utilize and exemplary controls.

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Developing SQL Data Models

Pass 4 sure 70-768 dumps | 70-768 actual questions |

Following a notion for SQL, architect creates NoSQL data modeling notation | actual questions and Pass4sure dumps

Emerging NoSQL data styles bring rapid evolution for innovative applications. But NoSQL also creates challenges. NoSQL systems can proceed into production quickly, sometimes without any upfront schema creation at all. However, analyzing NoSQL system output can be difficult when basic data modeling practices are eschewed. This was on Ted Hills' intellect when he set out to create a modeling notation that spanned SQL and NoSQL styles, enabling better NoSQL data modeling.

As an enterprise architect working on evolution and governance of enterprise data models at LexisNexis, Hills has seen efforts to incorporate SQL and NoSQL structured and unstructured data assets up close. In his novel book, NoSQL and SQL Data Modeling, Hills describes Concept and remonstrate Modeling Notation, or COMN (pronounced "common"), which shows how to bring NoSQL under the bigger modeling tent. They first heard him converse about COMN at Enterprise Data World 2016 and caught up with him more recently to debate these issues.

How did you approach to descry the requisite for a novel notation for data modeling?

Ted Hills: I possess used mostly entity relationship [ER] modeling in my work, as well as the Unified Modeling Language [UML] for software design. I was trying to model a metadata model and create it is really tough to execute in ER, in that a fundamental assumption of ER is that flagrant data is eventually going to be placed in tables. But that is not what the target is necessarily going to be if the target is a NoSQL database.

I create there were things I just could not curve or stretch the ER notation to represent. At a physical level, the two things that ER can't limn are arrays and nested types. At the ratiocinative level, it is more subtle.

Then I tried [Unified Modeling Language] and that didn't work. I tried fact-based modeling and that didn't toil out either.

You see, flagrant three of those modeling notations had some problems -- mistakes made at the fundamental level. And I decided I would try to address those by developing my own notation, COMN. Now, understand, COMN is open to the other methods in that you can elect ER, UML or fact-based models and express them in COMN. That is because it covers flagrant the identical concepts, but it covers them more universally.

Doesn't it seem, sometimes, that the rush to NoSQL obscures the requisite for NoSQL data modeling?

Hills: Well, we've seen the whole NoSQL world getting carried away with the fact that they did not possess to Tell the DBMS [database management system] what the schema of the data was before they started storing it -- which is wonderful. You don't possess to spend weeks or months developing your data model before you can store your first byte. You can just store your data and design out the model later.

But they also saw a lot of folks -- especially those working more exclusively in software evolution environments -- who had never worked on data projects per se that were making the typical mistake. They would just hurl the data in, without any thought to its schema, and then find later that their queries didn't perform, that they were missing data, that they didn't possess keys for identifying subsets of the data that were important. The results could be tragic.

Data projects that start with data models usually fare better than those that don't. That observation remains moral even in the NoSQL world. The Big incompatibility with NoSQL is that, since the database doesn't accommodate you to execute a model, it's more likely developers will just hurl data in and then struggle to Make things toil later on.

Still, you've remarked that NoSQL expands the toolbox for application builders in some ways, and that relational DBMSes possess some limitations.

Hills: Sure, if your only physical implementation platform is an RDBMS, there are limitations. One is that you are forced to store any repeating data in its own table and you are forced to give it a key whether the key has ratiocinative significance or not. But the fact is that the relational model of data is poorly understood -- in reality, it's about how to speculate about data, not about how you store data. Some things about the relational model are just not taught and are not well-known.

Give us an thought of what they can expect to learn when they read NoSQL and SQL Data Modeling. Why execute they requisite a novel notation?

Hills: Each of the existing notations has built-in assumptions that Make it really arduous to speculate about fundamental data issues. I felt that they had to start from scratch. One of the things the novel model makes evident is that decisions about keys are sometimes ratiocinative and sometimes physical. I, and others, possess discovered that, when you possess to Make a decision about a key, it is really sharp to descry if that decision needs to be expressed in the ratiocinative model or should only be expressed in the physical model. In the ER notation, it is often needed simply because that model doesn't allow you to possess nested types or arrays. But sometimes you requisite that key for ratiocinative reasons -- and then it belongs in the ratiocinative model. But no other notation can allow you to possess the key in one or the other [levels]. That wasn't workable before COMN.

Ruby on Rails: SQL Database & Models | actual questions and Pass4sure dumps

What is a database?

Hmmm... The first thought that comes to my intellect is “something” that stores data, information.

But this “definition” is quite imprecise! An array, a hash, a linked list, or any data structure can be “something” that is able to store data.

When you rotate off the computer, you lose every data values that were stored in that array (the identical as flagrant data structures). So it’s not a salubrious thought to store flagrant my precious data.


We requisite to decipher two problems here:

  • Store data and rep it anytime they want.
  • Store data in an organized and structured way, so they can rep it in an smooth way.
  • Should I store flagrant the data in a notepad? Just establish flagrant the information inside it separated by commas, deliver the txt file, and done. Now I can open it and rep flagrant the data I want. They can store data and rep it anytime… problem solved!

    We solved this problem, but they missed the other. Now flagrant the data is stored and they don’t lose it. But not well-structured in the file. They requisite the rule to store and rep data in an organized and well-structured form.

    Let’s speculate about how can they organize the data in a well structured way.

    What about organizing flagrant the data in tables?

    So, what they possess here: They possess the table’s header (columns name: First Name, ultimate Name, Address, etc) and it’ll possess values that we’ll store. For example, if they want to store the string “Mickey” (the value), it’ll be stored in the “First Name” column.

  • Table: let’s divulge People
  • Columns: First name, ultimate Name, Address, etc
  • Rows: in this case, they can divulge that a row can be a person with, for example, first designation “Mickey”, ultimate designation “Mouse”, address “123 Fantasy Way”, etc.
  • Fields: flagrant data stored in the database.
  • And now they possess a well-structured passage to store data: Table way!

    How about get, delete, insert, and update data?

    We’ll utilize SQL language (I’ll not mention NoSQL world!) to exploit data. Let’s rep the basics!

  • GET: if they want to rep flagrant data (person) from People table, they requisite to select it from that table.
  • The (*) symbol means that it will select flagrant columns from People table. If they can rep flagrant columns, they can specify which columns they requisite for this select.

    2. DELETE: they want to delete flagrant data from their People table.

    But it’s not common to delete flagrant data from a table. They usually utilize a condition to delete, fancy “I want to delete flagrant people under age (less than 21 years old)”. They will learn it later in this post!

    3. INSERT: they will insert/store data into the table.

    or they can specify which columns they want to insert data.

    4. UPDATE: they possess stored data, but they want to update it.

    Using conditions in our queries

    Now they can utilize SQL language to query (select, delete, insert, update) data.

  • But if they want to delete just records with ultimate designation Kinoshita?
  • Or if they want to update a specific person with first designation Leandro and ultimate designation Kinoshita?
  • Or just select flagrant data from people table and sorted by age from younger to older?
  • Yeah, they utilize conditions fancy where and order by and operators fancy or and and. Let’s descry some examples:

  • Deleting flagrant records from people table with ultimate designation Kinoshita.
  • Updating flagrant records from people table with first designation Leandro and ultimate designation Kinoshita.
  • Selecting flagrant records from people table but order by age. (in ascending order → ASC)
  • Relationship between tables

    We know how to execute queries (with or without conditions). Let’s understand how the tables’ relationship works.

  • One to One (1–1): it’s about a relationship between two tables in which one can only belong with the other. e.g. A person has one passport and that passport belongs to that specific person. So in this example, they possess table People, table Passports and a 1–1 relationship.
  • One to Many (1-n): it’s about a relationship between two tables in which a record from one table can reference many records from another. e.g. Imagine an e-commerce platform: users, orders, products, payments, etc. A user can possess many orders, and each order belongs to that specific user. So in this example, they possess table Users, table Orders, and a 1-n relationship.
  • Many to Many (n-n): it’s about a relationship between two tables in which a record from one table can reference many records from another. And a record from another can also reference many records from the one. e.g. They possess again the e-commerce platform: they divide products into categories. A category has many products (Category Technology has many products fancy cell phones, notebooks, etc) and a product can belong to many categories (Product Cellphone belongs to Technology and Electronics Categories). So in this example, they possess table Products, table Categories, and an n-n relationship.
  • Rails Mode ON

    We understood the acceptation of databases, tried some basic queries, and made the relationship between tables. But how can they utilize that scholarship in the Ruby on Rails and web evolution World?

    First of all: Rails is Rails. The Database is Database. Is it obvious? But people usually rep confused about that.

    A User model can limn a Users table. But the model isn’t the table.

  • In the database, they possess tables and rows.
  • On rails, they possess models (classes) and objects.
  • Imagine a blog site. The blog needs an author for each post. So they create an Authors table with some columns (first_name, last_name, etc)

    .. in the migration, they add columns first_name, last_name, email, birthday, email, created_at, and updated_at. (created_at and updated_at are created by the t.timestamps code.

    So they created a migration (Ruby code), shun rake db:migrate command in the terminal and it generates a table Authors with first_name, last_name, email, birthday, email, created_at, and updated_at columns.

    Back to Rails, they can create an Author model:

    So now they possess an Authors table with some columns and an Author model.

    Using Rails Console

    Open the terminal and kind bundle exec rails c. Remember, they are in the RAILS console, so they possess classes, objects, attributes, etc.

    Relationship on Rails

    We created an Authors table/model. What they requisite now is a Posts table/model. An author has many posts and a post belongs to a specific author. The relationship here is one to many (1-n). Remember?

    So when they create a Posts table, they requisite to store a reference to the post’s author (column author_id in the Posts table). It’s known as the foreign Key.

    And how execute they relate the models?

    author has_many posts post belongs_to an author Using Rails Console

    * Quick explanation about has_many and belongs_to. Both codes are methods defined on ActiveRecord class. If you see, they create their models inheriting from ActiveRecord::Base.

    Remember on Ruby Foundation that they studied about remonstrate Oriented Programming, the Inheritance part? This is why they can utilize has_many and belongs_to methods without defining it anywhere on their application. Rails handles it for us.

    If you want to understand this concept deep, clone the Rails repo or understand the Behind the Scenes of the ‘Has Many’ active Record Association.

    Queries on Rails

    We can query using ActiveRecord methods:

  • all: rep flagrant objects from a specific model.
  • Behind the scenes, it is executing the SELECT * FROM posts query.

  • find: Using find they can rep the remonstrate by the id (primary key).
  • Behind the scenes, it is executing SELECT * FROM posts WHERE id = 1 query.

  • where: rep the objects that pass the conditions.
  • Behind the scenes, it is executing SELECT * FROM posts WHERE title = 'Database & Rails'query.

  • order: Sort flagrant objects based on a column.
  • Behind the scenes, it is executing SELECT * FROM posts ORDER BY created_at DESC query.

    That’s all!

    We erudite a lot here. I hope you guys could prize the content and learn more about how the Databases and Rails models work.

    This is one more step forward in my journey to learning and mastering Rails and web development. You can descry the documentation of my complete journey here on my Renaissance Developer publication.

    Have fun, withhold learning and coding.

    Exam Ref 70-768 Developing SQL Data Models | actual questions and Pass4sure dumps

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