AWS Certified Database-Specialty (DBS-C01) Exam Dumps

AWS-CDBS Exam Format | Course Contents | Course Outline | Exam Syllabus | Exam Objectives

Format : Multiple choice, multiple answer
Type : Specialty
Delivery Method : Testing center or online proctored exam
Time : 180 minutes to complete the exam

Introduction
The AWS Certified Database - Specialty (DBS-C01) examination is intended for individuals who perform in a database-focused role. This exam validates an examinees comprehensive understanding of databases, including the concepts of design, migration, deployment, access, maintenance, automation, monitoring, security, and troubleshooting.

Response Types
There are two types of questions on the examination:
- Multiple choice: Has one correct response and three incorrect responses (distractors).
- Multiple response: Has two or more correct responses out of five or more options.
Select one or more responses that best complete the statement or answer the question. Distractors, or incorrect answers, are response options that an examinee with incomplete knowledge or skill would likely choose. However, they are generally plausible responses that fit in the content area defined by the test objective.
Unanswered questions are scored as incorrect; there is no penalty for guessing.

The AWS Certified Database - Specialty (DBS-C01) examination is a pass or fail exam. The examination is scored against a minimum standard established by AWS professionals who are guided by certification industry best practices and guidelines.
Your results for the examination are reported as a score from 1001,000, with a minimum passing score of 750. Your score shows how you performed on the examination as a whole and whether or not you passed. Scaled scoring models are used to equate scores across multiple exam forms that may have slightly different difficulty levels.
Your score report contains a table of classifications of your performance at each section level. This information is designed to provide general feedback concerning your examination performance. The examination uses a compensatory scoring model, which means that you do not need to pass the individual sections, only the overall examination.

Domain 1: Workload-Specific Database Design 26%
Domain 2: Deployment and Migration 20%
Domain 3: Management and Operations 18%
Domain 4: Monitoring and Troubleshooting 18%
Domain 5: Database Security 18%
TOTAL 100%

Domain 1: Workload-Specific Database Design
1.1 Select appropriate database services for specific types of data and workloads
1.2 Determine strategies for disaster recovery and high availability
1.3 Design database solutions for performance, compliance, and scalability
1.4 Compare the costs of database solutions
Domain 2: Deployment and Migration
2.1 Automate database solution deployments
2.2 Determine data preparation and migration strategies
2.3 Execute and validate data migration
Domain 3: Management and Operations
3.1 Determine maintenance tasks and processes
3.2 Determine backup and restore strategies
3.3 Manage the operational environment of a database solution
Domain 4: Monitoring and Troubleshooting
4.1 Determine monitoring and alerting strategies
4.2 Troubleshoot and resolve common database issues
4.3 Optimize database performance
Domain 5: Database Security
5.1 Encrypt data at rest and in transit
5.2 Evaluate auditing solutions
5.3 Determine access control and authentication mechanisms
5.4 Recognize potential security vulnerabilities within database solutions

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The next premier motion: the place AI Can support With content thoughts

A robot reading amongst a great stack of books picture: Adobe

entrepreneurs see wonderful skills value in using synthetic intelligence (AI) to help the use case of recommending extremely targeted content to clients in real time. That use case scored the highest amongst forty nine use instances introduced to entrepreneurs in the 2021 State of advertising AI file by waft and the advertising synthetic Intelligence Institute. 

That use case scored a three.96, putting it on the cusp of “excessive cost” (four.0), with 5.0 being “transformative.” The AI advertising use situations that trailed in the suitable 5 include:

  • Adapt audience concentrated on in accordance with behavior and lookalike evaluation (three.92)
  • Measure return on investment by way of channel, campaign and overall (three.ninety one)
  • discover insights into suitable-performing content and campaigns (three.86)
  • Create records-pushed content material (three.82)
  • “Most web sites you go to today for corporations, a human is writing the suggestions to assert which content to recommend,” Paul Roetzer, CEO and founding father of the advertising synthetic Intelligence Institute, instructed CMSWire in a CX Decoded Podcast. “What are the connected articles? There is some basic tagging system for in the event that they study this, then study that. Most of them are human-powered. They wouldn't have a Netflix or a Spotify type algorithm it really is definitely researching preferences, is aware of the final 15 articles someone study, and the way far alongside he acquired into them. it be now not pulling another form of behavioral intent records. Most don't seem to be doing that.”

    The facts Conundrum

    Therein lies abilities, however it’s anything marketers and consumer journey professionals stay hopeful about: 54% of them advised CMSWire researchers in the State of Digital client journey 2021 record they see AI having colossal influences on digital client journey over the next two to 5 years. And most of them see “gaining actionable customer insights” (27%) as the area where they see probably the most capabilities.

    Roetzer spoke of it is difficult to discover basically good options to do that out-of-the-container. Noz Urbina of Urbina Consulting agreed, calling the know-how nascent.

    The bigger question for entrepreneurs past what kind of tools are available is will we have the data to assist the use case, in line with Roetzer. And do we have a strong groundwork of metadata, content material tagging and content material taxonomies, in response to Urbina.

    “You need sufficient facts, for one,” Roetzer referred to. “every so often the problem is smaller statistics, not always the cost. it's do you have got sufficient information to make it rewarding to try and use a computer gaining knowledge of algorithm to do this stronger than a human would? Do you've got ample traffic coming to your website to justify it?”

    linked Article: CX Decoded Podcast: purposeful Use circumstances of AI in advertising and marketing

    construct or purchase?

    Does it make more sense to customized-build an answer on AWS or Google, or is there an out-of-the-container answer to move plug in for a couple grand a month so as to gain knowledge of our users and start making techniques? These are some questions entrepreneurs should still be asking when due to the fact that the usage of AI for targeted content options, in line with Roetzer.

    “lots of people are in fact building on GPT-three, a know-how that got here out of OpenAI, which become variety of a lab that turned into developed to all of a sudden improve AI technology and then share it with the realm thus Open AI within the name," Roetzer mentioned.

    in response to OpenAI, 9 months considering the fact that the launch of the first business product, the OpenAI API points more than 300 functions. these 300 or so groups are building language technology competencies on the backbone of GPT-3, according to Roetzer. He cited conversion.ai and copy.ai, the latter which secured $2.9 million in funding in March. “What they (reproduction.ai) do is that they have a bunch of pre-proficient fashions so that you just get a subscription, and you'll actually go in, feed it some inputs … and it'll basically write ad reproduction for you, email copy. Very unique.”

    OpenAI officers cited the illustration of Algolia, which partnered with OpenAI to integrate GPT-3 with its advanced search know-how so as to create their new “answers” product that stronger is familiar with valued clientele’ questions and connects them to the selected part of the content material that answers their questions, in response to OpenAI officers.

    “Algolia solutions helps publishers and customer aid support desks query in natural language and surface nontrivial answers,” they wrote. “After working checks of GPT-3 on 2.1 million information articles, Algolia saw 91% precision or superior and Algolia become in a position to accurately answer complicated natural language questions.”

    related Article: 8 issues When picking out an AI advertising and marketing seller

    Responding to Behaviors

    Urbina spoke of the most standard formula for generating targeted content material in actual-time via AI is thru advice engines. according to Google builders, content-primarily based filtering makes use of merchandise elements to advocate different items similar to what the consumer likes, in response to their previous movements or explicit comments. 

    “in preference to most effective responding to a question, which is a definition of a search engine, concepts engines are responding to behaviors,” Urbina pointed out. “Your vicinity, your actions, your previous search behaviors, all of those issues are ambient facts that search engine technology can use to then be turned right into a advice engine. And synthetic intelligence and computing device learning, of route, are foundational for that. they will find patterns within the records and then they'll make appropriate suggestion.”

    essentially the most commonplace phrase after suggestion engine that marketers should find out about is "subsequent-choicest motion," in accordance with Urbina. marketers want to usher americans alongside the experience, and desktop gaining knowledge of helps to investigate numerous subsequent movements akin to sending an e mail, an SMS or providing counseled content that pops up.

    “And it is optimizing this at scale beyond human capability,” Urbina spoke of. "So the AI has to look at the user undertaking, and, based on the data of that user correlated towards what the entire other users say, investigate the subsequent neatest thing that I could suggest to circulation them alongside the event. So it's really the main area that we need to focus on for content recommendations: finding out how we will correlate the person's behaviors, against trends to establish the subsequent-most appropriate motion, which will also be suggested content.” 

    AI cannot Do It by myself

    What marketers regularly struggle with is leaving the AI to do all of the heavy lifting, according to Urbina. There exists the need to have a superb structured content material plan in region: labeling and making use of metadata on current content material and then constructing content material taxonomies.

    “one of the most a hit things we're doing now's building out the taxonomy so that the innovations engine has something to work with," Urbina stated. "A taxonomy of personas. A taxonomy of enterprise situations. A taxonomy of challenges. A taxonomy of benefits. A taxonomy of services. A taxonomy of content material types. A taxonomy of channels. if you haven't actually received this taxonomy in place that defines these buckets, what can the AI work with?”

    With a foundational content structuring application, marketers can define what makes a white paper, what makes a case examine, what makes a brochure, what makes a product overview etc, in response to Urbina.

    “That mentioned, if you will not have any taxonomies, you could unleash the AI over all of the content that exists," Urbina pointed out. "it may read it, use natural language processing to see what the topics are and what the general phrases are on your content material, and then you can organize that into becoming your specific taxonomy. So before you've received any of this going, you could definitely use AI to determine what your expertise taxonomies are and what your categorizations could be. In both case, a human have to book the AI."

    Why a 'Brute drive' method to AI received’t Work

    Most entrepreneurs just desire a data scientist to do all of this, however that’s not at all times feasible. extra, they often do not definitely know that if they participated in the organizing of the content round taxonomies and metadata and tagging, the complete operation could be lots greater beneficial.

    “and that's where I see this technology is absolutely nascent. And its effectiveness through brute force tactics is the aspect it really is usually slowing it down," Urbina spoke of.

    Can this AI tech supporting content-recommendation AI engines prefer up manufacturer tone? Roetzer talked about it's getting there.

    “It’s made huge leaps forward within the final three years,” Roetzer pointed out. “2013 became variety of this tipping aspect the place the AI caught up with the promise of what it might eventually do, and language is on the core of that. it's why voice assistants have definitely gotten respectable. it be why some conversational brokers have gotten first rate and why language knowing and generation have gone to completely new degrees in the final few years. And so the means to remember and replicate tone, if or not it's not there, it be coming. And there are lots of people placing a lot of money in the back of that sort of aspect."


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