
Exam DP-900 Microsoft Azure Data Fundamentals Practice Exams
Description
The "Exam DP-900: Microsoft Azure Data Fundamentals Practice Exams" course is a robust preparatory course for those planning to take the DP-900 certification exam. This exam, organized by Microsoft, is a fundamental stepping stone for any individual seeking a career in data management and data analytics in the Microsoft Azure ecosystem.
This course has been meticulously designed to provide a comprehensive series of practice tests that closely emulate the actual exam. Covering core data concepts, how to work with relational and non-relational data on Azure, and an understanding of analytics workloads on Azure, these practice tests ensure you are well-prepared to tackle all aspects of the DP-900 exam.
Each practice test question comes with a detailed explanation, providing you with an understanding of why a particular answer is correct. This reinforces the fundamental principles and concepts you'll need to master for the exam.
Notably, the course doesn't require a background in data science or related fields. Whether you are an IT professional seeking to upskill, a developer aspiring to transition into data roles, or a student entering the field, this course provides an excellent opportunity to measure your readiness for the DP-900 exam and to gain confidence before sitting for the actual test.
By choosing the "Exam DP-900: Microsoft Azure Data Fundamentals Practice Exams" course, you're preparing yourself to make significant strides in the Azure data landscape, getting one step closer to certification and the numerous career opportunities that come with it.
The scope of the exam:
Describe ways to represent data
Identify options for data storage
Describe common data workloads
Identify roles and responsibilities for data workloads
Describe relational concepts
Describe relational Azure data services
Describe capabilities of Azure storage
Describe capabilities and features of Azure Cosmos DB
Describe common elements of large-scale analytics
Describe consideration for real-time data analytics
Describe data visualization in Microsoft Power BI
Is it possible to take the practice test more than once?
Certainly, you are allowed to attempt each practice test multiple times. Upon completion of the practice test, your final outcome will be displayed. With every attempt, the sequence of questions and answers will be randomized.
Is there a time restriction for the practice tests?
Indeed, each test comes with a time constraint of 120 seconds for each question.
What score is required?
The target achievement threshold for each practice test is to achieve at least 70% correct answers.
Do the questions have explanations?
Yes, all questions have explanations for each answer.
Am I granted access to my responses?
Absolutely, you have the opportunity to review all the answers you submitted and ascertain which ones were correct and which ones were not.
Are the questions updated regularly?
Indeed, the questions are routinely updated to ensure the best learning experience.
Additional Note: It is strongly recommended that you take these exams multiple times until you consistently score 90% or higher on each test. Take the challenge without hesitation and start your journey today. Good luck!
Who this course is for:
- data professionals who want to validate their knowledge and skills in data fundamentals on the Microsoft Azure platform and prepare for the DP-900 certification exam
- IT professionals or developers who work with data and want to gain a foundational understanding of data services on Microsoft Azure
- students or individuals studying data science, data engineering, or related fields who want to familiarize themselves with Azure data services and their core concepts
- professionals in non-technical roles, such as business analysts or project managers, who want to understand the basics of Azure data services to effectively collaborate with technical teams
- recruiters or hiring managers who want to evaluate the data-related knowledge and competency of job candidates applying for roles involving Microsoft Azure data services
- educators or trainers who want to assess the understanding and progress of their students in Microsoft Azure data fundamentals and guide them towards certification
Instructor
EN
Python Developer/AI Enthusiast/Data Scientist/Stockbroker
Enthusiast of new technologies, particularly in the areas of artificial intelligence, the Python language, big data and cloud solutions. Graduate of postgraduate studies at the Polish-Japanese Academy of Information Technology in the field of Computer Science and Big Data specialization. Master's degree graduate in Financial and Actuarial Mathematics at the Faculty of Mathematics and Computer Science at the University of Lodz. Former PhD student at the faculty of mathematics. Since 2015, a licensed Securities Broker with the right to provide investment advisory services (license number 3073). Lecturer at the GPW Foundation, conducting training for investors in the field of technical analysis, behavioral finance, and principles of managing a portfolio of financial instruments.
Founder at e-smartdata
PL
Data Scientist, Securities Broker
Jestem miłośnikiem nowych technologii, szczególnie w obszarze sztucznej inteligencji, języka Python big data oraz rozwiązań chmurowych. Posiadam stopień absolwenta podyplomowych studiów na kierunku Informatyka, specjalizacja Big Data w Polsko-Japońskiej Akademii Technik Komputerowych oraz magistra z Matematyki Finansowej i Aktuarialnej na wydziale Matematyki i Informatyki Uniwersytetu Łódzkiego. Od 2015 roku posiadam licencję Maklera Papierów Wartościowych z uprawnieniami do czynności doradztwa inwestycyjnego (nr 3073). Jestem również wykładowcą w Fundacji GPW prowadzącym szkolenia dla inwestorów z zakresu analizy technicznej, finansów behawioralnych i zasad zarządzania portfelem instrumentów finansowych. Mam doświadczenie w prowadzeniu zajęć dydaktycznych na wyższej uczelni z przedmiotów związanych z rachunkiem prawdopodobieństwa i statystyką. Moje główne obszary zainteresowań to język Python, sztuczna inteligencja, web development oraz rynki finansowe.
Założyciel platformy e-smartdata
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