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Helpful Books to Ace DP-900
By and large, candidates can incorporate the listed study guides from Amazon as they prepare for DP-900 so they have a better chance of passing the official test:
- ‘DP-900: Microsoft Azure Data Fundamentals: 110+ Exam Practice Questions with Detail Explanation and Reference Link’ by Analytiq Tech and Daniel Scott — this kindle guide contains more than 110 original and challenging sample questions for DP-900. What’s more is that each question is accompanied by detailed answers, which help students grasp why an answer is correct or incorrect, hence they can improve faster. In all, there are two entire mock tests in this e-book and the question type, time limit, structure, and passing score of those mock tests will exactly replicate that of DP-900, meaning students will receive the perfect practice. Taking mock tests such as these helps students assess their performance and identify the topics they are weak in. The question bank of this book is being constantly updated and improved using students’ feedback, and new items are added to the stock on a regular basis. The book even has an active Q&A forum online, where past and future candidates discuss the exam topics of DP-900 and share their test-taking experiences, all of which should facilitate further learning for potential candidates.
- ‘DP-900: Microsoft Azure Data Fundamentals 2020 Practice Exam (Solved Practice Test 120+)’ by Eaze Teach — Eaze Teach is one of the largest online IT content providers in the world and they have study guides & mock tests for technical exams of numerous IT vendors such as Linux, Cisco, and Microsoft. Plus, Eaze Teach even provides training courses to IT workers to succeed in their job positions. This almost 150-page paperback from such a provider is loaded with practice tests consisting of 120+ original and challenging questions for the Microsoft exam DP-900. These practice tests are meant to exactly replicate the actual DP-900 test, hence the structure, question types, time limit, and passing score are the same as DP-900. Significantly, each question in this book has been created in accordance with the official exam syllabus issued by Microsoft for DP-900, meaning they’ll cover all the necessary topics. Taking the mock tests in this book is a great way to assess where the candidate currently stands in terms of exam preparation and advance accordingly. Furthermore, these mocks will also help candidates identify gaps in their knowledge.
- ‘Exam Ref DP-900 Microsoft Azure Data Fundamentals’ by Daniel Seara & Francesco Milano — this is the official paperback provided by Microsoft for DP-900 test. Both the authors of this book are experienced IT veterans who have spent decades working with countless technologies. The target audience for this book is IT professionals, functional consultants, and business users. Simply put, it focuses on the main concepts and skills one would need in order to provide data solutions using Microsoft Azure data services out in the real world. Plus, such material promotes critical thinking in learners so they will be able to make better decisions on the job. More so, this book comprehensively covers each and every topic that candidates need to know for their DP-900 tests. This official paperback is also packed with ‘what if’ questions to further challenge the learners and teach them how to solve real-world IT problems. To easily blaze through the pages of this revision guide, candidates must be familiar with working with cloud-related data, Microsoft Azure data services, and know all the basic data concepts.
Microsoft DP-900 Exam Syllabus Topics:
| Topic | Details |
|---|---|
Describe core data concepts (15-20%) | |
| Describe types of core data workloads | - describe batch data - describe streaming data - describe the difference between batch and streaming data - describe the characteristics of relational data |
| Describe data analytics core concepts | - describe data visualization (e.g., visualization, reporting, business intelligence (BI)) - describe basic chart types such as bar charts and pie charts - describe analytics techniques (e.g., descriptive, diagnostic, predictive, prescriptive, cognitive) - describe ELT and ETL processing - describe the concepts of data processing |
Describe how to work with relational data on Azure (25-30%) | |
| Describe relational data workloads | - identify the right data offering for a relational workload - describe relational data structures (e.g., tables, index, views) |
| Describe relational Azure data services | - describe and compare PaaS, IaaS, and SaaS solutions - describe Azure SQL family of products including Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Azure Virtual Machines - describe Azure Synapse Analytics - describe Azure Database for PostgreSQL, Azure Database for MariaDB, and Azure Database for MySQL |
| Identify basic management tasks for relational data | - describe provisioning and deployment of relational data services - describe method for deployment including the Azure portal, Azure Resource Manager templates, Azure PowerShell, and the Azure command-line interface (CLI) - identify data security components (e.g., firewall, authentication) - identify basic connectivity issues (e.g., accessing from on-premises, access with Azure VNets, access from Internet, authentication, firewalls) - identify query tools (e.g., Azure Data Studio, SQL Server Management Studio, sqlcmd utility, etc.) |
| Describe query techniques for data using SQL language | - compare Data Definition Language (DDL) versus Data Manipulation Language (DML) - query relational data in Azure SQL Database, Azure Database for PostgreSQL, and Azure Database for MySQL |
Describe how to work with non-relational data on Azure (25-30%) | |
| Describe non-relational data workloads | - describe the characteristics of non-relational data - describe the types of non-relational and NoSQL data - recommend the correct data store - determine when to use non-relational data |
| Describe non-relational data offerings on Azure | - identify Azure data services for non-relational workloads - describe Azure Cosmos DB APIs - describe Azure Table storage - describe Azure Blob storage - describe Azure File storage |
| Identify basic management tasks for non-relational data | - describe provisioning and deployment of non-relational data services - describe method for deployment including the Azure portal, Azure Resource Manager templates, Azure PowerShell, and the Azure command-line interface (CLI) - identify data security components (e.g., firewall, authentication, encryption) - identify basic connectivity issues (e.g., accessing from on-premises, access with Azure VNets, access from Internet, authentication, firewalls) - identify management tools for non-relational data |
Describe an analytics workload on Azure (25-30%) | |
| Describe analytics workloads | - describe transactional workloads - describe the difference between a transactional and an analytics workload - describe the difference between batch and real time - describe data warehousing workloads - determine when a data warehouse solution is needed |
| Describe the components of a modern data warehouse | - describe Azure data services for modern data warehousing such as Azure Data Lake Storage Gen2, Azure Synapse Analytics, Azure Databricks, and Azure HDInsight - describe modern data warehousing architecture and workload |
| Describe data ingestion and processing on Azure | - describe common practices for data loading - describe the components of Azure Data Factory (e.g., pipeline, activities, etc.) - describe data processing options (e.g., Azure HDInsight, Azure Databricks, Azure Synapse Analytics, Azure Data Factory) |
| Describe data visualization in Microsoft Power BI | - describe the role of paginated reporting - describe the role of interactive reports - describe the role of dashboards - describe the workflow in Power BI |
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Explain the Techniques Involved in Working with Non-Relational Data on Microsoft Azure: 25-30%
- Identify the Fundamental Management Functions for Non-Relational Data: The examinees should have competence in explaining deployment and provisioning of non-relational data and the techniques for deployment. They also need the skills in identifying the components of data security, fundamental connectivity issues, and non-relational data management tools.
- Explain Non-Relational Data Workloads: The candidates should be able to explain the attributes of non-relational data and types of NoSQL and non-relational data. They need to have expertise in recommending the appropriate data stores and establishing them to utilize non-relational data.
- Explain Offerings of Non-Relational Data on Azure: The individuals need to have competence in explaining Azure Table storage, Azure File storage, Azure data service for non-relational workloads, Azure Blob Storage, and Azure Cosmos DB APIs.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-900
Skills measured
- Describe an analytics workload on Azure (25-30%)
- Describe how to work with relational data on Azure (25-30%)
- Describe how to work with non-relational data on Azure (25-30%)
- Describe core data concepts (15-20%)
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