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John Christopher

We really hope you'll agree, this training is way more than the average course on Udemy.

Have access to the following:

  • Training from an instructor of over 25 years who has trained thousands of people and also a Microsoft Certified Trainer

  • Lecture that explains the concepts in an easy to learn method for someone that is just starting out with this material

  • Instructor led hands on and simulations to practice that can be followed even if you have little to no experience

TOPICS COVERED INCLUDING HANDS ON LECTURE AND PRACTICE TUTORIALS:

Introduction

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We really hope you'll agree, this training is way more than the average course on Udemy.

Have access to the following:

  • Training from an instructor of over 25 years who has trained thousands of people and also a Microsoft Certified Trainer

  • Lecture that explains the concepts in an easy to learn method for someone that is just starting out with this material

  • Instructor led hands on and simulations to practice that can be followed even if you have little to no experience

TOPICS COVERED INCLUDING HANDS ON LECTURE AND PRACTICE TUTORIALS:

Introduction

  • Welcome to the course

  • Understanding the Microsoft Environment

  • Having a Solid Foundation of Active Directory Domains

  • Having a Solid Foundation of RAS, DMZ, and Virtualization

  • Having a Solid Foundation of the Microsoft Cloud Services

  • Order of concepts covered in the course

Setting up for hands on

  • IMPORTANT Using Assignments in the course

  • Creating a free Azure Account

  • Activating Entra ID P2 license

Describe ways to represent data

  • Features of structured data

  • Features of semi-structured

  • Features of unstructured data

Identify options for data storage

  • Understanding formats for data files

  • Relational databases as a type of data storage

  • Creating a relational database in Azure using Microsoft SQL

  • Installing SQL Server Management Studio (SSMS) for connecting to SQL

  • Connecting to a SQL database with SSMS

  • Non-relational databases as a type of data storage

  • Creating a non-relational database in Azure using Microsoft Cosmos

  • Connecting to a Microsoft Cosmos database

Describe common data workloads

  • Features of transactional workloads

  • Features of analytical workloads

Identify roles and responsibilities for data workloads

  • Responsibilities for database administrators

  • Permissions in Azure regarding a database administrator

  • Responsibilities for data engineers

  • Permissions in Azure regarding a data engineers

  • Responsibilities for data analysts

  • Permissions regarding a data analysts

Describe relational concepts

  • Features of relational data

  • Normalization and why it is used

  • Creating an Azure VM with Microsoft SQL server

  • Using common structured query language (SQL) statements

  • A look at common database objects

Describe relational Azure data services

  • Azure SQL Family: Azure SQL Database, SQL Managed Instance, SQL Server on VMs

  • Azure database services for open-source database systems

Describe capabilities of Azure storage

  • Understanding the capabilities of Azure storage accounts

  • Creating a storage account to explore Blob, File, & Table storage capabilities

  • Securing a Azure storage account

  • Utilizing Azure Blob storage

  • Utilizing Azure File storage

  • Utilizing Azure Table storage

Describe capabilities and features of Azure Cosmos DB

  • Use cases for Azure Cosmos DB

  • Understanding the Azure Cosmos DB APIs

  • Deleting the existing Cosmos DB before moving on

  • Creating a new Cosmos DB account for NoSQL

  • Adding and querying data within a Cosmos DB for NoSQL

  • Cleaning up our lab environment to this point

Describe common elements of large-scale analytics

  • Considerations for data ingestion and processing

  • Understanding Azure Data Lake storage

  • Creating an Azure Data Lake storage account

  • Understanding Azure Databricks

  • Visualizing Azure Synapse Analytics

  • Registering Azure Synapse as a resource provider in Azure

  • Setting up a SQL DB and server for use with Azure Synapse Analytics

  • Creating a Azure Synapse workspace and Data Lake Storage account

  • Concepts of SQL Pool usage with Azure Synapse Analytics

  • Purposes of Azure HDInsight

  • Understanding Azure Data Factory

  • Setting up an Azure Data Factory resources

  • Using Azure Data Factory to copy data into Azure Synapse Analytics <AZ-305>

Describe consideration for real-time data analytics

  • Understanding the difference between batch and streaming data

  • Concepts of Azure Stream Analytics

  • Creating an Azure Stream Analytics job for real-time analytics

  • Benefits of using Apache Spark

  • Cleaning up the existing resources before moving on

Describe data visualization in Microsoft Power BI

  • Capabilities of Power BI

  • Downloading and installing Power BI Desktop

  • Creating a database with data for testing Power B

  • Connecting Power BI to a SQL database and performing an import

  • Features of data models in Power BI

  • Using the appropriate visualizations for data

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What's inside

Learning objectives

  • Learn the concepts and perform hands on activities needed to pass the dp-900 exam
  • Gain a tremendous amount of knowledge involving data processing in microsoft azure
  • Get loads of hands on experience with microsoft azure data processing technologies!
  • Utilize hands on simulations that can be access anytime, anywhere!

Syllabus

Having a Solid Foundation of RAS, DMZ, and Virtualization
Having a Solid Foundation of the Microsoft Cloud Services
DONT SKIP: The first thing to know about Microsoft cloud services
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Career center

Learners who complete DP-900 Azure Data Fundamentals hands on course with sims will develop knowledge and skills that may be useful to these careers:
Database Administrator
A Database Administrator is crucial for managing and maintaining an organization's databases, ensuring their availability, performance, and security. This work involves tasks like installing, configuring, and upgrading database servers, as well as monitoring database health and implementing backup and recovery strategies. The DP-900 Azure Data Fundamentals course is exceptionally well-suited for someone pursuing this role, as it directly addresses responsibilities for database administrators, including permissions in Azure. You will gain hands-on experience with creating relational databases in Azure using Microsoft SQL and connecting with SQL Server Management Studio. Furthermore, the course delves into securing Azure storage accounts and understanding capabilities of Azure storage, all vital for a successful Database Administrator. This foundational knowledge in relational and non-relational databases within the Azure environment is highly relevant for establishing a strong career path.
Data Engineer
A Data Engineer builds and maintains the infrastructure for data processing, ensuring that data is readily available, reliable, and optimized for analytical and operational uses. This involves designing, constructing, installing, and managing data pipelines and data storage solutions. The DP-900 Azure Data Fundamentals course is an excellent starting point for aspiring Data Engineers, as it explicitly covers responsibilities for data engineers, including their permissions in Azure. You will gain practical experience with Azure Data Lake storage, Azure Databricks, Azure Synapse Analytics, Azure HDInsight, and critically, Azure Data Factory for data ingestion and processing. Understanding both relational and non-relational data storage, along with large-scale analytics concepts, provides a comprehensive foundation for designing robust data solutions. This course directly equips you with the fundamental Azure data processing technologies essential for this role.
Big Data Engineer
A Big Data Engineer designs, builds, and manages large-scale data processing systems and pipelines to handle massive volumes of data, often leveraging distributed computing frameworks. This role typically requires expertise in tools for ingesting, transforming, and storing big data. The DP-900 Azure Data Fundamentals course is highly relevant for aspiring Big Data Engineers, as it covers critical components of large-scale analytics in Azure. You will gain practical experience with Azure Data Lake storage, Azure Databricks, Azure Synapse Analytics (including SQL Pool usage), Azure HDInsight, and Azure Data Factory. The course also discusses considerations for real-time data analytics, concepts of Azure Stream Analytics, and the benefits of Apache Spark, all fundamental to big data processing. This comprehensive exposure to Azure's big data ecosystem is a strong start for this demanding career.
SQL Developer
A SQL Developer designs, develops, and maintains databases and queries using Structured Query Language. Their work involves creating tables, writing complex queries, stored procedures, and ensuring efficient data retrieval and storage. The DP-900 Azure Data Fundamentals course is an excellent resource for anyone aiming to become a SQL Developer, providing a strong practical foundation. You will gain extensive hands-on experience by creating relational databases in Azure using Microsoft SQL, installing SQL Server Management Studio, and connecting to SQL databases. The course meticulously covers using common SQL statements and understanding common database objects. Beyond basic SQL, it introduces the Azure SQL Family services, providing context for modern cloud-based SQL development. This concentrated focus on SQL within Azure is highly beneficial for this career path.
Data Analyst
A Data Analyst interprets complex datasets to identify trends, patterns, and insights that can inform business decisions. Their work involves collecting data, cleaning it, and then presenting findings through reports and visualizations. For individuals interested in becoming a Data Analyst, the DP-900 Azure Data Fundamentals course is highly beneficial. The course specifically outlines responsibilities for data analysts and their associated permissions within Azure. You will learn about data representation, common analytical workloads, and particularly, gain hands-on experience with Microsoft Power BI. This includes connecting Power BI to a SQL database, creating data models, and using appropriate visualizations to present insights effectively. Understanding how to work with structured, semi-structured, and unstructured data, coupled with practical visualization skills, provides a solid framework for embarking on a career as a Data Analyst.
Business Intelligence Developer
A Business Intelligence Developer specializes in transforming raw data into meaningful and actionable insights for businesses. They design and develop data warehouses, create reports, and build interactive dashboards to support decision-making. The DP-900 Azure Data Fundamentals course is particularly advantageous for individuals pursuing a career as a Business Intelligence Developer. It offers significant instruction on data visualization using Microsoft Power BI, including connecting to SQL databases, importing data, understanding data models, and utilizing appropriate visualizations. Furthermore, the course explores Azure Synapse Analytics, which is a key component for modern data warehousing, and covers concepts of SQL pool usage. The foundational understanding of relational data, SQL statements, and common data workloads like analytical workloads directly supports the development of robust BI solutions.
Data Warehouse Developer
A Data Warehouse Developer is responsible for designing, building, and maintaining an organization's data warehouse, which is a central repository of integrated data from one or more disparate sources. This involves ETL (Extract, Transform, Load) processes and schema design. The DP-900 Azure Data Fundamentals course is an excellent fit for a Data Warehouse Developer, as it covers many directly applicable technologies and concepts. You will gain experience with Azure Synapse Analytics, a powerful platform for data warehousing, and learn about setting up SQL DB and server for use with it. The course also covers Azure Data Factory for copying and ingesting data, a crucial ETL tool. Understanding relational data concepts, SQL statements, and various storage options provides a robust foundation for building and managing efficient data warehouses.
Data Migration Specialist
A Data Migration Specialist plans, executes, and verifies the transfer of data from one system to another, often from on-premises environments to cloud platforms. This role requires meticulous attention to detail and a deep understanding of source and target data systems. The DP-900 Azure Data Fundamentals course is highly beneficial for a Data Migration Specialist transitioning data to Azure. You will gain hands-on experience with various Azure data storage options, including relational databases (Azure SQL), non-relational databases (Azure Cosmos DB), and Azure storage accounts (Blob, File, Table storage). The course also covers data ingestion and processing with Azure Data Factory, a key tool for orchestrating data movement. This practical grounding in Azure's diverse data services makes the course an excellent foundation for effectively planning and executing data migrations.
Azure Administrator
An Azure Administrator is responsible for implementing, monitoring, and maintaining Microsoft Azure solutions, including managing compute, storage, networking, and security. The role focuses on the operational aspects of cloud services. This course is highly relevant for aspiring Azure Administrators, as it offers extensive hands-on experience with core Azure services. You will learn about understanding the Microsoft Environment, creating and managing Azure accounts, and activating Entra ID. Crucially, the course covers creating relational databases in Azure, managing Azure storage accounts, and securing them, along with permissions in Azure regarding data roles. This direct engagement with Azure's infrastructure components and security practices provides a fundamental skillset for effectively managing Azure resources as an Azure Administrator.
Cloud Engineer
A Cloud Engineer designs, implements, and manages cloud-based infrastructure and services, ensuring scalability, security, and efficiency. Their daily tasks often involve configuring virtual machines, managing storage, and deploying applications within cloud environments. The DP-900 Azure Data Fundamentals course provides a valuable introduction for someone aspiring to be a Cloud Engineer, especially within the Microsoft Azure ecosystem. It lays a solid foundation by covering the Microsoft Environment, Active Directory Domains, RAS, DMZ, Virtualization, and the Microsoft Cloud Services. You will gain practical experience creating a free Azure account, activating Entra ID, and working with Azure VMs, storage accounts, and various Azure data services. This comprehensive exposure to Azure's foundational components is directly relevant to establishing a strong career as a Cloud Engineer.
Cloud Support Engineer
A Cloud Support Engineer assists users and organizations with technical issues related to their cloud infrastructure and services. This involves troubleshooting, problem resolution, and providing guidance on cloud best practices and configurations. For an aspiring Cloud Support Engineer specializing in Azure, the DP-900 Azure Data Fundamentals course provides a helpful foundational understanding of the Azure data ecosystem. It covers essential topics such as understanding the Microsoft Environment, creating Azure accounts, managing Entra ID, and working with various Azure data services like SQL databases, Cosmos DB, and Azure storage accounts. The hands-on simulations of creating and connecting to these services will directly enhance one's ability to diagnose and resolve common issues, making them more effective in a support role. This practical familiarity with Azure data components is a significant advantage.
Data Architect
A Data Architect designs the vision and strategy for an organization's data infrastructure, defining how data is collected, stored, processed, and consumed. This role requires a broad understanding of various data technologies and their optimal application. The DP-900 Azure Data Fundamentals course may be useful for aspiring Data Architects, as it provides a comprehensive overview of fundamental data concepts and technologies within Azure. You will explore different ways to represent data, identify various options for data storage (relational, non-relational, Azure storage accounts), and understand common data workloads. The course also delves into large-scale analytics, including Azure Data Lake storage, Azure Databricks, and Azure Synapse Analytics. This broad exposure to Azure's data ecosystem helps build a foundational understanding of the components a Data Architect would leverage and design.
Solutions Architect
A Solutions Architect designs and oversees the implementation of complex technical solutions for businesses, ensuring they align with organizational goals and technical requirements. This often involves integrating various cloud services and platforms. The DP-900 Azure Data Fundamentals course may be useful for individuals targeting a Solutions Architect role, particularly one focused on data-centric solutions in Azure. It offers a foundational understanding of the Microsoft Cloud Services, Azure environment, and various data processing technologies. You will learn about relational and non-relational database services, Azure storage capabilities, and large-scale analytics components like Azure Synapse Analytics and Azure Data Factory. This breadth of exposure to Azure's data services and foundational cloud concepts helps in designing holistic and effective data solutions, which is a key responsibility for a Solutions Architect.
Technical Consultant
A Technical Consultant advises clients on technology solutions, helping them implement systems that meet their business needs. This often involves assessing client requirements, recommending appropriate cloud services, and assisting with deployment and integration. The DP-900 Azure Data Fundamentals course may be useful for someone pursuing a Technical Consultant role, especially if specializing in data and cloud solutions. It provides a solid understanding of the Microsoft Cloud Services and a wide array of Azure data processing technologies, including relational and non-relational databases, Azure storage, and large-scale analytics services like Azure Synapse Analytics. This breadth of knowledge, combined with hands-on experience, enables a Technical Consultant to confidently discuss, recommend, and demonstrate Azure data solutions to clients, establishing credibility and practical expertise.
DevOps Engineer
A DevOps Engineer works to bridge the gap between development and operations, focusing on automating and streamlining the software delivery lifecycle. This often involves managing cloud infrastructure, continuous integration, and continuous deployment pipelines. The DP-900 Azure Data Fundamentals course may be useful for an aspiring DevOps Engineer, particularly one working with Azure-based data solutions. While not a core DevOps course, it provides a crucial understanding of the Azure environment, cloud services, and data resources that a DevOps Engineer would need to provision, manage, and automate. Learning about creating Azure accounts, managing VMs, setting up Azure storage, and understanding permissions in Azure for data roles provides valuable context for automating infrastructure deployments and managing configurations for data-centric applications, forming a helpful baseline for success.

Reading list

We've selected 50 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in DP-900 Azure Data Fundamentals hands on course with sims.
Is widely considered the essential reference for understanding DAX, the formula language of Power BI. It provides a comprehensive deep dive into DAX concepts, evaluation contexts, and optimization techniques. While challenging, it's invaluable for anyone seeking to truly master Power BI's analytical capabilities and is often recommended for intermediate to advanced users and professionals.
Aligned directly with Microsoft's DP-420 certification, this comprehensive practitioner guide covers partition key design, Request Unit (RU/s) capacity planning, indexing policies, Change Feed event-driven processing, and multi-region replication in Azure Cosmos DB.
Provides a comprehensive overview of cloud computing, covering concepts, technologies, and architectures. It is written by leading experts in the field.
Introduces the fundamental principles of data science and data-analytic thinking from a business perspective. It helps readers understand how to extract valuable knowledge and business value from data, covering various data mining techniques without getting overly technical. Based on an MBA course, it uses real-world business problems to illustrate concepts, making it highly relevant for business-oriented individuals and professionals.
Provides the indispensable theoretical and architectural foundation for understanding Cosmos DB's five tunable consistency levels (Strong, Bounded Staleness, Session, Consistent Prefix, Eventual), quorum replication, and hash-based partitioning.
Focuses specifically on Power Query (M), the data transformation engine in Power BI. It's an excellent resource for users who need to connect to, clean, and shape data efficiently before analysis. It covers the M language in detail with practical examples, making it highly relevant for data preparation tasks.
Serves as a practical cookbook for solving common business problems using DAX. It provides a collection of reusable DAX patterns, making it an excellent companion to 'The Definitive Guide to DAX' for applying DAX in real-world scenarios.
A comprehensive guide to mastering the Power Query M language, this book is for users who need to perform complex data transformations. It delves into the intricacies of M code and provides practical examples for real-world problems.
Written by the same authors as 'The Definitive Guide to DAX', this book provides a strong foundation in data modeling and analysis using Power BI and Power Pivot. It's a great bridge for those transitioning from Excel and offers clear explanations of key concepts with practical examples.
Dissects how distributed storage engines implement consensus, leaderless and leader-based replication, anti-entropy, and inverted/Bw-tree indexing, giving senior engineers deep insight into how globally distributed databases guarantee low-latency SLA bounds.
The second edition of this book provides updated coverage on expert data modeling techniques in Power BI. It's a key resource for users looking to build optimized data models for complex reporting and business needs.
Written by the creator of the pandas library, this book practical, hands-on guide to data manipulation, cleaning, processing, and analysis using Python. It is an essential resource for anyone looking to use Python for data analytics, covering key libraries like pandas, NumPy, and Jupyter. It includes numerous real-world case studies and is widely used by students and professionals.
Focusing on the crucial aspect of communicating insights, this book teaches the fundamentals of data visualization and how to tell compelling stories with data. It provides practical guidance and real-world examples to help readers create effective visualizations and presentations. is highly recommended for anyone who needs to present data-driven findings clearly and persuasively, regardless of their technical background.
Essential for anyone looking to deepen their understanding of SQL performance and optimization. explains how databases execute queries and provides insights into writing efficient SQL code. It's highly recommended for developers and database administrators aiming to improve application performance.
Focuses on the practical application of Power Query for data collection, combination, and transformation in both Excel and Power BI. It's a valuable resource for anyone who spends significant time preparing data for analysis.
Introduces aggregate-oriented data modeling, polyglot persistence, and document, key-value, column-family, and graph paradigms, directly mapping to the multi-model APIs offered inside Azure Cosmos DB.
Provides a comprehensive overview of data storage systems, covering both the theoretical and practical aspects of the subject. It is suitable for both undergraduate and graduate students, as well as for professionals in the field.
Another strong resource for learning Power Query, this book by a well-known Power BI expert covers data transformation techniques in detail. It's suitable for users who want a thorough understanding of Power Query's capabilities.
Provides a broad, introductory overview of data analytics concepts, making it ideal for beginners across various disciplines. It covers key data concepts and includes real-world examples and case studies to solidify understanding. Many universities use this book as a textbook for introductory data analytics courses. It serves as excellent background reading for anyone new to the field.
Aimed at intermediate to advanced users, this book delves into expert techniques for creating impactful Power BI solutions. It covers various aspects of Power BI, including data modeling, visualization, and deployment, making it a valuable resource for professionals seeking to enhance their skills.
Situates Azure Cosmos DB alongside Azure Functions, Event Grid, Key Vault, and Azure AI services, showing developers how to integrate serverless NoSQL storage into modern cloud-native.NET and enterprise applications.
Focuses on the essential skill of data modeling within Power BI, covering concepts relevant to Power BI, Analysis Services tabular, and SQL databases. It's a valuable resource for understanding how to structure data for effective analysis.
Bridges event-driven compute and globally distributed storage by demonstrating Cosmos DB Change Feed triggers, Azure Functions bindings, and graph container patterns across C-sharp, TypeScript, and Python.
Dives into common mistakes and suboptimal solutions in database design and SQL coding, explaining how to identify and correct them. It's crucial for deepening understanding and writing more robust and maintainable SQL. It's a valuable resource for developers and database professionals seeking to improve their practices.
While focused on MySQL, this book provides in-depth coverage of database and SQL performance tuning that is applicable to other systems. It's essential for those working with large datasets and high-traffic applications. It's a comprehensive guide for optimizing SQL queries and database infrastructure.
Focuses on using SQL specifically for data analysis, covering techniques beyond basic querying to transform and gain insights from data. It's suitable for those who have a foundational understanding of SQL and want to apply it in a data analysis context. It's relevant for data scientists and analysts.
In the age of information overload, this book provides essential tools and frameworks for critically evaluating data, statistics, and claims presented as data-driven. It equips readers with the skills to identify misleading information and understand the potential for manipulation. This highly relevant book for navigating the contemporary data landscape.
Walks step by step through Cosmos DB's multi-model architecture, demonstrating SQL core queries, JavaScript stored procedures, triggers, user-defined functions, and global turnkey distribution across Azure regions.
Offers an accessible and engaging introduction to the fundamentals of statistics, a critical component of data analytics. It explains key statistical concepts using real-world examples and relatable anecdotes, making it an excellent resource for those without a strong mathematical background. It helps build a solid foundation in statistical thinking necessary for data analysis.
This guide provides a quick introduction to Power BI for beginners, covering essential topics like data modeling, visualization, and storytelling with data. It's a good resource for getting up to speed quickly with the core functionalities of Power BI.
Explains how operational NoSQL stores like Azure Cosmos DB integrate with analytical lakehouses and Microsoft Fabric via zero-ETL mirroring and Azure Synapse Link for real-time HTAP analytics.
While focused on T-SQL (for Microsoft SQL Server), this book provides a deep and rigorous understanding of SQL fundamentals that are applicable to many dialects. It's highly regarded for its clear explanations and challenging examples, making it excellent for solidifying core concepts. It's often used by professionals working with SQL Server.
Tailored for aspiring data scientists, this book focuses on the SQL skills needed for data analysis, including dataset construction and manipulation. It bridges the gap between basic SQL and its application in data science workflows. Relevant for those entering or working in the data science field.
Demonstrates practical C-sharp and.NET SDK application development with Azure Cosmos DB, covering document modeling, hierarchical partition keys, cross-partition query optimization, and throughput provisioning.
Offers an approachable and practical introduction to SQL, particularly for those interested in data analysis and storytelling. It uses PostgreSQL for examples but the concepts are widely applicable. It's great for beginners and those who want to apply SQL skills to real-world data tasks.
Serves as a practical guide for beginners to get started with self-service data analytics using Power BI Desktop and Excel. It covers the fundamental steps involved in the BI process using these tools.
This comprehensive reference guide covers a wide range of Power BI features, from installation and data modeling to dashboard creation and administration. It's a useful resource for gaining a broad understanding of the Power BI toolset.
Provides a theoretical foundation for cloud computing. It covers topics such as cloud architectures, cloud resource management, and cloud security.
Practical guide to cloud computing. It covers a wide range of topics, including cloud computing basics, cloud architectures, and cloud security.
Provides a hands-on approach to learning and practicing SQL through a variety of problems. It's an excellent supplement to theoretical learning and helps solidify understanding through practical application. Suitable for all levels looking to improve their problem-solving skills with SQL.
Surveys Azure's modern non-relational ecosystem for newcomers and DP-900 candidates, dedicating core chapters to Cosmos DB's multi-model APIs, consistency levels, partitioning, and global distribution.
Considered a classic in the field, this book provides a comprehensive and rigorous treatment of statistical learning methods. It covers a wide range of topics, including supervised and unsupervised learning, model selection, and a variety of algorithms. While mathematically more demanding, it is an invaluable reference for graduate students and researchers seeking a deep understanding of the theoretical underpinnings of many data analytics techniques.
A classic since its publication, this book remains highly relevant in highlighting how statistics can be manipulated or misinterpreted to present a misleading picture. It teaches readers to critically evaluate statistical claims and recognize common pitfalls. This valuable read for anyone who works with or consumes data and wants to avoid being misled.
Specifically aimed at Excel users transitioning to Power BI, this book leverages existing Excel knowledge to introduce Power Pivot, Power Query, and DAX. It's a helpful resource for those with a strong Excel background looking to expand their capabilities.
Compares document (MongoDB), wide-column (HBase/Cassandra), graph, and relational data models hands-on, equipping developers to choose the right API surface when provisioning an Azure Cosmos DB account.
Practical, hands-on introduction to creating interactive data visualizations for the web using JavaScript and the D3.js library. It is ideal for those who want to move beyond static visualizations and create dynamic, web-based data experiences. It requires some programming background but valuable resource for enhancing data communication skills.
Offers practical tips and techniques for writing more effective and efficient SQL code. It's a great resource for improving coding style and avoiding common pitfalls. Suitable for those with some SQL experience looking to refine their skills.
Offers a comprehensive introduction to forecasting methods, covering both theoretical principles and practical applications. It uses R to demonstrate various forecasting techniques and is suitable for students and practitioners in various fields. It's a key resource for anyone involved in time series analysis and forecasting as part of their data analytics work.

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