Azure Data Engineering Training in Washington [DP-203]

Name: Microsoft Azure Data Engineering Training Course
Item: Microsoft Azure Data Engineering Training Course
Rating: 5
Author: Sujit Samal

Data Engineer Course in Washington?

Microsoft is recognized as a leader in the Gartner Magic Quadrant for Data Analytics and Business Intelligence Platforms for 12 consecutive years

According to Linkedin, Data Engineer Training in Washington is one of the fast growing jobs in technology with a growth rate of 40% year on year

Average salary for a Data Engineer is INR 10.5 Lakhs per year in India and in the United States, it is $114,835 per year in the United States - Indeed.com

Introduction to Microsoft Azure and its Services

Topics:

Azure Subscriptions
Azure Resources
Azure Free Tier Account
Azure Resource Manager
Azure Resource Manager Template
Azure Storage
Types of Azure Storage

Hands-On:

Create a free tier Azure account
Create a web app service using Azure Portal
Create and Deploy ARM templates
Manage Azure Storage account
Manage Azure Cost and Billing

Skills You will Learn:

Creating ARM templates
Accessing Azure Storage Service
Azure Cost and Billing Services

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Introduction To Azure Data Engineering

Topics:

Understand the evolving world of data
Data abundance
Understanding the Data Engineering Problem
Understand job responsibilities
Understanding Data Engineering Processing - Extract Transform and Load
Overview of Azure Data Engineering Services
Understand data storage in Azure Storage
Understand data storage in Azure Data Lake Storage
Understand Azure Cosmos DB
Understand Azure SQL Database
Understand Azure Synapse Analytics
Understand Azure Stream Analytics
Understand Azure HDInsight
Understand other Azure data services

Hands-On:

Navigating through Azure data engineering services

Skills You will Learn:

Analyzing Data Engineering Process
Understanding Azure Services

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Storing Data in Azure

Topics:

How to choose an Azure Storage Service in Azure
Create an Azure Storage Account
Connect an app to Azure Storage API
Connect to your Azure storage account
Explore Azure Storage security features
Understand storage account keys
Understand shared access signatures
Control network access to your storage account
Understand Advanced Threat Protection for Azure Storage
Explore Azure Data Lake Storage security features
Introduction to Blob storage
What are blobs?
Design a storage organization strategy

Hands-On:

Add the storage client library to your app
Add Azure Storage configuration to your app
Connect your application to your Azure Storage account
Create Azure storage resources
Configure and initialize the client library
Get blob references
Blob uploads and downloads

Skills You will Learn:

Working with Azure Storage
Configuring Security in Azure Storage
Storing blob data in Azure Storage

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Azure Data Factory - I

Topics:

Integrate data with Azure Data Factory or Azure Synapse Pipeline
Understand Azure Data Factory
Describe data integration patterns
Explain the data factory process
Understand Azure Data Factory components
Azure Data Factory security
Set-up Azure Data Factory
Create linked services
Create datasets
Create data factory activities and pipelines
Manage integration runtimes
Petabyte-scale ingestion with Azure Data Factory or Azure Synapse Pipeline
List the data factory ingestion methods
Describe data factory connectors
Understand data ingestion security considerations

Hands-On:

Use the data factory copy activity
Manage the self hosted integration runtime
Setup the Azure integration runtime

Skills You will Learn:

Working with Azure Data Factory
Integrating Azure Data Factory
Azure Data Factory security
Implementing Data Factory connectors

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Azure Data Factory - II

Topics:

Explain Data Factory transformation methods
Describe Data Factory transformation types
Debug mapping data flow
Describe slowly changing dimensions
Choose between slowly changing dimension types
Understand data factory control flow
Work with data factory pipelines
Debug data factory pipelines
Add parameters to data factory components
Execute data factory packages
Describe SQL Server Integration Services
Understand the Azure-SIS integration runtime
Set-up Azure-SIS integration runtime
Run SSIS packages in Azure Data Factory
Migrate SSIS packages to Azure Data Factory
Configure a git repository with a development factory
Create and merge a feature branch
Deploy a release pipeline
Visually monitor pipeline runs
Integrate with Azure Monitor
Set up alerts
Rerun pipeline runs

Hands-On:

Author an Azure Data Factory mapping data flow
Use Data Factory wrangling data
Use compute transformations within Data Factory
Integrate SQL Server Integration Services packages within Data Factory
Design and implement a Type 1 slowly changing dimension with mapping data flows
Integrate a Notebook within Azure Synapse Pipelines

Skills You will Learn:

Implementing Data Factory transformations
Implementing slowly changing dimensions
Working with SQL server integration
Configuring a git repository
Integrating Azure monitor and set up alerts

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Azure Synapse Analytics - I

Topics:

What is Azure Synapse Analytics
How Azure Synapse Analytics works
When to use Azure Synapse Analytics
Create Azure Synapse Analytics workspace
Describe Azure Synapse Analytics SQL
Explain Apache Spark in Azure Synapse Analytics
Orchestrate data integration with Azure Synapse pipelines
Visualize your analytics with Power BI
Understand hybrid transactional analytical processing with Azure Synapse Link
Use Azure Synapse Studio

Hands-On:

Explore Azure Synapse Analytics
Create pools in Azure Synapse Analytics
Identifying Azure Synapse pipeline components

Skills You will Learn:

Working with Azure Synapse Analytics
Managing Azure Synapse Analytics workspace
Querying data and Visualizing analytics
Working with Azure Synapse pipeline components

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Azure Synapse Analytics - II

Topics:

Understand the Azure Synapse Analytical processes
Explore the Data hub
Explore the Develop hub
Explore the Integrate hub
Explore the Monitor hub
Explore the Manage hub

Hands-On:

Create a new data flow or dataset, and manage the file
Use the Monitor hub to view pipeline and trigger runs, view the status of the various integration runtimes

Skills You will Learn:

Designing the new data flow or dataset.
Working with various types of hubs

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Data Warehouses using Azure Synapse Analytics - I

Topics:

Describe a modern data warehouse
Define a modern data warehouse architecture
Exercise - Identify modern data warehouse architecture components
Design ingestion patterns for a modern data warehouse
Understand data storage for a modern data warehouse
Understand file formats and structure for a modern data warehouse
Prepare and transform data with Azure Synapse Analytics

Hands-On:

Serve data for analysis with Azure Synapse Analytics
Design a data warehouse schema
Create data warehouse tables
Load data warehouse tables
Query a data warehouse

Skills You will Learn:

Designing a Modern Data Warehouse Architecture
Building a Data Warehouse
Working with different file formats
Preparing and transforming data

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Data Warehouses using Azure Synapse Analytics - II

Topics:

Understand data load design goals
Explain load methods into Azure Synapse Analytics
Manage source data files
Manage singleton updates
Set-up dedicated data load accounts
Implement workload management
Simplify ingestion with the Copy Activity
Understand performance issues related to tables

Hands-On:

Data Loading in Azure Synapse Analytics
Data Ingestion using Copy Activity
Implement workload management
Understand performance issues related to tables

Skills You will Learn:

Loading data using Azure Synapse Analytics
Implementing workload management

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Optimizing Data Queries in Azure

Topics:

Understand table distribution design
Use indexes to improve query performance
Understand query plans
Create statistics to improve query performance
Improve query performance with materialized views
Use read committed snapshot for data consistency
How does statistics affect a query plan?
Describe the integration methods between SQL and spark pools in Azure Synapse Analytics
Understand the use-cases for SQL and spark pools integration
Exercise: Integrate SQL and spark pools in Azure Synapse Analytics
Externalize the use of spark pools within Azure Synapse Workspace
Transfer data outside the synapse workspace using the PySpark connector
Explore the development tools for Azure Synapse Analytics
Understand transact-SQL language capabilities for Azure Synapse Analytics

Hands-On:

Use table distribution and indexes to improve performance
Optimize common queries with result-set caching
Work with windowing functions
Work with approximate execution
Work with JSON data in SQL pools
Encapsulate transact-SQL logic with stored procedures
Authenticate in Azure Synapse Analytics
Transfer data between SQL and spark pool in Azure Synapse Analytics
Authenticate between spark and SQL pool in Azure Synapse Analytics

Skills You will Learn:

Optimizing data queries in Azure
Authenticating in Azure Synapse Analytics
Working with SQL and Spark pool

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Managing Workloads in Azure Synapse Analytics

Topics:

Scale compute resources in Azure Synapse Analytics
Pause compute in Azure Synapse Analytics
Manage workloads in Azure Synapse Analytics
Use Azure Advisor to review recommendations
Use dynamic management views to identify and troubleshoot query performance
Understand skewed data and space usage
Understand network security options for Azure Synapse Analytics
Configure Conditional Access
Configure authentication
Manage authorization through column and row level security
Manage sensitive data with Dynamic Data Masking
Implement encryption in Azure Synapse Analytics

Hands-On:

Manage authorization through column and row level security

Skills You will Learn:

Managing workloads in Azure Synapse Analytics
Authentication and authorization in Azure Synapse Analytics
Implementing encryption in Azure Synapse Analytics

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Deep Dive into Azure Databricks

Topics:

Get started with Azure Databricks
Identify Azure Databricks workloads
Understand key concepts
Use Apache Spark in Azure Databricks
Create a Spark cluster
Use Spark in notebooks
Use Spark to work with data files
Visualize data
Get Started with Delta Lake
Create Delta Lake tables
Create and query catalog tables
Use Delta Lake for streaming data
Get started with SQL Warehouses
Create databases and tables
Create queries and dashboards
Understand Azure Databricks notebooks and pipelines
Create a linked service for Azure Databricks
Use a Notebook activity in a pipeline
Use parameters in a notebook

Hands-On:

Explore Azure Databricks
Run an Azure Databricks Notebook with Azure Data Factory
Use a SQL Warehouse in Azure Databricks
Use Delta Lake in Azure Databricks
Use Spark in Azure Databricks

Skills You will Learn:

Working with Azure Databricks
Running interactive and scheduled data analysis workloads

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Capstone Project

Topics:

In these project, you will design a secure, analytical, data ingestion, scalable, build and deploy data pipeline solution which you have learned as a part of this certification course.
Documentation and presentation: Develop detailed documentation outlining the design and implementation of the Azure data solution, and effectively present the solution and its outcomes to business.
Design and implement an Azure Data Solution

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Integrating Azure Data Solutions with Other Services (Self-Paced)

Topics:

Integrating Azure Data Solutions with Azure Synapse Analytics
Integrating Azure Data Solutions with Power BI
Integrating Azure Data Solutions with Azure Logic Apps
Best Practices for Integrating Azure Data Solutions with Other Services

Hands-On:

Working with the Azure Data Solutions with Azure Synapse Analytics
Build and deploy Azure Data Solutions with Power BI

Skills You will Learn:

Using Azure Data Solutions with Power BI
Designing the Azure Data Solutions
Best practices for integrating Azure Data Solutions

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Security and Compliance (Self-Paced)

Topics:

Overview of Azure Security Features
Implementing Security for Azure Data Storage Solutions
Implementing Security for Azure Data Processing Solutions
Best Practices for Securing Data Solutions in Azure

Hands-On:

To demonstrate the practical implementation of security and compliance measures in Azure data engineering to safeguard the organization's data.
To demonstrate the practical implementation of compliance measures in Azure data engineering to ensure adherence to regulatory requirements.

Skills You will Learn:

Securing the Azure Data Storage Solutions
Implementing Security for Data Processing Solutions

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Monitoring and Optimizing Data Solutions (Self-Paced)

Topics:

Monitoring and Alerting Strategies for Azure Data Solutions
Optimizing Data Processing Solutions for Performance and Cost
Using Azure Monitor to Monitor Data Solutions
Best Practices for Monitoring and Optimizing Azure Data Solutions

Hands-On:

To demonstrate the practical implementation of monitoring measures in Azure data engineering solutions to ensure efficient system operation.
Implementation of optimization measures in Azure data engineering solutions to ensure better system performance, reduce costs, and increase productivity.

Skills You will Learn:

Enhancing Data for Performance and Cost
Setting up the Azure Monitor

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Industrial Case Studies (Self-Paced)

Topics:

Case Studies on Implementing Azure Data Solutions
Emerging Trends and Technologies in Azure Data Engineering
Best Practices for Keeping Up with Industry Trends in Azure Data Engineering

Use Cases:

Case Studies on Mitsubishi Heavy Industries (MHI) Group
Case Studies on Bayer AG
Case Studies on fischer
Case Studies on New York City Department of Education
Case Studies on Amadeus

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Scenario Based Exam Dumps

Topics:

Scenario Based Dumps Set -1,2,3,4,5,6,7

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Certification: Practice Exam

Topics:

Practise Exam Set 1,2,3
3 practise exams with a minimum passing score of 700 will allow you to gauge your level of preparation.

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Azure Data Engineering Interview Preparation

Topics:

Interview preparation material to assist you in getting ready for the upcoming interviews

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Reference Material

Topics:

Whitepapers
Reference Documents

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Bonus Content

Topics:

Additional Resources (Part 1)
Additional Resources (Part 2)

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Testimonial Reviews

Sujit SamalTechnical Lead, Wipro

I have been an Edureka!'s happy customer since 2013. I am a customer of Edureka enrolled for Big dat ... Read More

Rajendran GunasekarOffshore Delivery Manager at CSC, Chennai, India

Knowledgeable Presenters, Professional Materials, Excellent Customer Support what else can a person ... Read More

Vijay MajetiFunctional Data Analyst at Yorkshire Building Society Group

Very good learning experience. Training staff are really experienced. 24X7 Support is excellent,get ... Read More

GopinathSAP Architect Consultant, IBM India Pvt Ltd, Bengaluru, Karnataka, India

I attended the demo session without any intention of joining a course. But the demo class was so imp ... Read More

Janardhan SingamaneniPrincipal Data Engineer at Staples

I took kafka and datascience classes with EDUREKA and its overall nice. After thorough scanning of a ... Read More

AalapIntegrations, Developer Support, Engineering

Clean, simple and a fantastic learning resource. The courses are a great resource for personal devel ... Read More

Which companies hire Azure Data Engineer in Washington?

Companies hiring Azure Data Engineers in Washington:

Microsoft Corporation
Amazon Web Services (AWS)
T-Mobile
Boeing
Starbucks
Expedia Group
Nordstrom
REI (Recreational Equipment Inc.)
Tableau Software
Zillow Group

Who is an Microsoft Azure Data Engineer Certification?

Microsoft Azure Data Engineer Certification assist users in understanding the data through exploratory research. They design and maintain safe and legally compliant data processes employing various tools and methods. They employ a variety of Azure language and data service options to create and store data that is cleansed and improved to be analyzed. Azure Data Engineer Training Online help ensure data pipelines and data stores run at a high level and are efficient, organized, reliable, and reliable for business requirements and limitations. They address unexpected problems rapidly and reduce the loss of data. They also create, set up, monitor, analyze, and optimize data platforms to meet the requirements of the data pipeline.

What career options can I look forward to with my Data Engineering skills?

The skills of a Azure Data engineer Training in Washington are highly sought-after at present. You could be qualified for jobs such as data engineer or data warehouse manager, database administrator and business intelligence analyst, and even data architect. Start the beginning step of registering for the Azure Data engineer Training in Washington.

What is the minimum education requirement to become a Data Engineer?

There isn't a specific college degree required to become a Data Engineer. People in this field typically hold a bachelor's or master's degree in physics, computer science, applied math, statistics, or other related fields. Even if you don't possess the educational qualifications, this Azure Data engineer Training in Washington will help you start your career.

How much is the average Azure Data Engineer Certification in Washington Cost?

Data engineers are paid an average salary that is more than 830k annually for India and $116K for those in the U.S. With the addition of relevant experience and getting an industry-respected certification, such as Edureka's Azure Data engineer Training in Washington, there is no reason to believe that you won't make more money.

Is the Data Engineering course hard to master?

The difficulty level in the Microsoft Data Engineer Certification in Washington depends entirely on the individual's prior experience and commitment to learning the concepts. Our highly trained instructors explain everything in a way that is easy to comprehend. They are also aware of the students' requirements.

Does Data Engineering require coding?

Although not necessary, it is highly recommended that you have a basic understanding of programming before pursuing a job in Data Engineering.

What are the Azure Data Engineer job opportunities in Washington?

Azure Data Engineer job opportunities in Washington:

Azure Data Engineer
Data Engineer (Azure)
Big Data Engineer (Azure)
Cloud Data Engineer (Azure)
Data Platform Engineer (Azure)
Data Warehouse Engineer (Azure)
ETL Developer (Azure)
Business Intelligence Engineer (Azure)
Data Integration Engineer (Azure)
Data Analytics Engineer (Azure)

Which is the best language to use for Data Engineering?

Java, Python, R, SQL, and Scala are the most widely utilized languages in the area of Data Engineering

What are the criteria for admission to be a candidate for this Data Engineer Course in Washington?

There is no requirement for eligibility to enroll in ourData Engineer Certification in Washington. Anyone interested in learning about the art of data engineering using Azure can join our extensive program and begin their journey. But, having a basic understanding of data structures and algorithms, SQL, Programming knowledge of Python and Java Cloud platforms, distributed systems, and Data pipelines are helpful.

What are the most important skills you require to be a Data Engineer?

To become a data engineer, individuals must be proficient in programming languages such as Java, Python, or C++. They must be proficient in relational databases like MySQL and Oracle Database and writing SQL queries. Creating a data warehouse operating system, operating systems Apache Spark, data mining, and data modeling are the other crucial skills for an engineer in data. This Data Engineer Certification in Washington will assist you in developing these abilities.

What is the Average Payscale of a Azure Data Engineer professionals in Washington?

The average annual salary of an Azure Data Engineer professional in Washington ranges from $90,000 to $140,000. However, the actual salary can vary based on factors such as experience, skills, qualifications, and the employing organization.

Is it possible for a fresh graduate to find job opportunities after completing the Data Engineer course?

Anyone who wants to begin the journey to a career in Data Engineering can enroll in this Data Engineer Certification in Washington. Suppose you understand Algorithms and data structure, SQL, Programming knowledge of Python and Java, Cloud platforms and distributed systems, and data pipelines. In that case, it will be much simpler for you to take our course.

How long will it take to become a Data Engineer?

Attending the Data Engineer Course in Washington, which may last anywhere from three to twelve months, can help you become a data engineer. The course curriculum, on the other hand, varies based on the degree or certification desired. 3-month courses can provide important Data Engineer experience and internship possibilities, leading to entry-level positions at top businesses.

Why should I take Microsoft Azure Data Engineer Course in Washington?

The Data Engineering Course is the one to take if you want to work with businesses because it certifies you as an expert in data science. After finishing our comprehensive program, you'll have the skills you need to succeed as a data engineer and a job-ready portfolio to show off during the interview process.

What is the Azure Data Engineer market trend in Washington?

Increasing demand: The demand for Azure Data Engineers in Washington is growing as more organizations adopt Microsoft Azure for their cloud data solutions. Various industries such as technology, healthcare, finance, retail, and government sectors actively seek Azure Data Engineer professionals.
Cloud-based data solutions: With the rapid adoption of cloud computing, there is a strong need for Azure Data Engineers who can design, build, and manage data solutions on the Azure platform, including data lakes, data warehouses, and data pipelines.
Big data and analytics: Azure Data Engineers with expertise in big data technologies such as Apache Spark, Hadoop, and Azure HDInsight are highly sought after as organizations strive to leverage big data and analytics for business insights and decision-making.
Data integration and ETL: Azure Data Engineers proficient in data integration and ETL (Extract, Transform, Load) processes using tools like Azure Data Factory and Azure Databricks have excellent job prospects in Washington.
Data governance and security: With increasing concerns about data privacy and security, Azure Data Engineers who can implement data governance frameworks, ensure compliance, and establish robust security measures are valued in the market.
AI and machine learning: Azure offers a comprehensive suite of AI and machine learning services, and Azure Data Engineers who can utilize these technologies to build intelligent data solutions are in demand in Washington.
Continuous learning and certification: Azure Data Engineers in Washington should stay updated with the latest advancements in Azure services, pursue relevant certifications, and engage in continuous learning to remain competitive in the job market.

To thrive as an Azure Data Engineer in Washington, individuals should have a strong understanding of data engineering concepts, hands-on experience with Azure services, and an ability to adapt to the evolving data landscape and emerging technologies.

What is the DP 203 Certification?

This exam evaluates your capability to perform technical functions. Design and implement storage for data; design and create data processing; develop and establish data security and monitoring and optimize data storage and processing storage.

What is the average salary of Microsoft Data Engineer Certification across the countries?

Data engineers are among the most sought-after professions today and earn high salaries globally. The possession of certification will increase their earnings potential.

Mentioned below are the average annual salaries of Azure Data Engineers in popular countries, as per Payscale data:

India - INR 795,486
The UK - £43,401
Canada - CA $81,288
The US - $94,358

Is Azure Data Engineer Certification in Washington worth it?

Yes, the Azure Data Engineer certification is an excellent way to demonstrate your skills in data engineering. The Data Engineer certification will increase the number of job opportunities, boost employees' pay, and increase career prospects over the long term.

Azure certificate expands job opportunities.
Azure data engineer certification makes you more competitive.
Azure Data Engineer Course provides better salaries.
Azure certification helps you prepare to advance in your career.

How do I become an Azure data engineer?

The Azure DP 203 certification exam is for candidates working in the Data engineer role on Microsoft Azure. To be a Microsoft Certified Azure Data Engineer, you must be proficient in data computation languages such as SQL, Python, or Scala and parallel processing, as well as data architecture concepts.

Which certificate is best for Azure Data Engineering Course?

The following certifications are best suited for Data Engineers:

Google Professional Data Engineer
Cloudera Certified Professional (CCP) Data Engineer
Microsoft Certified: Azure Data Engineering Course
Arcitura Certified Big Data Architect
Amazon Web Services (AWS) Certified Data Analytics – Specialty
Cloudera Data Platform Generalist Certification
Data Science Council of America (DASCA) Associate Big Data Engineer
Data Science Council of America (DASCA) Senior Big Data Engineer
IBM Certified Solution Architect – Cloud Pak for Data v4.x
IBM Certified Solution Architect – Data Warehouse V1
SAS Certified Big Data Professional

Is Azure Data Engineering Training a good career?

As long as there's data to process, Data Engineers will always be sought-after. Dice Insights reported in 2019 that data engineering was the most sought-after job in the tech sector, beating computer scientists, web developers, and database designers. The field of data engineering can be rewarding as well as difficult. You'll contribute to an organization's success by facilitating access to information that analysts, data scientists, and decision-makers require to fulfill their tasks. You'll depend on your knowledge of programming and problem-solving to develop efficient solutions.

What is the future of Azure data Engineering Training?

Data engineers can quickly complete large tasks due to the computing power in BigQuery, Snowflake, Firebolt, Databricks, and other cloud warehousing solutions. This shift from open-source and on-prem solutions to cloud and managed SaaS allows engineers to focus on tasks unrelated to managing databases. Since data engineers are not responsible for managing storage and computing, their role has changed in the direction of the infrastructure development to more performance-focused elements in the information stack or even more specialized functions.

Which is better, a Data Engineer or Data Scientist?

Simply said, a data scientist can interpret data only after having received the data in the correct format. The role of the Data Engineer is to deliver the data to the hands of an expert in data science. Today, a Data Engineer is more popular than a Data Scientist because tools cannot perform the Data Engineer's duties. However, a Data Engineer can earn as much as $90,8390 per year, whereas an individual who is a data scientist earns $91,470 per year. If you compare these numbers of the Data Engineer and the Data Scientist, you may not notice a significant distinction initially. If you look more deeply into numbers, the data scientist can earn between 20 and 30% more than the average Data Engineer.

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Azure Data Engineering Training in Washington

Data Engineer Course in Washington?

Instructor-led Microsoft Azure Data Engineering Training Course live online classes

Financing Options

Azure Data Engineer Course in Washington Curriculum

Introduction to Microsoft Azure and its Services

Introduction To Azure Data Engineering

Storing Data in Azure

Azure Data Factory - I

Azure Data Factory - II

Azure Synapse Analytics - I

Azure Synapse Analytics - II

Data Warehouses using Azure Synapse Analytics - I

Data Warehouses using Azure Synapse Analytics - II

Optimizing Data Queries in Azure

Managing Workloads in Azure Synapse Analytics

Deep Dive into Azure Databricks

Capstone Project

Integrating Azure Data Solutions with Other Services (Self-Paced)

Security and Compliance (Self-Paced)

Monitoring and Optimizing Data Solutions (Self-Paced)

Industrial Case Studies (Self-Paced)

Scenario Based Exam Dumps

Certification: Practice Exam

Azure Data Engineering Interview Preparation

Reference Material

Bonus Content

Azure Data Engineer Course in Washington Description

Who is an Azure Data Engineer?

What are the prerequisites for Data Engineer Training in Washington?

What are the Azure Data Engineer Skills?

Who should go for this Azure Data Engineering Training?

Testimonial Reviews

Video Reviews

Microsoft Azure Data Engineer Course in Washington FAQs

Which companies hire Azure Data Engineer in Washington?

Who is an Microsoft Azure Data Engineer Certification?

What career options can I look forward to with my Data Engineering skills?

What is the minimum education requirement to become a Data Engineer?

How much is the average Azure Data Engineer Certification in Washington Cost?

Is the Data Engineering course hard to master?

Does Data Engineering require coding?

What are the Azure Data Engineer job opportunities in Washington?

Which is the best language to use for Data Engineering?

What are the criteria for admission to be a candidate for this Data Engineer Course in Washington?

What are the most important skills you require to be a Data Engineer?

What is the Average Payscale of a Azure Data Engineer professionals in Washington?

Is it possible for a fresh graduate to find job opportunities after completing the Data Engineer course?

How long will it take to become a Data Engineer?

Why should I take Microsoft Azure Data Engineer Course in Washington?

What is the Azure Data Engineer market trend in Washington?

What is the DP 203 Certification?

What is the average salary of Microsoft Data Engineer Certification across the countries?

Is Azure Data Engineer Certification in Washington worth it?

How do I become an Azure data engineer?

Which certificate is best for Azure Data Engineering Course?

Is Azure Data Engineering Training a good career?

What is the future of Azure data Engineering Training?

Which is better, a Data Engineer or Data Scientist?

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