Data Engineer Training We offer proven Data Engineer Training regularly delivered to our worldwide Fortune 500 clients Watch our Data Engineering Training Video Data Engineering with Python Take Data Engineer Training with the Experts! Data engineer training with Web Age will teach you to organize, analyze and interpret your many sources of big data and information. The data engineer training courses we offer are comprehensive and provide your teams the skills they need to discover insights required for analyzing and tackling critical factors such as risk, performance, quality, forecasting, estimating, simulation, business process improvement, and much more.  Data Engineer Training Courses and Schedules * Click a course below to view the scheduled class dates Data Engineer Training Fundamentals Data Engineering Bootcamp Training A data engineer conceives, builds and maintains the data infrastructure that holds your enterprise’s advanced analytics capacities together. Learn about the world of data engineering. This five day Data Engineering Bootcamp training course is supplemented by hands-on labs that help attendees reinforce their theoretical knowledge of the learned material. View this Data Engineering Training Course outline and schedule Data Engineer Training with Python Data engineering is a software engineering practice with focus on design, development, and the productionizing of data processing systems. It includes all the practical aspects of data acquisition, transfer, transformation, and storage on-prem or in the cloud. This intensive hands-on training course teaches the students how to apply Python to the practical aspects of data engineering and introduces the students to the popular Python libraries used in the field, including NumPy, pandas, Matplotlib, scikit-learn, and Apache Spark. Data Engineer Training with Python – Course Outline Data Engineer Training for Managers Data Engineering for Managers Training. Duration: 1/2 Day View Data Engineer Training for Managers Course Outline and Scheduled Classes API Management Fundamentals for Architects Training API Management Fundamentals for Architects. Audience: Developers, Software Engineers, Data Scientists, and IT Architects Duration: Three days View This Data Engineering Course Outline and Scheduled Class Dates Data Engineering with PySpark Data Engineering with PySpark Audience: Data Warehouse and Data Lake Specialists, Software Developers Prerequisites: General background in programming and/or data processing; ability to learn a new language (Python) by doing stepwise exercises Duration: Three days Data Engineering With PySpark Complete Course Outline and Dates Azure Data Engineer Training Designing an Azure Data Solution In this Azure Data Engineer Training course, the students will design various data platform technologies into solutions that are in line with business and technical requirements. This can include on-premises, cloud, and hybrid data scenarios which incorporate relational, No-SQL or Data Warehouse data. They will also learn how to design process architectures using a range of technologies for both streaming and batch data. The students will also explore how to design data security including data access, data policies and standards. They will also design Azure data solutions which includes the optimization, availability and disaster recovery of big data, batch processing and streaming data solutions. View This Azure Data Engineer Training Course Outline Implementing an Azure Data Solution In this Azure Data Engineer Training course, the students will implement various data platform technologies into solutions that are in line with business and technical requirements including on-premises, cloud, and hybrid data scenarios incorporating both relational and No-SQL data. They will also learn how to process data using a range of technologies and languages for both streaming and batch data. The students will also explore how to implement data security including authentication, authorization, data policies and standards. They will also define and implement data solution monitoring for both the data storage and data processing activities. Finally, they will manage and troubleshoot Azure data solutions which includes the optimization and disaster recovery of big data, batch processing and streaming data solutions. Implementing an Azure Data Solutions – Course Outline and Schedule Migrate SQL and NoSQL Workloads to Azure  (Bundle) This Azure Data Engineer Training course provides the knowledge and skills to migrate SQL and NoSQL data workloads to Azure. The students will learn the objectives of data platform modernization and how it is suitable for given business requirements. They will also learn each stage of the data platform modernization process and define what tasks are involved at each stage, such as the assessment and planning phase. Students will also learn the available migration tools and how they are suitable for each stage of the data migration process. The student will learn how to migrate to the three target platforms for SQL based workloads; Azure Virtual Machines, Azure SQL Databases and Azure SQL Database Managed Instances . The student will learn the benefits and limitations of each target platform and how they can be used to fulfill both business and technical requirements for modern SQL workloads. The student will explore the changes that may need to be made to existing SQL based applications, so that they can make best use of modern data platforms in Azure. The students will also learn what is Cosmos DB and how you can migrate MongoDB and Cassandra workloads to Cosmos DB. VIew This Course Outline and Scheduled Course Dates Migrate Data Workloads to Azure  (Bundle) This Azure Data Engineering Training course provides the knowledge and skills to migrate SQL, NoSQL and Open Source data workloads to Azure. The students will learn the objectives of data platform modernization and how it is suitable for given business requirements. They will also learn each stage of the data platform modernization process and define what tasks are involved at each stage, such as the assessment and planning phase. Students will also learn the available migration tools and how they are suitable for each stage of the data migration process. The student will learn how to migrate to the three target platforms for SQL based workloads; Azure Virtual Machines, Azure SQL Databases and Azure SQL Database Managed Instances . The student will learn the benefits and limitations of each target platform and how they can be used to fulfil both business and technical requirements for modern SQL workloads. The student will explore the changes that may need to be made to existing SQL based applications, so that they can make best use of modern data platforms in Azure. The students will learn what is Cosmos DB and how you can migrate MongoDB and Cassandra workloads to Cosmos DB. The students will learn what is required to migrate MySQL and PostgreSQL workloads to Azure SQL Database. View Complete Course Outline Design Migrate Data Workloads to Azure (Bundle) This Azure Data Engineering Training course provides the knowledge and skills to compare and contrast various database options on Azure, identify data streaming options for large-scale data ingest, and identify longer-term data storage options. Students will gain the knowledge and skills needed to leverage Azure storage services and features in their development solutions. It covers Azure Table storage, Azure Cosmos DB, Azure Blob, and developing against relational databases in Azure. The students will learn what is Cosmos DB and how you can migrate MongoDB and Cassandra workloads to Cosmos DB. The students will learn what is required to migrate MySQL and PostgreSQL workloads to Azure SQL Database. View This Azure Data Engineer Training Course Outline and Scheduled Dates Design Develop and Migrate NoSQL Workloads to Azure (Bundle) This Azure Data Engineering Training course provides the knowledge and skills to compare and contrast various database options on Azure, identify data streaming options for large-scale data ingest, and identify longer-term data storage options. Students will gain the knowledge and skills needed to leverage Azure storage services and features in their development solutions. It covers Azure Table storage, Azure Cosmos DB, Azure Blob, and developing against relational databases in Azure. The students will learn what is Cosmos DB and how you can migrate MongoDB and Cassandra workloads to Cosmos DB. Complete Course Outline and Dates AWS Data Engineer Training AWS Data Engineering Training This AWS Data Engineering Training course discusses the approaches that can be taken with respect to ingesting, storing and processing big data in AWS. It takes a look at features and tools available for data scientists in AWS. You will learn how to ingest, store, process, visualize and programmatically address data on the AWS platform to help with day to day analytics tasks, short and long term projections and can help improve your business intelligence model. See the Complete AWS Data Engineering Course Outline and Schedule Cloud Data Engineer Training with NiFi on AWS or GCP This Cloud Data Engineer Training course is intended for students looking to learn data processing on the cloud with Apache NiFi – a visually programmed software tool that automates the movement and transformation of data between systems. Course material will cover data engineering theory and practical development advice. View Cloud Data Engineer Training with NiFi on AWS or GCP complete course outline NEW! Data Engineering Bootcamp Training (WA2926) Check out our 5 Day Data Engineering Bootcamp Training View Full Course Outline and Scheduled Course Dates Request Pricing For yourself or private, customized training for 3 or more people. We will not share your email. Read our privacy policy. Share PySpark for Data Engineering & Machine Learning In this data engineering training video we will review the core capabilities of PySpark as well as PySpark’s areas of specialization in data engineering, ETL, and Machine Learning use cases. Related courses: Practical Machine Learning with Apache Spark (WA2845) Data Engineering with Python Training (WA2905) Proven Results For over 20 years, we have trained thousands of developers at some of the country’s largest tech companies – including many Fortune 500 companies. Here are a few of the clients we have delivered Data Engineering Courses to:                Here are some reviews from past students who completed our Data Engineering Courses: “This was a great course. I loved the blend of Python Concepts Plus Just enough Data science to be productive” “Instructor was very thorough, yet practical. He was a great communicator and explained everything in layman’s terms.” “Great tutorials! I will go back to these” “This course is excellent. It gave me an overview of data science and a good understanding. It put me in the right direction of data analysis in my work.” Featured Data Engineer Training Blogs What is Data Engineering? Data engineering is a software engineering practice with a focus on design, development, and productionizing of data processing systems. Read More… Distributed Computing Concepts for Data Engineers We need a new approach — distributed computing where processing is done on clusters of computers. But there are challenges like… Read More Frequently Asked Data Engineer Training Questions What is a Data Engineer? A data engineer conceives, builds and maintains the data infrastructure that holds your enterprise’s advanced analytics capacities together. A data engineer is responsible for building and maintaining the data architecture of a data science project. Data Engineers are responsible for the creation and maintenance of analytics infrastructure that enables almost every other function in the data world. They are responsible for the development, construction, maintenance and testing of architectures, such as databases and large-scale processing systems. As part of this, Data Engineers are also responsible for the creation of data set processes used in modeling, mining, acquisition, and verification. Data Engineer Training was last modified: May 25th, 2020 by admin What is the Data Engineer Role? Data engineers are software engineers who have the primary focus on dealing with data engineering tasks They work closely with System Administrators, Data Analysis, and Data Scientists to prepare the data and make it consumable in subsequent advanced data processing scenarios Most of these activities fall under the category of ETL (Extract, Transform and Load) processes Practitioners in this field deal with such aspects of data processing as processing efficiency, scalable computation, system interoperability, and security Data engineers have knowledge of the appropriate data storage systems (RDBMS or NoSQL types) used by organizations they work for and their external interfaces Typically, data engineers have to understand the database and data schemas as well as the APIs to access the stored data  Depending on the task at hand, internal standards, etc., they may be required to use a variety of programming languages, including Java, Scala, Python, C#, C, etc Data Engineer Training was last modified: May 25th, 2020 by admin What is the difference between a Data Scientist and a Data Engineer? It is important to know the distinction between these 2 roles. While there is frequent collaboration between data scientists and data engineers, they’re different positions that prioritize different skill sets. Data scientists focus on advanced statistics and mathematical analysis of the data that’s generated and stored, all in the interest of identifying trends and solving business needs or industry questions. But they can’t do their job without a team of data engineers who have advanced programming skills (Java, Scala, Python) and an understanding of distributed systems and data pipelines. Broadly speaking, a data scientist builds models using a combination of statistics, mathematics, machine learning and domain based knowledge. He/she has to code and build these models using the same tools/languages and framework that the organization supports. A data engineer on the other hand has to build and maintain data structures and architectures for data ingestion, processing, and deployment for large-scale data-intensive applications. To build a pipeline for data collection and storage, to funnel the data to the data scientists, to put the model into production – these are just some of the tasks a data engineer has to perform. Data scientists and data engineers need to work together for any large scale data science project to succeed, Data Engineer Training was last modified: May 25th, 2020 by admin What are the different roles in Data Engineering? Data Engineer: A data engineer needs to have knowledge of database tools, languages like Python and Java, distributed systems like Hadoop, among other things. It’s a combination of tasks into one single role. Data Architect: A data architect lays down the foundation for data management systems to ingest, integrate and maintain all the data sources. This role requires knowledge of tools like SQL, XML, Hive, Pig, Spark, etc. Database Administrator: As the name suggests, a person working in this role requires extensive knowledge of databases. Responsibilities entail ensuring the databases are available to all the required users, is maintained properly and functions without any hiccups when new features are added. Data Engineer Training was last modified: May 25th, 2020 by admin What are the core Data Engineering skills? Introduction to Data Engineering (Related Course: Data Engineering Training for Managers) Basic Language Requirement: Python (Related Course: Introduction to Python Programming) Solid Knowledge of Operating Systems (Related Course: Unix Training) Heavy, In-Depth Database Knowledge – SQL and NoSQL (Related Course: NoSQL Training and Courseware) Data Warehousing – Hadoop, MapReduce, HIVE, PIG, Apache Spark, Kafka (Related Course: Big Data Training) Basic Machine Learning Familiarity (Related Course: AI and Machine Learning Training) Data Engineer Training was last modified: May 25th, 2020 by admin What is the future for Data Engineering? The data engineering field is expected to continue growing rapidly over the next several years, and there’s huge demand for data engineers across industries. The global Big Data and data engineering services market is expected to grow at a CAGR of 31.3 percent by 2025. Data Engineer Training was last modified: May 25th, 2020 by admin What is Data Wrangling (Munging)? Data wrangling (a.k.a. munging) is the process of organized data transformation from one data format (or structure) into another Normally, it is part of a data processing workflow the output of which is consumed downstream, normally, by systems with focus on data analytics / machine learning Usually, it is part of automated ETL (Extract, Transform, and Load) activities Specific activities include: Data cleansing, removing data outliers, repairing data (by plugging in some surrogate data in place of the missing values), data enhancement / augmenting, aggregation, sorting, filtering, and normalizing Data Engineer Training was last modified: May 25th, 2020 by admin Can I take Data Engineer Training online? Yes! We know your busy work schedule may prevent you from getting to one of our classrooms which is why we offer convenient Data Engineer training online to meet your needs wherever you want. We offer our Data Engineering courses as public Data Engineer training classes or dedicated Data Engineer training. Ask us about taking a Data Engineer training online course! Click here to see our Guaranteed to Run Virtual Online Class Schedules Data Engineer Training was last modified: May 25th, 2020 by admin Data Engineer Training was last modified: May 25th, 2020 by admin
Data Engineer Training We offer proven Data Engineer Training regularly delivered to our worldwide Fortune 500 clients Watch our Data Engineering Training Video Data Engineering with Python Take Data Engineer Training with the Experts! Data engineer training with Web Age will teach you to organize, analyze and interpret your many sources of big data and information. The data engineer training courses we offer are comprehensive and provide your teams the skills they need to discover insights required for analyzing and tackling critical factors such as risk, performance, quality, forecasting, estimating, simulation, business process improvement, and much more.  Data Engineer Training Courses and Schedules * Click a course below to view the scheduled class dates Data Engineer Training Fundamentals Data Engineering Bootcamp Training A data engineer conceives, builds and maintains the data infrastructure that holds your enterprise’s advanced analytics capacities together. Learn about the world of data engineering. This five day Data Engineering Bootcamp training course is supplemented by hands-on labs that help attendees reinforce their theoretical knowledge of the learned material. View this Data Engineering Training Course outline and schedule Data Engineer Training with Python Data engineering is a software engineering practice with focus on design, development, and the productionizing of data processing systems. It includes all the practical aspects of data acquisition, transfer, transformation, and storage on-prem or in the cloud. This intensive hands-on training course teaches the students how to apply Python to the practical aspects of data engineering and introduces the students to the popular Python libraries used in the field, including NumPy, pandas, Matplotlib, scikit-learn, and Apache Spark. Data Engineer Training with Python – Course Outline Data Engineer Training for Managers Data Engineering for Managers Training. Duration: 1/2 Day View Data Engineer Training for Managers Course Outline and Scheduled Classes API Management Fundamentals for Architects Training API Management Fundamentals for Architects. Audience: Developers, Software Engineers, Data Scientists, and IT Architects Duration: Three days View This Data Engineering Course Outline and Scheduled Class Dates Data Engineering with PySpark Data Engineering with PySpark Audience: Data Warehouse and Data Lake Specialists, Software Developers Prerequisites: General background in programming and/or data processing; ability to learn a new language (Python) by doing stepwise exercises Duration: Three days Data Engineering With PySpark Complete Course Outline and Dates Azure Data Engineer Training Designing an Azure Data Solution In this Azure Data Engineer Training course, the students will design various data platform technologies into solutions that are in line with business and technical requirements. This can include on-premises, cloud, and hybrid data scenarios which incorporate relational, No-SQL or Data Warehouse data. They will also learn how to design process architectures using a range of technologies for both streaming and batch data. The students will also explore how to design data security including data access, data policies and standards. They will also design Azure data solutions which includes the optimization, availability and disaster recovery of big data, batch processing and streaming data solutions. View This Azure Data Engineer Training Course Outline Implementing an Azure Data Solution In this Azure Data Engineer Training course, the students will implement various data platform technologies into solutions that are in line with business and technical requirements including on-premises, cloud, and hybrid data scenarios incorporating both relational and No-SQL data. They will also learn how to process data using a range of technologies and languages for both streaming and batch data. The students will also explore how to implement data security including authentication, authorization, data policies and standards. They will also define and implement data solution monitoring for both the data storage and data processing activities. Finally, they will manage and troubleshoot Azure data solutions which includes the optimization and disaster recovery of big data, batch processing and streaming data solutions. Implementing an Azure Data Solutions – Course Outline and Schedule Migrate SQL and NoSQL Workloads to Azure  (Bundle) This Azure Data Engineer Training course provides the knowledge and skills to migrate SQL and NoSQL data workloads to Azure. The students will learn the objectives of data platform modernization and how it is suitable for given business requirements. They will also learn each stage of the data platform modernization process and define what tasks are involved at each stage, such as the assessment and planning phase. Students will also learn the available migration tools and how they are suitable for each stage of the data migration process. The student will learn how to migrate to the three target platforms for SQL based workloads; Azure Virtual Machines, Azure SQL Databases and Azure SQL Database Managed Instances . The student will learn the benefits and limitations of each target platform and how they can be used to fulfill both business and technical requirements for modern SQL workloads. The student will explore the changes that may need to be made to existing SQL based applications, so that they can make best use of modern data platforms in Azure. The students will also learn what is Cosmos DB and how you can migrate MongoDB and Cassandra workloads to Cosmos DB. VIew This Course Outline and Scheduled Course Dates Migrate Data Workloads to Azure  (Bundle) This Azure Data Engineering Training course provides the knowledge and skills to migrate SQL, NoSQL and Open Source data workloads to Azure. The students will learn the objectives of data platform modernization and how it is suitable for given business requirements. They will also learn each stage of the data platform modernization process and define what tasks are involved at each stage, such as the assessment and planning phase. Students will also learn the available migration tools and how they are suitable for each stage of the data migration process. The student will learn how to migrate to the three target platforms for SQL based workloads; Azure Virtual Machines, Azure SQL Databases and Azure SQL Database Managed Instances . The student will learn the benefits and limitations of each target platform and how they can be used to fulfil both business and technical requirements for modern SQL workloads. The student will explore the changes that may need to be made to existing SQL based applications, so that they can make best use of modern data platforms in Azure. The students will learn what is Cosmos DB and how you can migrate MongoDB and Cassandra workloads to Cosmos DB. The students will learn what is required to migrate MySQL and PostgreSQL workloads to Azure SQL Database. View Complete Course Outline Design Migrate Data Workloads to Azure (Bundle) This Azure Data Engineering Training course provides the knowledge and skills to compare and contrast various database options on Azure, identify data streaming options for large-scale data ingest, and identify longer-term data storage options. Students will gain the knowledge and skills needed to leverage Azure storage services and features in their development solutions. It covers Azure Table storage, Azure Cosmos DB, Azure Blob, and developing against relational databases in Azure. The students will learn what is Cosmos DB and how you can migrate MongoDB and Cassandra workloads to Cosmos DB. The students will learn what is required to migrate MySQL and PostgreSQL workloads to Azure SQL Database. View This Azure Data Engineer Training Course Outline and Scheduled Dates Design Develop and Migrate NoSQL Workloads to Azure (Bundle) This Azure Data Engineering Training course provides the knowledge and skills to compare and contrast various database options on Azure, identify data streaming options for large-scale data ingest, and identify longer-term data storage options. Students will gain the knowledge and skills needed to leverage Azure storage services and features in their development solutions. It covers Azure Table storage, Azure Cosmos DB, Azure Blob, and developing against relational databases in Azure. The students will learn what is Cosmos DB and how you can migrate MongoDB and Cassandra workloads to Cosmos DB. Complete Course Outline and Dates AWS Data Engineer Training AWS Data Engineering Training This AWS Data Engineering Training course discusses the approaches that can be taken with respect to ingesting, storing and processing big data in AWS. It takes a look at features and tools available for data scientists in AWS. You will learn how to ingest, store, process, visualize and programmatically address data on the AWS platform to help with day to day analytics tasks, short and long term projections and can help improve your business intelligence model. See the Complete AWS Data Engineering Course Outline and Schedule Cloud Data Engineer Training with NiFi on AWS or GCP This Cloud Data Engineer Training course is intended for students looking to learn data processing on the cloud with Apache NiFi – a visually programmed software tool that automates the movement and transformation of data between systems. Course material will cover data engineering theory and practical development advice. View Cloud Data Engineer Training with NiFi on AWS or GCP complete course outline NEW! Data Engineering Bootcamp Training (WA2926) Check out our 5 Day Data Engineering Bootcamp Training View Full Course Outline and Scheduled Course Dates Request Pricing For yourself or private, customized training for 3 or more people. We will not share your email. Read our privacy policy. Share PySpark for Data Engineering & Machine Learning In this data engineering training video we will review the core capabilities of PySpark as well as PySpark’s areas of specialization in data engineering, ETL, and Machine Learning use cases. Related courses: Practical Machine Learning with Apache Spark (WA2845) Data Engineering with Python Training (WA2905) Proven Results For over 20 years, we have trained thousands of developers at some of the country’s largest tech companies – including many Fortune 500 companies. Here are a few of the clients we have delivered Data Engineering Courses to:                Here are some reviews from past students who completed our Data Engineering Courses: “This was a great course. I loved the blend of Python Concepts Plus Just enough Data science to be productive” “Instructor was very thorough, yet practical. He was a great communicator and explained everything in layman’s terms.” “Great tutorials! I will go back to these” “This course is excellent. It gave me an overview of data science and a good understanding. It put me in the right direction of data analysis in my work.” Featured Data Engineer Training Blogs What is Data Engineering? Data engineering is a software engineering practice with a focus on design, development, and productionizing of data processing systems. Read More… Distributed Computing Concepts for Data Engineers We need a new approach — distributed computing where processing is done on clusters of computers. But there are challenges like… Read More Frequently Asked Data Engineer Training Questions What is a Data Engineer? A data engineer conceives, builds and maintains the data infrastructure that holds your enterprise’s advanced analytics capacities together. A data engineer is responsible for building and maintaining the data architecture of a data science project. Data Engineers are responsible for the creation and maintenance of analytics infrastructure that enables almost every other function in the data world. They are responsible for the development, construction, maintenance and testing of architectures, such as databases and large-scale processing systems. As part of this, Data Engineers are also responsible for the creation of data set processes used in modeling, mining, acquisition, and verification. Data Engineer Training was last modified: May 25th, 2020 by admin What is the Data Engineer Role? Data engineers are software engineers who have the primary focus on dealing with data engineering tasks They work closely with System Administrators, Data Analysis, and Data Scientists to prepare the data and make it consumable in subsequent advanced data processing scenarios Most of these activities fall under the category of ETL (Extract, Transform and Load) processes Practitioners in this field deal with such aspects of data processing as processing efficiency, scalable computation, system interoperability, and security Data engineers have knowledge of the appropriate data storage systems (RDBMS or NoSQL types) used by organizations they work for and their external interfaces Typically, data engineers have to understand the database and data schemas as well as the APIs to access the stored data  Depending on the task at hand, internal standards, etc., they may be required to use a variety of programming languages, including Java, Scala, Python, C#, C, etc Data Engineer Training was last modified: May 25th, 2020 by admin What is the difference between a Data Scientist and a Data Engineer? It is important to know the distinction between these 2 roles. While there is frequent collaboration between data scientists and data engineers, they’re different positions that prioritize different skill sets. Data scientists focus on advanced statistics and mathematical analysis of the data that’s generated and stored, all in the interest of identifying trends and solving business needs or industry questions. But they can’t do their job without a team of data engineers who have advanced programming skills (Java, Scala, Python) and an understanding of distributed systems and data pipelines. Broadly speaking, a data scientist builds models using a combination of statistics, mathematics, machine learning and domain based knowledge. He/she has to code and build these models using the same tools/languages and framework that the organization supports. A data engineer on the other hand has to build and maintain data structures and architectures for data ingestion, processing, and deployment for large-scale data-intensive applications. To build a pipeline for data collection and storage, to funnel the data to the data scientists, to put the model into production – these are just some of the tasks a data engineer has to perform. Data scientists and data engineers need to work together for any large scale data science project to succeed, Data Engineer Training was last modified: May 25th, 2020 by admin What are the different roles in Data Engineering? Data Engineer: A data engineer needs to have knowledge of database tools, languages like Python and Java, distributed systems like Hadoop, among other things. It’s a combination of tasks into one single role. Data Architect: A data architect lays down the foundation for data management systems to ingest, integrate and maintain all the data sources. This role requires knowledge of tools like SQL, XML, Hive, Pig, Spark, etc. Database Administrator: As the name suggests, a person working in this role requires extensive knowledge of databases. Responsibilities entail ensuring the databases are available to all the required users, is maintained properly and functions without any hiccups when new features are added. Data Engineer Training was last modified: May 25th, 2020 by admin What are the core Data Engineering skills? Introduction to Data Engineering (Related Course: Data Engineering Training for Managers) Basic Language Requirement: Python (Related Course: Introduction to Python Programming) Solid Knowledge of Operating Systems (Related Course: Unix Training) Heavy, In-Depth Database Knowledge – SQL and NoSQL (Related Course: NoSQL Training and Courseware) Data Warehousing – Hadoop, MapReduce, HIVE, PIG, Apache Spark, Kafka (Related Course: Big Data Training) Basic Machine Learning Familiarity (Related Course: AI and Machine Learning Training) Data Engineer Training was last modified: May 25th, 2020 by admin What is the future for Data Engineering? The data engineering field is expected to continue growing rapidly over the next several years, and there’s huge demand for data engineers across industries. The global Big Data and data engineering services market is expected to grow at a CAGR of 31.3 percent by 2025. Data Engineer Training was last modified: May 25th, 2020 by admin What is Data Wrangling (Munging)? Data wrangling (a.k.a. munging) is the process of organized data transformation from one data format (or structure) into another Normally, it is part of a data processing workflow the output of which is consumed downstream, normally, by systems with focus on data analytics / machine learning Usually, it is part of automated ETL (Extract, Transform, and Load) activities Specific activities include: Data cleansing, removing data outliers, repairing data (by plugging in some surrogate data in place of the missing values), data enhancement / augmenting, aggregation, sorting, filtering, and normalizing Data Engineer Training was last modified: May 25th, 2020 by admin Can I take Data Engineer Training online? Yes! We know your busy work schedule may prevent you from getting to one of our classrooms which is why we offer convenient Data Engineer training online to meet your needs wherever you want. We offer our Data Engineering courses as public Data Engineer training classes or dedicated Data Engineer training. Ask us about taking a Data Engineer training online course! Click here to see our Guaranteed to Run Virtual Online Class Schedules Data Engineer Training was last modified: May 25th, 2020 by admin Data Engineer Training was last modified: May 25th, 2020 by admin
