CERTIFIED DATA ENGINEER CERTIFICATION AUTHORITIES

COURSE FEATURES

DATA ENGINEER LEAD MENTORS

DATA ENGINEER COURSE FEES IN ROURKELA

Live Virtual

Instructor Led Live Online

110,000
63,945

  • IABAC® & JAINx® Certification
  • 6-Month | 150+ Learning Hours
  • 50+Hour Live Online Training
  • 10 Capstone & 1 Client Project
  • 365 Days Flexi Pass + Cloud Lab
  • Internship + Job Assistance

Blended Learning

Self Learning + Live Mentoring

55,000
36,645

  • IABAC® & JAINx® Certification
  • One year access to Self Learning
  • 10 Capstone Projects
  • 365 Days Flexi Pass + Cloud Lab
  • Internship + Job Assistance

Classroom

In - Person Classroom Training

110,000
69,195

  • IABAC® & JAINx® Certification
  • 6-Month | 150+ Learning Hours
  • 50+Hour Classroom Training
  • 10 Capstone & 1 Client Project
  • Cloud Lab Access
  • Internship + Job Assistance

ARE YOU LOOKING TO UPSKILL YOUR TEAM ?

Enquire Now

UPCOMING DATA ENGINEER ONLINE CLASSES IN ROURKELA

BEST CERTIFIED DATA ENGINEER CERTIFICATIONS

The entire training includes real-world projects and highly valuable case studies.

IABAC® certification provides global recognition of the relevant skills, thereby opening opportunities across the world.

images not display images not display

WHY DATAMITES INSTITUTE FOR DATA ENGINEER COURSE

Why DataMites Infographic

SYLLABUS OF DATA ENGINEER CERTIFICATION IN ROURKELA

MODULE 1: DATA ENGINEERING INTRODUCTION

• What is Data Engineering?
• Data Engineering scope
• Data Ecosystem, Tools and platforms
• Core concepts of Data engineering

MODULE 2: DATA SOURCES AND DATA IMPORT

• Types of data sources
• Databases: SQL and Document DBs
• Connecting to various data sources
• Importing data with SQL
• Managing Big data

MODULE 3: DATA PROCESSING

• Python NumPy Package Introduction
• Array data structure, Operations
• Python Pandas package introduction
• Data wrangling with Pandas
• Managing large data sets with Pandas
• Data structures: Series and DataFrame
• Importing data into Pandas DataFrame
• Data processing with Pandas

MODULE 4: DATA ENGINEERING PROJECT

• Setting Project Environment
• Data Ingestion through Pandas methods
• Hands-on: Ingestion, Transform Data and Load data

MODULE 1: PYTHON BASICS

• Introduction of python
• Installation of Python and IDE
• Python objects
• Python basic data types
• Number & Booleans, strings
• Arithmetic Operators
• Comparison Operators
• Assignment Operators
• Operator’s precedence and associativity

MODULE 2: PYTHON CONTROL STATEMENTS

• IF Conditional statement
• IF-ELSE
• NESTED IF
• Python Loops basics
• WHILE Statement
• FOR statements
• BREAK and CONTINUE statements

MODULE 3: PYTHON DATA STRUCTURES

• Basic data structure in python
• String object basics and inbuilt methods
• List: Object, methods, comprehensions
• Tuple: Object, methods, comprehensions
• Sets: Object, methods, comprehensions
• Dictionary: Object, methods, comprehensions

MODULE 4: PYTHON FUNCTIONS

• Functions basics
• Function Parameter passing
• Iterators
• Generator functions
• Lambda functions
• Map, reduce, filter functions

MODULE 5: PYTHON NUMPY PACKAGE

• NumPy Introduction
• Array – Data Structure
• Core Numpy functions
• Matrix Operations

MODULE 6: PYTHON PANDAS PACKAGE

• Pandas functions
• Data Frame and Series – Data Structure
• Data munging with Pandas
• Imputation and outlier analysis

MODULE 1 : OVERVIEW OF STATISTICS 

  • Descriptive And Inferential Statistics
  • Basic Terms Of Statistics
  • Types Of Data

MODULE 2 : HARNESSING DATA 

  • Random Sampling
  • Sampling With Replacement And Without Replacement
  • Cochran's  Minimum Sample Size
  • Simple Random Sampling
  • Stratified Random Sampling
  • Cluster Random Sampling
  • Systematic Random Sampling
  • Biased Random Sampling Methods
  • Sampling Error
  • Methods Of Collecting Data

MODULE 3 : EXPLORATORY DATA ANALYSIS 

  • Exploratory Data Analysis Introduction
  • Measures Of Central Tendencies: Mean, Median And Mode
  • Measures Of Central Tendencies: Range, Variance And Standard Deviation
  • Data Distribution Plot: Histogram
  • Normal Distribution
  • Z Value / Standard Value
  • Empherical Rule  and Outliers
  • Central Limit Theorem
  • Normality Testing
  • Skewness & Kurtosis
  • Measures Of Distance: Euclidean, Manhattan And MinkowskiDistance

MODULE 4 : HYPOTHESIS TESTING 

  • Hypothesis Testing Introduction
  • P- Value, Confidence Interval
  • Parametric Hypothesis Testing Methods
  • Hypothesis Testing Errors : Type I And Type Ii
  • One Sample T-test
  • Two Sample Independent T-test
  • Two Sample Relation T-test
  • One Way Anova Test

MODULE 5 : CORRELATION AND REGRESSION 

  • Correlation Introduction
  • Direct/Positive Correlation
  • Indirect/Negative Correlation
  • Regression
  • Choosing Right Method

MODULE 1: DATA ENGINEERING INTRODUCTION

• What is Data Engineering?
• Data Engineering scope
• Data Ecosystem, Tools, and platforms
• Core concepts of Data engineering

MODULE 2: DATA WAREHOUSE FOUNDATION

• Data Warehouse Introduction
• Database vs Data Warehouse
• Data Warehouse Architecture
• ETL (Extract, Transform, and Load)
• ETL vs ELT
• Star Schema and Snowflake Schema
• Data Mart Concepts
• Data Warehouse vs Data Mart — Know the Difference
• Data Lake Introduction
• Data Lake Architecture
• Data Warehouse vs Data Lake

MODULE 3: DATA SOURCES AND DATA IMPORT

• Types of data sources
• Databases: SQL and Document DBs
• Connecting to various data sources
• Importing data with SQL
• Managing Big data

MODULE 4: DATA PROCESSING

• Python NumPy Package Introduction
• Array data structure, Operations
• Python Pandas package introduction
• Data structures: Series and DataFrame
• Importing data into Pandas DataFrame
• Data processing with Pandas

MODULE 5: DOCKER AND KUBERNETES FOUNDATION

• Docker Introduction
• Docker Vs. regular VM
• Hands-on: Running our first container
• Common commands (Running, editing, stopping, and managing images)
• Publishing containers to DockerHub
• Kubernetes Orchestration of Containers
• Build Docker on Kubernetes Cluster

MODULE 6: DATA ORCHESTRATION WITH APACHE AIRFLOW

• Data Orchestration Overview
• Apache Airflow Introduction
• Airflow Architecture
• Setting up Airflow
• TAG and DAG
• Creating Airflow Workflow
• Airflow Modular Structure
• Executing Airflow

MODULE 7: DATA ENGINEERING PROJECT

• Setting Project Environment
• Data pipeline setup
• Hands-on: build scalable data pipelines

MODULE 1 : AWS DATA SERVICES INTRODUCTION 

  • AWS Overview and Account Setup
  • AWS IAM Users, Roles and Policies
  • AWS Lamdba overview
  • AWS Glue overview
  • AWS Kinesis overview
  • AWS Dynamodb overview
  • AWS Anthena overview
  • AWS Redshift overview

MODULE 2 : DATA INGESTION USING AWS LAMDBA 

  • Setup AWS Lamdba  local development env
  • Deploy project to Lamdba console
  • Data pipeline setup with Lamdba
  • Validating data files incrementally
  • Deploying Lamdba function

MODULE 3 : DATA PIPELINE WITH AWS KINESIS 

  • AWS Kinesis overview and setup
  • Data Streams with AWS Kinesis
  • Data Ingesting from AWS S3 using AWS Kinesis

MODULE 4 : DATA WAREHOUSE WITH AWS REDSHIFT 

  • AWS Redshift Overview
  • Analyze data using AWS Redshift from warehouses, data lakes and operations DBs
  • Develop Applications using AWS Redshift cluster
  • AWS Redshift federated Queries and Spectrum

MODULE 5 : DATA PIPELINE WITH AZURE SYNAPSE 

  • Azure Synapse setup
  • Understanding Data control flow with ADF
  • Data Pipelines with Azure Synapse
  • Prepare and transform data with Azure Synapse Analytics

MODULE 6 : STORAGE IN AZURE 

  • Create Azure storage account
  • Connect App to Azure Storage
  • Azure Blog Storage

MODULE 7: AZURE DATA FACTORY

  • Azure Data Factory Introduction
  • Data transformation with Data Factory
  • Data Wrangling with Data Factory

MODULE 8 : DATA ENG PROJECT WITH AZURE/AWS

  • Hands-on Project Case-study
  • Setup Project Development Env
  • Organization of Data Sources
  • AZURE/AWS services for Data Ingestion
  • Data Extraction Transformation  

MODULE 1: DATA WAREHOUSE FOUNDATION

• Data Warehouse Introduction
• Database vs Data Warehouse
• Data Warehouse Architecture
• ETL (Extract, Transform, and Load)
• ETL vs ELT
• Star Schema and Snowflake Schema
• Data Mart Concepts
• Data Warehouse vs Data Mart — Know the Difference
• Data Lake Introduction
• Data Lake Architecture
• Data Warehouse vs Data Lake

MODULE 2: DOCKER FOUNDATION

• Docker Introduction
• Docker Vs. regular VM
• Hands-on: Running our first container
• Common commands (Running, editing, stopping and managing images)
• Publishing containers to Docker Hub
• Kubernetes Orchestration of Containers
• Build Docker on Kubernetes Cluster

MODULE 3: KUBERNETES CONTAINER ORCHESTRATION

• Kubernetes Introduction
• Setting up Kubernetes Clusters
• Kubernetes Orchestration of Containers
• Build Docker on Kubernetes Cluster

MODULE 4: DATA ORCHESTRATION WITH APACHE AIRFLOW

• Data Orchestration Overview
• Apache Airflow Introduction
• Airflow Architecture
• Setting up Airflow
• TAG and DAG
• Creating Airflow Workflow
• Airflow Modular Structure
• Executing Airflow

MODULE 5: DATA ENGINEERING PROJECT

• Setting Project Environment
• Data pipeline setup
• Hands-on: build scalable data pipelines

MODULE 1 : DATABASE INTRODUCTION 

  • DATABASE Overview
  • Key concepts of database management
  • CRUD Operations
  • Relational Database Management System
  • RDBMS vs No-SQL (Document DB)

MODULE 2 : SQL BASICS 

  • Introduction to Databases
  • Introduction to SQL
  • SQL Commands
  • MY SQL  workbench installation
  • Comments
  • import and export dataset

MODULE 3 : DATA TYPES AND CONSTRAINTS 

  • Numeric, Character, date time data type
  • Primary key, Foreign key, Not null
  • Unique, Check, default, Auto increment

MODULE 4 : DATABASES AND TABLES (MySQL) 

  • Create database
  • Delete database
  • Show and use databases
  • Create table, Rename table
  • Delete table, Delete  table records
  • Create new table from existing data types
  • Insert into, Update records
  • Alter table

MODULE 5 : SQL JOINS 

  • Inner join
  • Outer join
  • Left join
  • Right join
  • Cross join
  • Self join

MODULE 6 : SQL COMMANDS AND CLAUSES 

  • Select, Select distinct
  • Aliases, Where clause
  • Relational operators, Logical
  • Between, Order by, In
  • Like, Limit, null/not null, group by
  • Having, Sub queries

MODULE 7 : DOCUMENT DB/NO-SQL DB

  • Introduction of Document DB
  • Document DB vs SQL DB
  • Popular Document DBs
  • MongoDB basics
  • Data format and Key methods
  • MongoDB data management

MODULE 1: BIG DATA INTRODUCTION

• Big Data Overview
• Five Vs of Big Data
• What is Big Data and Hadoop
• Introduction to Hadoop
• Components of Hadoop Ecosystem
• Big Data Analytics Introduction

MODULE 2: HDFS AND MAP REDUCE

• HDFS – Big Data Storage
• Distributed Processing with Map Reduce
• Mapping and reducing stages concepts
• Key Terms: Output Format, Partitioners, Combiners, Shuffle, and Sort
• Hands-on Map Reduce task

MODULE 3: PYSPARK FOUNDATION

• PySpark Introduction
• Spark Configuration
• Resilient distributed datasets (RDD)
• Working with RDDs in PySpark
• Aggregating Data with Pair RDDs

MODULE 4: SPARK SQL and HADOOP HIVE

• Introducing Spark SQL
• Spark SQL vs Hadoop Hive
• Working with Spark SQL Query Language

MODULE 5: MACHINE LEARNING WITH SPARK ML

• Introduction to MLlib Various ML algorithms supported by Mlib
• ML model with Spark ML.
• Linear regression
• logistic regression
• Random forest

MODULE 6: KAFKA and Spark

• Kafka architecture
• Kafka workflow
• Configuring Kafka cluster
• Operations

DATA ENGINEER TRAINING COURSE REVIEWS

ABOUT DATAMITES DATA ENGINEER TRAINING IN ROURKELA

In today's digital landscape, data engineers hold the key to unlocking the immense value hidden within the vast realm of data. As data emerges as the new currency, these skilled professionals serve as the architects of information, crafting scalable data pipelines and employing state-of-the-art technologies to process and analyze massive volumes of data. Market projections indicate that the big data industry is poised to soar to a staggering $103 billion by 2027, underscoring the growing need for talented data engineers who can navigate this data-driven landscape with finesse and expertise.

Embark on a transformative journey in data engineering with DataMites' comprehensive Data Engineer Course in Rourkela. This course spans over 6 months, offering an extensive learning experience of 150+ hours. Through our 50+ hours of live online training, you will gain in-depth knowledge of data engineering concepts, techniques, and tools. As part of the course, you will work on 10 capstone projects and a real-world client project, applying your skills to solve practical data engineering challenges. With our 365 days Flexi Pass and Cloud Lab, you have the flexibility to access course materials and practice in a cloud-based lab environment at your convenience. Additionally, we also offer Data Engineer Offline Courses On Demand in Rourkela, catering to those who prefer an offline learning experience.

10 reasons to choose DataMites for Data Engineer Training in Rourkela:

Ashok Veda and Faculty: Learn from industry experts and experienced professionals, including renowned data scientist Ashok Veda, who will guide you throughout the course.

Comprehensive Course Curriculum: Our course curriculum covers all essential data engineering concepts, tools, and techniques, ensuring a holistic learning experience.

Global Certification: Gain prestigious certifications from IABAC, NASSCOM FutureSkills Prime, and JainX, enhancing your credibility and employability.

Flexible Learning: Enjoy the convenience of flexible learning options, including online data engineer courses in Rourkela, self-paced study, and access to course materials anytime, anywhere.

Projects with Real-World Data: Work on hands-on projects using real-world datasets to develop practical data engineering skills and experience.

Internship Opportunity: Get a chance to apply your knowledge and gain industry exposure through our data engineer course with internship in Rourkela with leading organizations.

Placement Assistance and Job References: Avail data engineer training with placement in Rourkela and job references to kick-start your career as a data engineer.

Hardcopy Learning Materials and Books: Access hardcopy learning materials and books that supplement your online learning experience.

DataMites Exclusive Learning Community: Connect and collaborate with a vibrant community of data enthusiasts, professionals, and experts.

Affordable Pricing and Scholarships: We offer competitive pricing for our courses, and eligible candidates can also avail scholarships to support their learning journey.

Rourkela, located in the state of Odisha, India, is a city known for its rich industrial heritage and vibrant culture. It is home to several steel plants and engineering institutes, making it a hub of technical education and opportunities. The city's strategic location provides easy access to nearby metropolitan areas and business centers. Rourkela's dynamic and evolving landscape makes it an ideal place to pursue a career in data engineering, with ample opportunities for professionals in the field.

Along with the data engineer courses, DataMites also provides data analytics, IoT, AI expert, machine learning, data mining, tableau, artificial intelligence, deep learning, mlops, data science, data  analyst, r programming and python training courses in Rourkela.

ABOUT DATA ENGINEER COURSE IN ROURKELA

Data engineering refers to the field that focuses on the design, development, and maintenance of systems and processes involved in handling large volumes of data. Data engineers build and manage data infrastructure to ensure data quality and availability for analysis and decision-making.

The benefits of undergoing Data Engineer Training include gaining in-depth knowledge of data engineering concepts, acquiring practical skills in data pipeline development and management, improving employability in the growing field of data engineering, and staying updated with industry practices and technologies.

The prerequisites for enrolling in a Data Engineer Course in Rourkela may vary, but a basic understanding of programming, databases, and data concepts is beneficial. Some courses may require a background in computer science or related fields.

The fees for Data Engineer Training in Rourkela vary depending on the institute, course duration, and curriculum. It is recommended to check with specific training providers for detailed fee information and any available scholarships or discounts.

The best institute for Data Engineer Training in Rourkela depends on individual preferences and specific requirements. It is advisable to research and compare different institutes based on curriculum, faculty expertise, industry reputation, alumni reviews, and placement opportunities.

After completing Data Engineer Training, individuals can pursue job roles such as Data Engineer, Data Architect, ETL Developer, Data Warehouse Manager, Big Data Engineer, Database Administrator, or Cloud Data Engineer. These roles involve designing and managing data infrastructure, developing data pipelines, and ensuring efficient data processing and storage.

A bachelor's degree in computer science, information technology, or a related field is typically required for a data engineering career. However, some positions may require a master's degree or higher level of education, depending on the organization and complexity of the data engineering tasks.

While a postgraduate (PG) degree is not mandatory for Data Engineer Training, it can be beneficial for gaining a deeper understanding of advanced data engineering concepts and research methodologies. However, individuals with a bachelor's degree and practical experience can also have successful careers in data engineering.

Essential skills for a data engineer include proficiency in programming languages like Python, SQL, or Scala, knowledge of database systems and data modeling, familiarity with big data technologies such as Hadoop and Spark, experience with data integration and ETL processes, understanding of cloud platforms and data warehousing, and strong problem-solving and analytical abilities.

The choice of language for data engineering depends on specific requirements and the technology stack being used. However, Python is widely preferred in the data engineering field due to its versatility, extensive libraries for data manipulation and analysis, and ease of use. SQL is also essential for working with relational databases and querying data. Other languages like Scala and Java are commonly used in big data processing frameworks like Apache Spark.

Data Analytics offers promising career opportunities in roles such as data analysts, data scientists, business analysts, and data engineers. Skilled professionals are in high demand across diverse industries.

Being a data analyst can be challenging as it involves working with complex datasets, applying analytical techniques, and staying updated with emerging technologies. Strong analytical and problem-solving skills are essential.

View more

FAQ’S OF DATA ENGINEER COURSE IN ROURKELA

Data engineering can be defined as the discipline that involves designing, constructing, and maintaining the systems, processes, and infrastructure necessary for the efficient and reliable collection, storage, transformation, and analysis of large volumes of data. Data engineers play a crucial role in developing and managing the pipelines that extract, transform, and load data from various sources into data warehouses or data lakes, ensuring data quality, integrity, and availability for further analysis and decision-making.

Data Engineer Training offers several benefits, including gaining comprehensive knowledge of data engineering concepts, acquiring practical skills in data pipeline development and management, enhancing career prospects in the growing field of data engineering, and staying updated with industry practices and technologies.

A career in data engineering typically requires a strong educational background in computer science, information technology, or a related field. A bachelor's degree is often the minimum requirement, but some positions may prefer or require a master's degree, especially for more advanced or research-oriented roles.

The requirements for joining a Data Engineer Course in Rourkela typically include a bachelor's degree in a related field (such as computer science or engineering), basic programming skills, knowledge of data and databases, familiarity with big data technologies, and a basic understanding of mathematics and statistics.

The cost of Data Engineer Training in Rourkela can vary due to factors such as the institute selected, program duration, delivery mode (online or classroom), and any additional features included. On average, the fees for data engineer training in Rourkela usually range from 40,000 INR to INR 1,00,000.

With the exponential growth of data and the increasing importance of data-driven decision-making in organizations across industries, the demand for skilled data engineers is expected to continue rising. Data engineering plays a critical role in managing and processing large volumes of data efficiently, ensuring data quality and availability for analysis. As businesses seek to harness the power of data to gain insights and drive innovation, data engineers will be in high demand to design and maintain robust data infrastructure, develop efficient data pipelines, and implement scalable solutions.

After completing Data Engineer Training, individuals can pursue various career options, including roles such as Data Engineer, Data Architect, ETL Developer, Data Warehouse Manager, Big Data Engineer, Database Administrator, or Cloud Data Engineer. These roles involve designing and managing data infrastructure, developing data pipelines, and ensuring efficient data processing and storage.

No, DevOps and data engineering are not interchangeable terms. DevOps is a set of practices that combines software development and IT operations to improve collaboration and efficiency, while data engineering focuses specifically on the management and processing of data within an organization. Although there may be some overlap in skills and responsibilities, they are distinct disciplines within the technology industry.

The best institute for data engineering training depends on several factors, such as the curriculum, faculty proficiency, industry relationships, alumni testimonials, and available training formats. DataMites is widely regarded as an exceptional institute for data engineering training. Its well-structured curriculum, practical projects aligned with industry requirements, and experienced instructors contribute to a comprehensive learning experience, enabling students to grasp essential data engineering concepts, tools, and techniques.

While a postgraduate degree is not always mandatory for Data Engineer Training, it can provide a deeper understanding of advanced data engineering concepts and research methodologies. However, a bachelor's degree and relevant practical experience can also be sufficient to pursue a successful career in data engineering.

The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -

  • 1. Job connect
  • 2. Resume Building
  • 3. Mock interview with industry experts
  • 4. Interview questions

The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.

No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.

View more

DATA ENGINEER PROJECTS

DATA ENGINEER JOB INTERVIEW QUESTIONS

OTHER DATA ENGINEER TRAINING CITIES IN INDIA

Global CERTIFIED DATA ENGINEER COURSES Countries

popular career ORIENTED COURSES

DATAMITES POPULAR COURSES


HELPFUL RESOURCES - DataMites Official Blog