Best Data Engineering Course Training in Japan
- 40 Hours Interactive Online Sessions
- 80 Hours Assignments & Real-Time Projects
- Complementary Hadoop and Spark
- Complementary ML on Cloud
- Complementary Python Programming
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3117 Learners
Academic Partners & International Accreditations
Data engineering is about generating quality data and making it available for businesses to make data-driven decisions. Requirement for Data Engineering professionals has always outstripped the supply since 2017. Data Engineers enable businesses to engage in insights produced by data science using advanced analytics. This course in Data Engineering will equip you to build big data superhighways by teaching you the skills to unlock the value of data. According to reports, Data Engineer is the fastest-growing job in the space of technology, and with this course in Data Engineering, you will be able to kick start your new career as a Data Engineer today!
Data Engineering
Total Duration
3 Months
Prerequisites
- Computer Skills
- Basic Mathematical Concepts
- Analytical Mindset
Data Engineering Training Overview in Japan
With our Data Engineering Training, you get to explore the various tools used by Data Engineers and understand the difference between a Data Scientist and a Data Engineer. In this training, get introduced to tools like Python, Spark, Kafka, Jupyter. Spyder, TensorFlow, Keras, PyTorch, etc. along with advanced SQL techniques. Learn to extract raw data from various data sources in multiple formats and then transform them into actionable insights, and deploy them into a single, easy-to-query database. Learn how to build pipelines while handling huge data to optimize the process of big data. Get firsthand experience with advanced data engineering projects.
What is Data Engineering?
A Data Engineer collects and transforms data to empower businesses to make data-driven decisions. He has to pay attention to security and compliance; reliability and fidelity; scalability and efficiency; and flexibility and portability while designing, operationalizing and monitoring data processing systems.
Data Engineering Training Learning Outcomes in Japan
These modules will lay out the foundation for data science and analytics. The core of Data Engineering involves an understanding of various techniques like data modelling, building data engineering pipelines, and deploying the analytics models. Students will learn how to wrangle data and perform advance analytics to get the most value out of data. As you progress, you'll learn how to design as well as build data pipelines and work with big data of diverse complexity and production databases. You will also learn to extract and gather data from multiple sources, build data processing systems, optimize processes for big data, build data pipelines, and much more. With this course develop skills to use multiple data sources in a scalable way and also master the skills involved in descriptive and inferential statistics, interactive data analysis, regression analysis, forecasting, and hypothesis testing. Also, learn to
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Who Should Sign Up?
- Science, Math and Commerce graduates
- IT professionals who want to specialise in digital tech
- Professionals who want to move into Data Analytics
- Professionals who want to add Data Analytics to current job skills
- Academicians and researchers working in Data Analytics
Data Engineering Course Syllabus in Japan
These modules on Data Engineering are designed to ensure that they are at par with the current industry requirements for Data Engineers. All the modules will wrap up with hands-on practice using real tools and real-time multiple databases. With these modules you will learn to manage, load, extract, and transform data to facilitate delivering of results that your organization can leverage. You will also learn to master the core skills of cleansing, and migrating data.
- Data Science vs Data Engineering
- Data Engineering Infrastructure and Data Pipeline
- Data Architecture
- Lambda
- Kappa
- Streaming Big Data Architectures Monitoring pipelines
- With Databases and various File formats (Data Lakes)
- SQL
- MySQL
- PostgreSQL
- NoSQL
- MongoDB
- HBase
- Amazon Relational Database Service
- Microsoft Azure SQL Database
- Google Cloud SQL
- Concepts of Extra-Load, Extract-Load-Transform, or Extract-Transform-Load paradigms
- Getting started with Python programming for Data Processing
- Data Types
- Python Packages
- Loops and Conditional Statements
- Functions
- Collections
- String Handling
- File handling
- Exceptional Handling
- MySQL Integration
- INSERT, READ, DELETE, UPDATE, COMMIT, ROLLBACK operations
- MongoDB Integration
- Pre-processing, Cleaning, and Transforming Data
- Linux OS
- Apache Hadoop
- HDFS
- Hadoop Cluster on GCP - Dataproc
- Spark Components
- Spark Executions – Spark Session
- RDD
- Spark DataFrames
- Spark Core
- Spark SQL
- Spark MLlibs
- Spark Streaming
- Big Data and Apache Kafka
- Producers and Consumers
- Clusters Architectures
- Kafka Streams
- Kafka pipeline transformations
- Building pipelines in Apache Airflow
- Deploy and Monitor Data Pipelines
- Production Data Pipeline
- Data Lake Cloud offerings
- Cloud Data Warehouse Services
- Introduction to AWS platform, Creation of free account
- Walk through the platform and services offered by AWS
- IAM - Identity and Access Management
- Intro to AWS Data Warehouses, Data Marts, Data Lakes, and ETL/ELT pipelines
- Configuring the AWS Command Line Interface tool
- Creating an S3 bucket
- Working with Databases and various File formats (Data Lakes)
- Amazon Database Migration Service (DMS) for ingesting data
- Amazon Kinesis and Amazon MSK for streaming data
- AWS Lambda for transforming data
- AWS Glue for orchestrating big data pipelines
- Consuming data - Amazon Redshift & Amazon Athena for SQL queries
- Introduction to Microsoft Azure platform, Creation of free account
- Walk through the platform and services offered by Azure
- IAM - Identity and Access Management
- Azure Data Lake - Managing Data
- Securing and Monitoring Data
- Introduction to Azure Data Factory (ADF)
- Building Data Ingestion Pipelines Using Azure Data Factory
- Azure Data Factory Integration Runtime
- Configuring Azure SQL Database
- Processing Data with Azure Databricks
- Introduction to Azure Synapse Analytics
- Data Transformations with Azure Synapse Dataflows
- Monitoring And Maintaining Azure Data Engineering Pipelines
- Introduction to GCP platform, Creation of free account
- Walk through the platform and services offered by GCP
- IAM - Identity and Access Management
- Bigdata Solutions with GCP Components
- Data Warehouse - BigQuery
- Processing ETL/ELT pipelines with Data Fusion
- Connecting BI tool for visualizing Data with Looker Studio
- Architecting Data Pipelines
- CI/CD On Google Cloud Platform for Data Engineers
- Storage Accounts
- Designing Data Storage Structures
- Data Partitioning
- Designing the Serving Layer
- Physical Data Storage Structures
- Logical Data Structures
- The Serving Layer
- Data Policies & Standards
- Securing Data Access
- Securing Data
- Data Lake Storage
- Data Flow Transformations
- Databricks
- Databrick Processing
- Stream Analytics
- Synapse Analytics
- Data Storage Monitoring
- Data Process Monitoring
- Data Solution Optimization
- Google Cloud Platform Fundamentals
- Google Cloud Platform Storage and Analytics
- Deeper through GCP Analytics and Scaling
- GCP Network Data Processing Models
- Google Cloud Dataproc
- Dataproc Architecture
- Continued Dataproc Operations
- Implementations with BigQuery for Big Data
- Fundamentals of Big Query
- APIs and Machine Learning
- Dataflow Autoscaling Pipelines
- Machine Learning with TensorFlow and Cloud ML
- GCP Engineering and Streaming Architecture
- Streaming Pipelines and Analytics
- GCP Big Data and Security
Trends in Data Engineering Certification in Japan
A Data Engineer will analyze the given data and discover trends in the data sets and develop algorithms to sort the data to make it useful to the organization. To understand the organization's large data, Data Engineers need technical skills with good communication skills to work across various departments. 2021 saw a tremendous increase in usage of AI, MI, and Data Science in the industry. Data Engineering trends can be classified into Data Infrastructure, Data Architecture, and Data Management categories. While metadata management tools like data lineage, data quality, and data discovery will merge into the mainstream data management platform. To manage this platform Data Mesh Principles and change in data engineering structure should be made and serverless architecture is one among them. Cloud data warehouses will be the future of data management systems. A Data Engineer will be able to manage the main role in this process to develop, expand and deploy new technologies. Join our Data Engineering training program to grab the best opportunity in the growing job market.
How we prepare you
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Additional assignments of over 80+ hours
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Live Free Webinars
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Resume and LinkedIn Review Sessions
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Lifetime LMS Access
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24/7 support
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Job placements in Data Engineering fields
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Complimentary Courses
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Unlimited Mock Interview and Quiz Session
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Hands-on experience in a live project
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Offline Hiring Events
Call us Today!
+60 19-383 1378Data Engineering Course Panel of Coaches
Bharani Kumar Depuru
- Areas of expertise: Data Analytics, Digital Transformation, Industrial Revolution 4.0
- Over 18+ years of professional experience
- Trained over 2,500 professionals from eight countries
- Corporate clients include Deloitte, Hewlett Packard Enterprise, Amazon, Tech Mahindra, Cummins, Accenture, IBM
- Professional certifications - PMP, PMI-ACP, PMI-RMP from Project Management Institute, Lean Six Sigma Master Black Belt, Tableau Certified Associate, Certified Scrum Practitioner, (DSDM Atern)
- Alumnus of Indian Institute of Technology, Hyderabad and Indian School of Business
Sharat Chandra Kumar
- Areas of expertise: Data sciences, Machine learning, Business intelligence and Data Visualization
- Trained over 1,500 professional across 12 countries
- Worked as a Data scientist for 18+ years across several industry domains
- Professional certifications: Lean Six Sigma Green and Black Belt, Information Technology Infrastructure Library
- Experienced in Big Data Hadoop, Spark, NoSQL, NewSQL, MongoDB, Python, Tableau, Cognos
- Corporate clients include DuPont, All-Scripts, Girnarsoft (College-, Car-) and many more
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Bhargavi Kandukuri
- Areas of expertise: Business analytics, Quality management, Data
visualisation with Tableau, COBOL, CICS, DB2 and JCL - Electronics and communications engineer with over 19+ years of industry experience
- Senior Tableau developer, with experience in analytics solutions development in domains such as retail, clinical and manufacturing
- Trained over 750+ professionals across the globe in three years
- Worked with Infosys Technologies, iGate, Patni Global Solutions as technology analyst
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Alumni Speak
"Coming from a psychology background, I was looking for a Data Science certification that can add value to my degree. The 360DigiTMG program has such depth, comprehensiveness, and thoroughness in preparing students that also looks into the applied side of Data Science."
"I'm happy to inform you that after 4 months of enrolling in a Professional Diploma in Full Stack Data Science, I have been offered a position that looks into applied aspects of Data Science and psychology."
Nur Fatin
Associate Data Scientist
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"360DigiTMG has an outstanding team of educators; who supported and inspired me throughout my Data Science course. Though I came from a statistical background, they've helped me master the programming skills necessary for a Data Science job. The career services team supported my job search and, I received two excellent job offers. This program pushes you to the next level. It is the most rewarding time and money investment I've made-absolutely worth it.”
Thanujah Muniandy
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"360DigiTMG’s Full Stack Data Science programme equips its graduates with the latest skillset and technology in becoming an industry-ready Data Scientist. Thanks to this programme, I have made a successful transition from a non-IT background into a career in Data Science and Analytics. For those who are still considering, be bold and take the first step into a domain that is filled with growth and opportunities.”
Ann Nee, Wong
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"360DigiTMG is such a great place to enhance IR 4.0 related skills. The best instructor, online study platform with keen attention to all the details. As a non-IT background student, I am happy to have a helpful team to assist me through the course until I have completed it.”
Mohd Basri
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"I think the Full Stack Data Science Course overall was great. It helped me formalize and think more deeply about ways to tackle the projects from a Data Science perspective. Also, I was remarkably impressed with the instructors, specifically their ability to make complicated concepts seem very simple."
"The instructors from 360DigiTMG were great and it showed how they engaged with all the students even in a virtual setting. Additionally, all of them are willing to help students even if they are falling behind. Overall, a great class with great instructors. I will recommend this to upcoming deal professionals going forward.”
Ashner Novilla
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FAQs for Data Engineering Certification Training in Japan
The Data Engineering course aims to provide aspirants with an in-depth understanding of all the essential tools and skills used by Data Engineers. The course provides hands-on learning of leading as Python, SQL, Spark, Kafka, and many more.
The training will be conducted in hybrid mode i.e., through the live instructor-led virtual sessions. The timings for both the sessions will be the same.
After the successful completion of 80% of your assignments, you are assigned to a live project where you will work with a group of students to bring the project to closure. After that, you will make a project presentation.
After the successful completion of the program, you will be awarded the Data Engineering certificate, powered by IBM.
This course is designed for students as well as working professionals. The basic requirement to undertake this course includes a degree in engineering, computer applications, or mathematics.
No, there are no extra charges for the certification. The cost is included in the package.
Not to worry, if you miss out on a session you can access the recorded session from the online Learning Management System (LMS).
We do not guarantee placements nevertheless, our placement cell supports you with resume building sessions, mock interviews, mentorship, and interview preparation. Our team also helps you launch your career by providing interview opportunities.
Jobs in Data Engineering in Japan
A Data Engineer is responsible for developing computer algorithms to identify trends in large data sets. The most common career paths for Data Engineer include Data Scientist, Data Architecture, Data Analyst, and Software Engineers.
Salary for Data Engineers in Japan
The demand for Big Data Engineers with strong analytic skills to handle data generated from various platforms with proficiency in SQL database design gets an average salary of Rs 8,17,911 LPA.
Projects in the field of Data Engineering in Japan
Data engineering is the most critical skill for a Data Scientist and the various projects students could take up include Analyzing sentiments, Detecting credit card fraud, Detection of color, and many more.
Role of Open Source Tools in Data Engineering in Japan
The various tools we will be exploring in this course are Apache Hadoop, Apache Spark, Apache Hive, Apache Kafka, NoSQL, and many more.
Modes Of Training For Data Engineering in Japan
The course in Data Engineering is designed to suit the needs of students as well as working professionals. We at 360DigiTMG give our students the option of interactive live online learning. We also support e-learning as part of our curriculum.
Industry Applications of Data Engineering in Japan
Data Engineers dominate many industries including Banking, Media, Education, Healthcare, manufacturing, etc.
Companies That Trust Us
360DigiTMG offers customised corporate training programmes that suit the industry-specific needs of each company. Engage with us to design continuous learning programmes and skill development roadmaps for your employees. Together, let’s create a future-ready workforce that will enhance the competitiveness of your business.
Student Voices
Sana Ahsan
3 years agoI still remember going through websites for the Data Scientist course and reading reviews. That's when I finally found 360DigiTMG. Today, I will consider 360DigiTMG as the best one because it has offered me way more than any other training institute can do: Incredible curriculum, instructors, mentorship, and most job search skills and interviews best practices. One of the best decisions I made, I strongly recommend the Data Science program at 360DigiTMG to anyone looking for a Data Scientist/Analyst role. I am happy to announce that presently I am deputed as a Specialist Data Scientist at one of the top MNC.
Suriyaa Kumar
3 years agoI attended the Certification in Data Science program by 360DigiTMG. The course was amazing. I had a great learning & networking experience. Also, trainers are highly experienced and knowledgeable in the field of Data Science. I will recommend this course to anyone who wants to become a Data Scientist.
Asyraaf Afandi
3 years agoI joined the Data Science Certification Program which is a great place to learn if you want to start your career in the Data Science industry. The trainers are very knowledgeable and will try to explain the topics until you truly understand it. I would definitely recommend others to join it.
Iqmal Harris
3 years agoThe courses are taught by seasoned industry experts who know how to train absolute beginners and established professionals alike. Glad to have trained under 360DigiTMG.
Zarif Iqram
2 years agoI worked on a Survival Analysis project, which gave me good exposure and boosted my skill set in Business Intelligence with Power BI. Good to have it more and be involved in the real-time projects.
