Train learners in cutting-edge tools for Data Analysis, Data Stream Processing, Data Pipelines and Workflow Management
Guide learners in practical applications of Data Governance & Data Operations on Cloud Platforms
Equip learners with technical skills, problem solving abilities and collaborative work practices
Prepare learners for key roles such as Data Engineer, Big Data Architect and Cloud Data Engineer
On successful completion of the program learners will have:
Who are Data Engineers?
Data engineering is the process of transforming raw data into valuable information.
It’s a critical process for businesses that want to make data-driven decisions and is assuming importance with the generation of massive volumes of data in our daily lives.
Data engineers are professionals skilled in the collection, storing and parsing of data and utilizing machine learning to analyze the data.
Their job requires a critical understanding of both software development tools as well as business skills required to convert that data into valuable information.
Data Engineer: A data engineer lays down the foundation for data management systems to ingest, integrate and maintain all the data sources. The person has knowledge of databases and understands the needs of the business and its long-time data scalability needs. Tools: SQL, XML, Hive, Pig, Spark, etc.
Database Administrator: A database administrator has extensive knowledge of traditional as well as new-age NoSQL and Cloud databases, and ensures that the data generating and the data ingesting systems are up and running in a live business scenario.
Enterprise Data Architect: The enterprise data architect is responsible for visualizing and designing an organization’s enterprise data management framework that describes the processes used to plan, specify, enable, create, acquire, maintain, use, archive, retrieve, control, and purge data. They have extensive knowledge of database tools, languages like Python, Java and Scala, and distributed systems like Hadoop.
ETL Engineer: The ETL engineer is responsible for maintaining the veracity of the data in the source and target systems. They ensure that the right kind of tools, permission and system pipelines are in place for smooth transfer of the data.
The 6-month program is divided into three trimesters of two-months each covering: Working with traditional data Engineering platforms for big data, and Running enterprise business on cloud. The pedagogy comprises design of a contemporary and relevant curriculum delivery which is a blend of classroom lectures, use case discussions and hands-on labs, and assessment based on tests, assignments and projects.
Pedagogy
Blend of lectures, case discussions, labs, assessment via tests, assignments, projects.
Trimester 1 - Working with Traditional Data | Trimester 2 - Managing Data Platforms & Cloud | Trimester 3 - Enterprise Business Applications |
Data Fluency | Python Programming | Spark Data Analytics |
Data Modeling | RDBMS | NoSQL |
Business Intelligence | Data Warehousing | Big Data |
Data Exploration and Analysis | Cloud Data Management | Capstone Project |
Structured Query Language (SQL) |
The Capstone Project at Praxis is designed to bridge the gap between theory and practice. Learners get to work on relevant industry problems using the latest cutting edge tools and technologies.
FEES
Total Program Fee: Rs. 99,000 (Incl. 18% GST)
ELIGIBILITY
Who is this program meant for?
This course is aimed at facilitating a smooth transition of the participants into the domain of data engineering. It is meant for candidates satisfying any of the following criteria:
SELECTION PROCESS
SCHOLARSHIPS
Students can avail themselves of any one of the above scholarships. Praxis reserves the right to grant scholarship based on the criteria mentioned above.
ONLINE FEE PAYMENT
Please note, when transferring the fee online towards the course fee, the following payment gateway charges would need to be borne by the student:
Details Charges:
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+91-7676-160-161
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