Why Big data?
Generally, the data is not prepared for the immediate use of
the Data Scientist. It is that the mass of data is optimized so that the
Scientist can make the best use of this valuable asset that drives the
decision-making of the main companies in the world. The Big Data market
understands that it is important to let the Data Scientist focus only on what
to do with the data. Therefore, a professional is needed with a focus on how to
access this data efficiently (high performance) and effective (high accuracy).
The Data Engineer must be able to create means that
transform the mass of data into formats that can be analyzed by the Data
Scientist. The technical term for this medium is pipeline. The pipeline is a
process composed of ingestion, processing, storage and data access operations.
The Data Engineer has a general profile and is focused on the pipeline and
databases. The professional who wants to be a Data Engineer should start by
learning how to architect distributed systems and data warehouses, create reliable
pipelines, combine multiple data sources, and collaborate with the Data Science
team.
Communication between the Data Engineer and the Data Scientist is vital
to the success of the company that wants to work with Big Data. This course is
the gateway to the Data Engineer world and presents an essential overview of
the key tools the student must master. This course is focused on open tools
since Open Source is the main reason for the evolution of Big Data.
In addition, this course shows how is the integration and
communication between the areas of Science and Data Engineering. The course
aims to present the main Open Source tools of the world of Data Engineering
with examples and real practices of the market focusing mainly on Hadoop and
Spark.
This course presents aspects related to Hadoop
infrastructure, especially in the topics of troubleshooting, user management
(Knox, Ranger, ACLs) as well as topics related to high availability and
balancing in Hadoop. With this, we now meet the requirements for Hortonworks
HDPCA (HDP Certified Administrator) and HDPCD (HDP Certified Developer)
certification. This course now also takes care of orienting the student showing
how to fit all these open source tools into a data architecture: lambda. It is
important that the Data Engineer master a programming language, big data online training in Bangalore that is easy to
learn and scalable, so without disturbing your daily works through online you
can easily learn Big Data course.
The big data
online training in Bangalore Program transforms you into a qualified Hadoop
Developer. This data architect certification lets you master various aspects of
Hadoop, including real-time processing using Spark and NoSQL database
technology Big Data Hadoop developers are among the highest paid professionals
in the IT industry. Hadoop and Big data technologies is the future of IT in the
future