Knowledge Hut

JULY 27, 2023

They are skilled in working with tools like MapReduce, Hive, and HBase to manage and process huge datasets, and they are proficient in programming languages like Java and Python. Using the Hadoop framework, Hadoop developers create scalable, fault-tolerant Big Data applications. What do they do?

Hadoop 52

Hadoop Programming Language Banking Scala 52

ProjectPro

DECEMBER 28, 2021

Discretized Streams, or DStreams, are fundamental abstractions here, as they represent streams of data divided into small chunks(referred to as batches). Many traditional stream processing systems use a continuous operator model to process data. live logs, IoT device data, system telemetry data, etc.)

Architecture 52

Architecture Kafka Java Scala 52

phData: Data Engineering

JANUARY 3, 2022

Performance It’s not as simple as having data correct and available for a data engineer. Data must also be performant. It’s also important to define what performance means with regard to your data. This may be okay for small datasets, but certainly isn’t feasible when you’re in the Big Data ecosystem.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

U-Next

SEPTEMBER 23, 2022

To handle this large amount of data, we want a far more complicated architecture comprised of numerous components of the database performing various tasks rather than just one. . Real-life Examples of Big Data In Action . To address these issues, Big Data technologies such as Hadoop were established.

Big Data Ecosystem 40

Big Data Ecosystem Big Data Healthcare Data Lake 40

U-Next

JUNE 29, 2022

Preparing data for analysis is known as extract, transform and load (ETL). While the ETL workflow is becoming obsolete, it still serves as a common word for the data preparation layers in a big data ecosystem. Working with large amounts of data necessitates more preparation than working with less data.

Big Data 40

Big Data Big Data Ecosystem Data Lake Raw Data 40