U-Next

SEPTEMBER 23, 2022

The fast development of digital technologies, IoT goods and connectivity platforms, social networking apps, video, audio, and geolocation services has created the potential for massive amounts of data to be collected/accumulated. Real-life Examples of Big Data In Action .

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

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). Moreover, Spark SQL makes it possible to combine streaming data with a wide range of static data sources. 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. Data governance is more focused on data administration, and data engineering is focused on data execution.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52