Knowledge Hut

JANUARY 18, 2024

“Big data Analytics” is a phrase that was coined to refer to amounts of datasets that are so large traditional data processing software simply can’t manage them. For example, big data is used to pick out trends in economics, and those trends and patterns are used to predict what will happen in the future.

Data Process 52

Data Process Process Hadoop Scala 52

Knowledge Hut

SEPTEMBER 6, 2023

Data Analysis : Strong data analysis skills will help you define ways and strategies to transform data and extract useful insights from the data set. Big Data Frameworks : Familiarity with popular Big Data frameworks such as Hadoop, Apache Spark, Apache Flink, or Kafka are the tools used for data processing.

Big Data 52

Big Data Certification Hadoop Scala 52

Data Engineering Podcast

JUNE 11, 2021

Summary Google pioneered an impressive number of the architectural underpinnings of the broader big data ecosystem. In this episode Lak Lakshmanan enumerates the variety of services that are available for building your various data processing and analytical systems. No more scripts, just SQL.

Google Cloud 100

Google Cloud Cloud Big Data Ecosystem BI 100

Knowledge Hut

DECEMBER 21, 2023

The primary process comprises gathering data from multiple sources, storing it in a database to handle vast quantities of information, cleaning it for further use and presenting it in a comprehensible manner. Data engineering involves a lot of technical skills like Python, Java, and SQL (Structured Query Language).

Data Engineering 52

Data Engineering Data Engineer Engineering MongoDB 52

Edureka

JUNE 1, 2023

Without spending a lot of money on hardware, it is possible to acquire virtual machines and install software to manage data replication, distributed file systems, and entire big data ecosystems. This happens often in data analytics since running reports on huge data processes is done once in a while.

AWS 52

AWS Data Analytics Cloud Amazon Web Services 52

ProjectPro

DECEMBER 28, 2021

Spark Streaming was launched in 2013 to enable data engineers and data scientists to process real-time data from SQL databases, Flume, Amazon Kinesis, etc. Discretized Streams, or DStreams, are fundamental abstractions here, as they represent streams of data divided into small chunks(referred to as batches).

Architecture 52

Architecture Kafka Java Scala 52

ProjectPro

FEBRUARY 8, 2017

The need for speed to use Hadoop for sentiment analysis and machine learning has fuelled the growth of hadoop based data stores like Kudu and adoption of faster databases like MemSQL and Exasol. 2) Big Data is no longer just Hadoop A common misconception is that Big Data and Hadoop are synonymous.

Big Data 40

Big Data Hadoop Data Lake Data Governance 40