Knowledge Hut

MAY 2, 2024

Why We Need Big Data Frameworks Big data is primarily defined by the volume of a data set. Big data sets are generally huge – measuring tens of terabytes – and sometimes crossing the threshold of petabytes. It is surprising to know how much data is generated every minute. billion (2019 – 2022).

Scala 94

Scala Hadoop Datasets Java 94

ProjectPro

JULY 23, 2021

Sentiment Analysis on Real-time Twitter Data 23. AWS Athena Big Data Project for Querying COVID-19 Data 25. Build an AWS ETL Data Pipeline in Python on YouTube Data 26. Build a Job Winning Data Engineer Portfolio with Solved End-to-End Big Data Projects. Hybrid Recommendation System 21.

AWS 52

AWS Project Amazon Web Services Cloud Computing 52

AltexSoft

JULY 18, 2023

These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Maintained by the Apache Software Foundation, Apache Spark is an open-source, unified engine designed for large-scale data analytics. Big data processing.

Big Data 52

Big Data Data Process Process Hadoop 52

ProjectPro

FEBRUARY 10, 2016

It is difficult to believe that the first Hadoop cluster was put into production at Yahoo, 10 years ago, on January 28 th , 2006. Ten years ago nobody was aware that an open source technology, like Apache Hadoop will fire a revolution in the world of big data. Happy Birthday Hadoop With more than 1.7

Hadoop 40

Hadoop Big Data Programming SQL 40

AltexSoft

MAY 14, 2021

Big Data enjoys the hype around it and for a reason. But the understanding of the essence of Big Data and ways to analyze it is still blurred. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics. Key Big Data characteristics.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Knowledge Hut

NOVEMBER 17, 2023

In 2006, Amazon launched AWS to handle its online retail operations. Analytics Another essential tool being offered by Amazon for a data scientist is- Amazon Athena is a query service for analyzing the data in Amazon S3 or Glacier. Amazon Kinesis aggregates and processes the streaming data in real time.

AWS 52

AWS Data Science Certification Amazon Web Services 52

ProjectPro

AUGUST 26, 2015

"Big data is at the foundation of all of the megatrends that are happening today, from social to mobile to the cloud to gaming."- ”- Atul Butte, Stanford With the big data hype all around, it is the fuel of the 21 st century that is driving all that we do. .”- said Chris Lynch, the ex CEO of Vertica.

Big Data 40

Big Data Unstructured Data Hadoop NoSQL 40

ProjectPro

NOVEMBER 7, 2016

Understanding the Hadoop architecture now gets easier! This blog will give you an indepth insight into the architecture of hadoop and its major components- HDFS, YARN, and MapReduce. We will also look at how each component in the Hadoop ecosystem plays a significant role in making Hadoop efficient for big data processing.

Hadoop 40

Hadoop Architecture IT Big Data 40

Cloudera

OCTOBER 3, 2018

First, remember the history of Apache Hadoop. Google built an innovative scale-out platform for data storage and analysis in the late 1990s and early 2000s, and published research papers about their work. The two of them started the Hadoop project to build an open-source implementation of Google’s system.

Hadoop 75

Hadoop Cloud Data Storage Big Data 75

Knowledge Hut

NOVEMBER 2, 2023

In 2006, Amazon launched AWS from its internal infrastructure that was used for handling online retail operations. For Big data Amazon Elastic MapReduce is responsible for processing a large amount of data through the Hadoop framework. For processing and analyzing streaming data, you can use Amazon Kinesis.

Amazon Web Services 52

Amazon Web Services AWS IT Transportation 52

ProjectPro

AUGUST 31, 2018

For big data, EBS storage is incredibly fast. Big data poses challenges for standard storage, demanding the use of premium storage. For big data, much more advanced cloud infrastructure is required. Although Azure's services are less developed for big data, they are improving.

AWS 45

AWS Cloud Amazon Web Services Cloud Computing 45

ProjectPro

JANUARY 24, 2023

The three essential functions of combining Google Analytics and BigQuery include- 1) Data Manipulation BigQuery allows for data manipulation and transformation, such as filtering, joins, and aggregations, which helps to prepare the data for analysis and visualization. While a field name is optional, the type must be specified.

Bytes 52

Bytes Google Cloud Data Warehouse Datasets 52

ProjectPro

SEPTEMBER 6, 2021

On the other hand, GCP Dataflow is a fully managed data processing service for batch and streaming big data processing. Dataflow allows a streaming data pipeline to be developed fast and with lower data latency. Learn more about real-world big data applications with unique examples of big data projects.

AWS 52

AWS Amazon Web Services Google Cloud Cloud Storage 52