ProjectPro

SEPTEMBER 30, 2014

Hadoop’s significance in data warehousing is progressing rapidly as a transitory platform for extract, transform, and load (ETL) processing. Mention about ETL and eyes glaze over Hadoop as a logical platform for data preparation and transformation as it allows them to manage huge volume, variety, and velocity of data flawlessly.

Hadoop 52

Hadoop ETL Tools Unstructured Data ETL System 52

ProjectPro

MARCH 17, 2014

Big data and hadoop are catch-phrases these days in the tech media for describing the storage and processing of huge amounts of data. Over the years, big data has been defined in various ways and there is lots of confusion surrounding the terms big data and hadoop. What is Big Data according to Gartner?

Hadoop 52

Hadoop Big Data Unstructured Data Data Analytics 52

ProjectPro

FEBRUARY 1, 2018

News on Hadoop - Janaury 2018 Apache Hadoop 3.0 The latest update to the 11 year old big data framework Hadoop 3.0 The latest update to the 11 year old big data framework Hadoop 3.0 This new feature of YARN federation in Hadoop 3.0 This new feature of YARN federation in Hadoop 3.0

Hadoop 52

Hadoop Food Healthcare Cloud Computing 52

ProjectPro

JUNE 9, 2015

Big Data Hadoop skills are most sought after as there is no open source framework that can deal with petabytes of data generated by organizations the way hadoop does. 2014 was the year people realized the capability of transforming big data to valuable information and the power of Hadoop in impeding it.

Hadoop 52

Hadoop Big Data Skills Big Data Retail 52

ProjectPro

JUNE 4, 2015

All the components of the Hadoop ecosystem, as explicit entities are evident. All the components of the Hadoop ecosystem, as explicit entities are evident. The holistic view of Hadoop architecture gives prominence to Hadoop common, Hadoop YARN, Hadoop Distributed File Systems (HDFS ) and Hadoop MapReduce of the Hadoop Ecosystem.

Hadoop 52

Hadoop Architecture IT Java 52

Knowledge Hut

DECEMBER 21, 2023

This massive amount of data is referred to as “big data,” which comprises large amounts of data, including structured and unstructured data that has to be processed. To establish a career in big data, you need to be knowledgeable about some concepts, Hadoop being one of them. What is Hadoop?

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

ProjectPro

OCTOBER 28, 2015

Apache Hadoop is synonymous with big data for its cost-effectiveness and its attribute of scalability for processing petabytes of data. Data analysis using hadoop is just half the battle won. Getting data into the Hadoop cluster plays a critical role in any big data deployment.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

ProjectPro

NOVEMBER 14, 2015

Big data has taken over many aspects of our lives and as it continues to grow and expand, big data is creating the need for better and faster data storage and analysis. These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis. Data Migration 2.

Hadoop 52

Hadoop Project Big Data Healthcare 52

ProjectPro

SEPTEMBER 11, 2015

Hadoop has now been around for quite some time. But this question has always been present as to whether it is beneficial to learn Hadoop, the career prospects in this field and what are the pre-requisites to learn Hadoop? By 2018, the Big Data market will be about $46.34 Big Data is not going to go away.

Hadoop 52

Hadoop Java BI Big Data 52

ProjectPro

OCTOBER 15, 2014

Pig and Hive are the two key components of the Hadoop ecosystem. What does pig hadoop or hive hadoop solve? Pig hadoop and Hive hadoop have a similar goal- they are tools that ease the complexity of writing complex java MapReduce programs. Apache HIVE and Apache PIG components of the Hadoop ecosystem are briefed.

Hadoop 52

Hadoop Java Unstructured Data SQL 52

Cloudera

SEPTEMBER 15, 2022

It was designed as a native object store to provide extreme scale, performance, and reliability to handle multiple analytics workloads using either S3 API or the traditional Hadoop API. Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases.

Systems 87

Systems Hadoop Metadata Telecommunication 87

Knowledge Hut

MARCH 7, 2024

Introduction to Big Data Analytics Tools Big data analytics tools refer to a set of techniques and technologies used to collect, process, and analyze large data sets to uncover patterns, trends, and insights. Importance of Big Data Analytics Tools Using Big Data Analytics has a lot of benefits.

Big Data 52

Big Data Data Analytics Data Mining MongoDB 52

ProjectPro

MARCH 15, 2016

Hadoop is beginning to live up to its promise of being the backbone technology for Big Data storage and analytics. Companies across the globe have started to migrate their data into Hadoop to join the stalwarts who already adopted Hadoop a while ago. Hadoop runs on clusters of commodity servers.

Hadoop 40

Hadoop Retail Healthcare Banking 40

ProjectPro

JULY 3, 2015

SAP is all set to ensure that big data market knows its hip to the trend with its new announcement at a conference in San Francisco that it will embrace Hadoop. What follows is an elaborate explanation on how SAP and Hadoop together can bring in novel big data solutions to the enterprise.

Hadoop 40

Hadoop Big Data Data Solutions Unstructured Data 40

ProjectPro

AUGUST 1, 2016

News on Hadoop-July 2016 Driven 2.2 allows enterprises to monitor large scale Hadoop and Spark applications. a leader in Application Performance Monitoring (APM) for big data applications has launched its next version – Driven 2.2. ZDNet.com Hortonworks has come a long way in its 5-year journey as a Hadoop vendor.

Hadoop 40

Hadoop Consulting Big Data Unstructured Data 40

ProjectPro

NOVEMBER 5, 2014

Hadoop is the way to go for organizations that do not want to add load to their primary storage system and want to write distributed jobs that perform well. MongoDB NoSQL database is used in the big data stack for storing and retrieving one item at a time from large datasets whereas Hadoop is used for processing these large data sets.

MongoDB 40

MongoDB Hadoop NoSQL Big Data 40

ProjectPro

SEPTEMBER 14, 2016

A lot of people who wish to learn hadoop have several questions regarding a hadoop developer job role - What are typical tasks for a Hadoop developer? How much java coding is involved in hadoop development job ? What day to day activities does a hadoop developer do? Table of Contents Who is a Hadoop Developer?

Hadoop 40

Hadoop Unstructured Data Java Big Data 40

Knowledge Hut

DECEMBER 26, 2023

Pipeline-centric Pipeline-centric data engineers work with Data Scientists to help use the collected data and mostly belong in midsize companies. Database-centric In bigger organizations, Data engineers mainly focus on data analytics since the data flow in such organizations is huge.

Data Engineering 98

Data Engineering Data Engineer Engineering Hadoop 98

Knowledge Hut

MARCH 27, 2024

The collection of meaningful market data has become a critical component of maintaining consistency in businesses today. A company can make the right decision by organizing a massive amount of raw data with the right data analytic tool and a professional data analyst. What Is Big Data Analytics?

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

ProjectPro

MAY 22, 2015

In our earlier articles we had mentioned how popular Hadoop is becoming and the huge job opportunities that are out there. IT professionals must learn Hadoop online to gain expertise knowledge in Hadoop skills. Prospective Hadoopers can hone their Hadoop skills with intensive research and practice on real time hands-on project.

Hadoop 40

Hadoop Big Data Unstructured Data Education 40

ProjectPro

MAY 19, 2015

It is possible today for organizations to store all the data generated by their business at an affordable price-all thanks to Hadoop, the Sirius star in the cluster of million stars. With Hadoop, even the impossible things look so trivial. So the big question is how is learning Hadoop helpful to you as an individual?

Hadoop 40

Hadoop Big Data NoSQL Database-centric 40

U-Next

MARCH 1, 2023

A solid understanding of relational databases and SQL language is a must-have skill, as an ability to manipulate large amounts of data effectively. A good Data Engineer will also have experience working with NoSQL solutions such as MongoDB or Cassandra, while knowledge of Hadoop or Spark would be beneficial.

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

Knowledge Hut

MAY 3, 2024

Cluster Computing: Efficient processing of data on Set of computers (Refer commodity hardware here) or distributed systems. It’s also called a Parallel Data processing Engine in a few definitions. Spark is utilized for Big data analytics and related processing. Hadoop and Spark can execute on common Resource Manager ( Ex.

Hadoop 98

Hadoop Scala Healthcare Big Data 98

ProjectPro

NOVEMBER 24, 2014

With a rapid pace in evolution of Big Data, its processing frameworks also seem to be evolving in a full swing mode. Hadoop (Hadoop 1.0) has progressed from a more restricted processing model of batch oriented MapReduce jobs to developing specialized and interactive processing models (Hadoop 2.0). to Hadoop 2.0.

Hadoop 40

Hadoop Programming Big Data Unstructured Data 40

ProjectPro

APRIL 2, 2018

News on Hadoop - March 2018 Kyvos Insights to Host Session "BI on Big Data - With Instant Response Times" at the Gartner Data and Analytics Summit 2018.PRNewswire.com, Source : [link] ) The data lake continues to grow deeper and wider in the cloud era.Information-age.com, March 5 , 2018.

Hadoop 40

Hadoop Data Lake Relational Database Big Data 40

ProjectPro

MARCH 23, 2016

And so spawned from this research paper, the big data legend - Hadoop and its capabilities for processing enormous amount of data. Same is the story, of the elephant in the big data room- “Hadoop” Surprised? Yes, Doug Cutting named Hadoop framework after his son’s tiny toy elephant.

Hadoop 40

Hadoop IT Big Data Portfolio 40

DataKitchen

APRIL 13, 2021

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. Amaterasu — is a deployment tool for data pipelines.

Consulting 121

Consulting Machine Learning Data Science Data Pipeline 121

ProjectPro

SEPTEMBER 26, 2014

The toughest challenges in business intelligence today can be addressed by Hadoop through multi-structured data and advanced big data analytics. Big data technologies like Hadoop have become a complement to various conventional BI products and services.

Business Intelligence 40

Business Intelligence Hadoop BI Relational Database 40

Knowledge Hut

DECEMBER 22, 2023

Data analytics, data mining, artificial intelligence, machine learning, deep learning, and other related matters are all included under the collective term "data science" When it comes to data science, it is one of the industries with the fastest growth in terms of income potential and career opportunities.

Hadoop 98

Hadoop Deep Learning Data Science Machine Learning 98

ProjectPro

AUGUST 11, 2016

When people talk about big data analytics and Hadoop, they think about using technologies like Pig, Hive , and Impala as the core tools for data analysis. R and Hadoop combined together prove to be an incomparable data crunching tool for some serious big data analytics for business.

Hadoop 40

Hadoop Big Data R (Programming) Programming Language 40

ProjectPro

MARCH 23, 2015

was intensive and played a significant role in processing large data sets, however it was not an ideal choice for interactive analysis and was constrained for machine learning, graph and memory intensive data analysis algorithms. In one of our previous articles we had discussed about Hadoop 2.0

Hadoop 40

Hadoop Big Data Architecture Kafka 40

ProjectPro

APRIL 11, 2016

Let’s face it; the Hadoop Interview process is a tough cookie to crumble. If you are planning to pursue a job in the big data domain as a Hadoop developer , you should be prepared for both open-ended interview questions and unique technical hadoop interview questions asked by the hiring managers at top tech firms.

Hadoop 40

Hadoop Big Data Java Unstructured Data 40

ProjectPro

FEBRUARY 18, 2016

Apache Hadoop, an open source framework is used widely for processing gigantic amounts of unstructured data on commodity hardware. Four core modules form the Hadoop Ecosystem : Hadoop Common, HDFS, YARN and MapReduce. Apache Zookeeper and Oozie are the Hadoop admin tools used for this purpose.

Hadoop 40

Hadoop Management Java Metadata 40

ProjectPro

JANUARY 27, 2016

Installing Hadoop cluster in production is just half the battle won. It is extremely important for a Hadoop admin to tune the Hadoop cluster setup to gain maximum performance. During Hadoop installation , the cluster is configured with default configuration settings which are on par with the minimal hardware configuration.

Hadoop 40

Hadoop Big Data Unstructured Data Portfolio 40

Cloudera

AUGUST 21, 2020

Perhaps one of the most significant contributions in data technology advancement has been the advent of “Big Data” platforms. Historically these highly specialized platforms were deployed on-prem in private data centers to ensure greater control , security, and compliance. Streaming data analytics. .

Hadoop 76

Hadoop Big Data Cloud Kafka 76

ProjectPro

AUGUST 21, 2015

With the help of ProjectPro’s Hadoop Instructors, we have put together a detailed list of big data Hadoop interview questions based on the different components of the Hadoop Ecosystem such as MapReduce, Hive, HBase, Pig, YARN, Flume, Sqoop , HDFS, etc. What is the difference between Hadoop and Traditional RDBMS?

Hadoop 40

Hadoop Big Data Metadata Java 40

ProjectPro

NOVEMBER 11, 2014

Confused over which framework to choose for big data processing - Hadoop MapReduce vs. Apache Spark. This blog helps you understand the critical differences between two popular big data frameworks. Hadoop and Spark are popular apache projects in the big data ecosystem.

Hadoop 40

Hadoop Machine Learning Scala Big Data 40