ProjectPro

JUNE 6, 2025

Let's delve deeper into the essential responsibilities and skills of a Big Data Developer: Develop and Maintain Data Pipelines using ETL Processes Big Data Developers are responsible for designing and building data pipelines that extract, transform, and load (ETL) data from various sources into the Big Data ecosystem.

Big Data 40

Big Data Hadoop Scala NoSQL 40

ProjectPro

JUNE 6, 2025

Source Code: Build a Similar Image Finder Top 3 Open Source Big Data Tools This section consists of three leading open-source big data tools- Apache Spark , Apache Hadoop, and Apache Kafka. In Hadoop clusters , Spark apps can operate up to 10 times faster on disk. Hadoop, created by Doug Cutting and Michael J.

Big Data Tools 40

Big Data Tools Big Data Hadoop Kafka 40

ProjectPro

JUNE 6, 2025

Data Lake Architecture- Core Foundations How To Build a Data Lake From Scratch-A Step-by-Step Guide Tips on Building a Data Lake by Top Industry Experts Building a Data Lake on Specific Platforms How to Build a Data Lake on AWS? How to Build a Data Lake on Azure? How to Build a Data Lake on Hadoop?

Data Lake 40

Data Lake Building Hadoop Raw Data 40

ProjectPro

JUNE 6, 2025

Azure Data Lake provides seamless integration and is the best answer to the productivity and scalability issues businesses face now. Azure Data Lake is a huge central storage repository powered by Apache Hadoop and built on YARN and HDFS. It can effectively store organized, semi-structured, and unstructured data.

Data Lake 40

Data Lake Hadoop Big Data SQL 40

ProjectPro

JUNE 6, 2025

Data Collection The first step is to collect real-time data (purchase_data) from various sources, such as sensors, IoT devices, and web applications, using data collectors or agents. These collectors send the data to a central location, typically a message broker like Kafka.

Data Ingestion 40

Data Ingestion Kafka Google Cloud AWS 40

ProjectPro

JUNE 6, 2025

In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The structured data comprises data that can be saved and retrieved in a fixed format, like email addresses, locations, or phone numbers. However, it is not straightforward to create data pipelines.

Data Pipeline 40

Data Pipeline Architecture Kafka Data Lake 40

ProjectPro

JUNE 6, 2025

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

JUNE 6, 2025

Apache Hadoop Hadoop is an open-source framework that helps create programming models for massive data volumes across multiple clusters of machines. Hadoop helps data scientists in data exploration and storage by identifying the complexities in the data.

Data Science 40

Data Science Hadoop Machine Learning Unstructured Data 40

ProjectPro

JUNE 6, 2025

NoSQL databases are the new-age solutions to distributed unstructured data storage and processing. The speed, scalability, and fail-over safety offered by NoSQL databases are needed in the current times in the wake of Big Data Analytics and Data Science technologies.

NoSQL 40

NoSQL Database Hadoop Big Data 40

ProjectPro

JUNE 6, 2025

Decide the process of Data Extraction and transformation, either ELT or ETL (Our Next Blog) Transforming and cleaning data to improve data reliability and usage ability for other teams from Data Science or Data Analysis. Dealing With different data types like structured, semi-structured, and unstructured data.

Data Science 40

Data Science Data Engineering Data Engineer Engineering 40

ProjectPro

JUNE 6, 2025

Automated tools are developed as part of the Big Data technology to handle the massive volumes of varied data sets. Big Data Engineers are professionals who handle large volumes of structured and unstructured data effectively. You will get to learn about data storage and management with lessons on Big Data tools.

Big Data 40

Big Data Data Engineering Data Engineer Engineering 40

ProjectPro

JUNE 6, 2025

Big Data Data engineers must focus on managing data lakes, processing large amounts of big data, and creating extensive data integration pipelines. These tasks require them to work with big data tools like the Hadoop ecosystem and related tools like PySpark , Spark, and Hive.

Data Engineering 59

Data Engineering Data Engineer Engineering ETL Tools 59

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

ProjectPro

JUNE 6, 2025

Is Snowflake a data lake or data warehouse? Is Hadoop a data lake or data warehouse? Storage Layer: This is a centralized repository where all the data loaded into the data lake is stored. The storage layer can be considered a landing zone for all the data that is to be stored in the data lake.

Data Lake 40

Data Lake Data Warehouse Cloud Hadoop 40

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 IBM?

Hadoop 52

Hadoop Big Data Unstructured Data Retail 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

Knowledge Hut

DECEMBER 26, 2023

Analyzing and organizing raw data Raw data is unstructured data consisting of texts, images, audio, and videos such as PDFs and voice transcripts. The job of a data engineer is to develop models using machine learning to scan, label and organize this unstructured data.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

ProjectPro

JUNE 6, 2025

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 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

JUNE 6, 2025

ETL works best when there is a mismatch in supported data types between the source and destination. You want to store all structured and unstructured data in your organization, irrespective of the size. You can use Azure Data Factory to build and manage data-driven workflows or pipelines that can input data from many sources.

Data Engineering 40

Data Engineering Data Engineer Engineering Data Lake 40

ProjectPro

JUNE 6, 2025

Microsoft introduced the Data Engineering on Microsoft Azure DP 203 certification exam in June 2021 to replace the earlier two exams. This professional certificate demonstrates one's abilities to integrate, analyze, and transform various structured and unstructured data for creating effective data analytics solutions.

Certification 40

Certification Data Engineering Data Engineer Engineering 40

Knowledge Hut

MAY 3, 2024

Before getting into Big data, you must have minimum knowledge on: Anyone of the programming languages >> Core Python or Scala. Spark installations can be done on any platform but its framework is similar to Hadoop and hence having knowledge of HDFS and YARN is highly recommended. Basic knowledge of SQL. Yarn etc) Or, 2.

Scala 98

Scala Hadoop Healthcare Big Data 98

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

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. But the “elephant in the room” is NOT ‘Hadoop’.

Hadoop 76

Hadoop Big Data Cloud Kafka 76

AltexSoft

MAY 14, 2021

It’s worth noting though that data collection commonly happens in real-time or near real-time to ensure immediate processing. Apache Hadoop. Apache Hadoop is a set of open-source software for storing, processing, and managing Big Data developed by the Apache Software Foundation in 2006. Hadoop architecture layers.

Big Data 78

Big Data Data Analytics IT NoSQL 78

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 Kafka Architecture 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 Java Big Data Unstructured Data 40

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

DataKitchen

APRIL 13, 2021

Airflow — An open-source platform to programmatically author, schedule, and monitor data pipelines. Apache Oozie — An open-source workflow scheduler system to manage Apache Hadoop jobs. DBT (Data Build Tool) — A command-line tool that enables data analysts and engineers to transform data in their warehouse more effectively.

Consulting 121

Consulting Machine Learning Government Data Science 121

ProjectPro

JUNE 6, 2025

Map-reduce - Map-reduce enables users to use resizable Hadoop clusters within Amazon infrastructure. Amazon’s counterpart of this is called Amazon EMR ( Elastic Map-Reduce) Hadoop - Hadoop allows clustering of hardware to analyse large sets of data in parallel. Blob storage provides storing of unstructured data.

Cloud Computing 53

Cloud Computing Cloud Amazon Web Services AWS 53

AltexSoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data Architect 87

Data Architect Certification Generalist Big Data 87

ProjectPro

JUNE 6, 2025

Data Loading: The transformed data is loaded into a data warehouse or data lake, depending on the architecture of your data ecosystem. Data warehouses are optimized for querying and are usually structured, while data lakes can handle structured and unstructured data.

Python 40

Python ETL Tools Data Warehouse Programming Language 40

Monte Carlo

MAY 28, 2024

Popular Data Ingestion Tools Choosing the right ingestion technology is key to a successful architecture. Common Tools Data Sources Identification with Apache NiFi : Automates data flow, handling structured and unstructured data. Used for identifying and cataloging data sources.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

Cloudera

SEPTEMBER 9, 2020

jar' | sort | tr 'n' ':' | head -c -1) export myJVMOptions="-DmaxConnectionsPerHost=10000 -DmaxConnections=10000 -Djava.io.tmpdir=/tmp/dir/ " export myResourcesDir=" <RESOURCE_DIR> " export HADOOP_CONF_DIR="/etc/hadoop/conf" spark-submit. -name '*-sources.jar') export myDependencyJarFiles=$(find $myDependencyJarDir -name '*.jar'

AWS 84

AWS Data Unstructured Data Hadoop 84

Knowledge Hut

NOVEMBER 28, 2023

With a plethora of new technology tools on the market, data engineers should update their skill set with continuous learning and data engineer certification programs. What do Data Engineers Do? Concepts of IaaS, PaaS, and SaaS are the trend, and big companies expect data engineers to have the relevant knowledge.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Silectis

JANUARY 3, 2021

BI (Business Intelligence) Strategies and systems used by enterprises to conduct data analysis and make pertinent business decisions. Big Data Large volumes of structured or unstructured data. Big Query Google’s cloud data warehouse. Data Visualization Graphic representation of a set or sets of data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

JUNE 6, 2025

Ace your Big Data engineer interview by working on unique end-to-end solved Big Data Projects using Hadoop Amazon Redshift Project Ideas for Practice PySpark Project - Build an AWS Data Pipeline using Kafka and Redshift. This acceleration contributed to better decision-making and game optimization.

AWS 40

AWS Database Amazon Web Services MySQL 40