AltexSoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. What are its limitations and how do the Hadoop ecosystem address them? What is Hadoop.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

ProjectPro

JUNE 6, 2025

The datasets are usually present in Hadoop Distributed File Systems and other databases integrated with the platform. Hive is built on top of Hadoop and provides the measures to read, write, and manage the data. Hive uses HQL, while Spark uses SQL as the language for querying the data.

Hadoop 45

Hadoop Java Big Data Tools SQL 45

ProjectPro

JUNE 6, 2025

The job of data engineers typically is to bring in raw data from different sources and process it for enterprise-grade applications. We will look at the specific roles and responsibilities of a data engineer in more detail but first, let us understand the demand for such jobs in the industries. are prevalent in the industry.

Data Engineer 58

Data Engineer Data Engineering Engineering Amazon Web Services 58

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 Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

AltexSoft

MAY 12, 2023

In today’s data-driven world, organizations amass vast amounts of information that can unlock significant insights and inform decision-making. A staggering 80 percent of this digital treasure trove is unstructured data, which lacks a pre-defined format or organization. What is unstructured data?

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

JUNE 6, 2025

Big data enables businesses to get valuable insights into their products or services. Almost every company employs data models and big data technologies to improve its techniques and marketing campaigns. Most leading companies use big data analytical tools to enhance business decisions and increase revenues.

Big Data 40

Big Data Hadoop Relational Database NoSQL 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

MongoDB stores data in collections of JSON documents in a human-readable format. MongoDB offers several advantageous features to store your data. This data can be accessed and analyzed via several clients supported by MongoDB. Access the project with this source code.

MongoDB 66

MongoDB Coding Project NoSQL 66

ProjectPro

JUNE 6, 2025

Here’s a sneak-peak into what big data leaders and CIO’s predict on the emerging big data trends for 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.

Big Data 40

Big Data Hadoop Data Lake Data Governance 40

ProjectPro

JUNE 6, 2025

Key Features: Along with direct connections to Google Cloud's streaming services like Dataflow, BigQuery includes built-in streaming capabilities that instantly ingest streaming data and make it readily accessible for querying. You can use Dataproc for ETL and modernizing data lakes.

Data Engineer 40

Data Engineer Data Engineering Engineering Google Cloud 40

Cloudera

NOVEMBER 7, 2023

Are you struggling to manage the ever-increasing volume and variety of data in today’s constantly evolving landscape of modern data architectures? Apache Ozone is compatible with Amazon S3 and Hadoop FileSystem protocols and provides bucket layouts that are optimized for both Object Store and File system semantics.

Systems 105

Systems Hadoop Unstructured Data Media 105

ProjectPro

JUNE 6, 2025

Features of Apache Spark Allows Real-Time Stream Processing- Spark can handle and analyze data stored in Hadoop clusters and change data in real time using Spark Streaming. Faster and Mor Efficient processing- Spark apps can run up to 100 times faster in memory and ten times faster in Hadoop clusters.

Data Engineer 45

Data Engineer Data Engineering Engineering Kafka 45

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

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 Engineer Data Engineering Engineering 40

ProjectPro

JUNE 6, 2025

Big data analytics market is expected to be worth $103 billion by 2023. We know that 95% of companies cite managing unstructured data as a business problem. of companies plan to invest in big data and AI. million managers and data analysts with deep knowledge and experience in big data. While 97.2%

Big Data 45

Big Data Big Data Skills Scala Hadoop 45

phData: Data Engineering

NOVEMBER 8, 2024

Hence, the metadata files record schema and partition changes, enabling systems to process data with the correct schema and partition structure for each relevant historical dataset. Data Versioning and Time Travel Open Table Formats empower users with time travel capabilities, allowing them to access previous dataset versions.

Architecture 52

Architecture Systems Data Lake Google Cloud 52

ProjectPro

JUNE 6, 2025

Many organizations are struggling to store, manage, and analyze data due to its exponential growth. Cloud-based data lakes allow organizations to gather any form of data, whether structured or unstructured, and make this data accessible for usage across various applications, to address these issues.

Data Lake 40

Data Lake Hadoop Big Data SQL 40

ProjectPro

JUNE 6, 2025

Key Features of RapidMiner: RapidMiner integrates with your current systems, is easily scalable to meet any demand, can be deployed anywhere, encrypts your data, and gives you complete control over who may access projects. Many developers have access to it due to its integration with Python IDEs like PyCharm.

Big Data Tools 40

Big Data Tools Big Data Hadoop Kafka 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 Engineer 59

Data Engineer Data Engineering Engineering ETL Tools 59

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

A data architect, in turn, understands the business requirements, examines the current data structures, and develops a design for building an integrated framework of easily accessible, safe data aligned with business strategy. Table of Contents What is a Data Architect Role?

Data Architect 40

Data Architect Data Mining Programming Language Java 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 Unstructured Data Machine Learning 40

ProjectPro

JUNE 6, 2025

Volume refers to the amount of data being ingested; Velocity refers to the speed of arrival of data in the pipeline; Variety refers to different types of data, such as structured and unstructured data. Why do you need a Data Ingestion Layer in a Data Engineering Project? AWS Kinesis Image Source d1.awsstatic.com

Data Ingestion 45

Data Ingestion Data Engineer Data Engineering Project 45

ProjectPro

JUNE 6, 2025

Is Snowflake a data lake or data warehouse? Is Hadoop a data lake or data warehouse? The data warehouse layer consists of the relational database management system (RDBMS) that contains the cleaned data and the metadata, which is data about the data.

Data Lake 40

Data Lake Data Warehouse Cloud Hadoop 40

ProjectPro

MAY 26, 2015

In view of the above we have launched Industry Interview Series – where every month we interview someone from the industry to speak on Big Data Hadoop use cases. Table of Contents How IoT leverages Hadoop? ” MobStac is a proximity marketing and analytics platform for beacons.

Hadoop 52

Hadoop Unstructured Data Big Data Retail 52

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 Engineer Data Engineering Engineering 40

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

APRIL 1, 2016

News on Hadoop- March 2016 Hortonworks makes its core more stable for Hadoop users. PCWorld.com Hortonworks is going a step further in making Hadoop more reliable when it comes to enterprise adoption. Hortonworks Data Platform 2.4, Source: [link] ) Syncsort makes Hadoop and Spark available in native Mainframe.

Hadoop 52

Hadoop BI Big Data Big Data Tools 52

ProjectPro

JUNE 6, 2025

In 2024, the data engineering job market is flourishing, with roles like database administrators and architects projected to grow by 8% and salaries averaging $153,000 annually in the US (as per Glassdoor ). These trends underscore the growing demand and significance of data engineering in driving innovation across industries.

Data Engineer 59

Data Engineer Data Engineering Project Engineering 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

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

JUNE 6, 2025

Several big data companies are looking to tame the zettabyte’s of BIG big data with analytics solutions that will help their customers turn it all in meaningful insights. ”- says Rishi Tirumala, Software Engineer at Paxata Paxata is always on the quest to hire top-tier big data talent.

Big Data 40

Big Data Hadoop Business Analyst Data Analytics 40

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

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

ProjectPro

JUNE 6, 2025

Microsoft offers Azure Data Lake, a cloud-based data storage and analytics solution. It is capable of effectively handling enormous amounts of structured and unstructured data. Therefore, it is a popular choice for organizations that need to process and analyze big data files.

Data Lake 40

Data Lake Amazon Web Services Data Warehouse SQL 40

ProjectPro

JUNE 6, 2025

Key Components of Batch Data Pipeline Architecture The batch data pipeline architecture consists of several key components and follows the below typical batch data pipeline workflow across systems - Data Source- This is where your data originates. Data Storage- Processed data needs a destination for storage.

Data Pipeline 40

Data Pipeline Building Retail Data Ingestion 40