Striim

MARCH 21, 2025

With instant elasticity, high-performance, and secure data sharing across multiple clouds , Snowflake has become highly in-demand for its cloud-based data warehouse offering. As organizations adopt Snowflake for business-critical workloads, they also need to look for a modern data integration approach.

Data Warehouse 52

Data Warehouse MongoDB MySQL Hadoop 52

Data Engineering Podcast

FEBRUARY 19, 2023

TimeXtender takes a holistic approach to data integration that focuses on agility rather than fragmentation. By bringing all the layers of the data stack together, TimeXtender helps you build data solutions up to 10 times faster and saves you 70-80% on costs. But don't worry, there is a better way.

IT 147

IT Data Lake Metadata Data Warehouse 147

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

NOVEMBER 6, 2015

Hadoop has continued to grow and develop ever since it was introduced in the market 10 years ago. Every new release and abstraction on Hadoop is used to improve one or the other drawback in data processing, storage and analysis. Apache Hive is an abstraction on Hadoop MapReduce and has its own SQL like language HiveQL.

Hadoop 52

Hadoop SQL Java Metadata 52

Data Engineering Podcast

AUGUST 19, 2019

Summary Managing big data projects at scale is a perennial problem, with a wide variety of solutions that have evolved over the past 20 years. One of the early entrants that predates Hadoop and has since been open sourced is the HPCC (High Performance Computing Cluster) system.

Big Data 100

Big Data Hadoop Data Lake Media 100

ProjectPro

MAY 12, 2016

Big Data has found a comfortable home inside the Hadoop ecosystem. Hadoop based data stores have gained wide acceptance around the world by developers, programmers, data scientists, and database experts. Explore SQL Database Projects to Add them to Your Data Engineer Resume.

Hadoop 40

Hadoop SQL Business Intelligence Java 40

phData: Data Engineering

NOVEMBER 8, 2024

Evolution of Open Table Formats Here’s a timeline that outlines the key moments in the evolution of open table formats: 2008 - Apache Hive and Hive Table Format Facebook introduced Apache Hive as one of the first table formats as part of its data warehousing infrastructure, built on top of Hadoop.

Architecture 52

Architecture Systems Data Lake Google Cloud 52

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. Big data, multi-structured data, and advanced analytics.

Business Intelligence 40

Business Intelligence Hadoop BI Relational Database 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 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

Maxime Beauchemin

JANUARY 20, 2017

In relation to previously existing roles , the data engineering field could be thought of as a superset of business intelligence and data warehousing that brings more elements from software engineering. This includes tasks like setting up and operating platforms like Hadoop/Hive/HBase, Spark, and the like.

Data Engineer 130

Data Engineer Data Engineering Engineering ETL Tools 130

Snowflake

OCTOBER 16, 2024

Many of our customers — from Marriott to AT&T — start their journey with the Snowflake AI Data Cloud by migrating their data warehousing workloads to the platform. Snowflake's separate clusters for ETL, reporting and data science eliminated resource contention.

Digital Media 105

Digital Media Media Data Lake Data Warehouse 105

Data Engineering Podcast

JULY 15, 2018

What mechanisms are available to ensure data integrity across the cluster? Contact Info Email @liewegas on Twitter liewegas on GitHub Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? What mechanisms are available to ensure data integrity across the cluster?

Hadoop 100

Hadoop Data Engineer Data Engineering Coding 100

Data Engineering Podcast

JULY 22, 2019

One of the intended benefits of data lakes is the idea that data integration becomes easier by having everything in one place. How do you approach the challenge of data integration in a domain oriented approach, particularly as it applies to aspects such as data freshness, semantic consistency, and schema evolution?

Data Lake 100

Data Lake Hadoop Data Architecture 100

Data Engineering Podcast

JANUARY 1, 2022

In the data domain, we have seen a number of bottlenecks, for example, scaling data platforms, the answer to which was Hadoop and on-prem columnar stores and then cloud data warehouses such as Snowflake & BigQuery.

Data Warehouse 100

Data Warehouse Hadoop SQL Data Lake 100

Data Engineering Podcast

JANUARY 30, 2022

If you’re a data engineering podcast listener, you get credits worth $3000 on an annual subscription StreamSets DataOps Platform is the world’s first single platform for building smart data pipelines across hybrid and multi-cloud architectures.

Data Engineer 100

Data Engineer Data Engineering Engineering Data Pipeline 100

Snowflake

JULY 22, 2024

LTIMindtree’s PolarSled Accelerator helps migrate existing legacy systems, such as SAP, Teradata and Hadoop, to Snowflake. Snowflake governance capabilities help you uphold and enforce data integrity, compliance and security policies.

Government 119

Government Data Cloud Hadoop 119

Christophe Blefari

APRIL 8, 2023

I did not care about data modeling for years. I was in the Hadoop world and all I was doing was denormalisation. Microsoft data integration new capabilities — Few months ago I've entered the Azure world. Denormalisation everywhere. The machine learning is mainly in Python and uses PyTorch.

Pipeline-centric 130

Pipeline-centric Database-centric Algorithm Data 130

Christophe Blefari

APRIL 8, 2023

I did not care about data modeling for years. I was in the Hadoop world and all I was doing was denormalisation. Microsoft data integration new capabilities — Few months ago I've entered the Azure world. Denormalisation everywhere. The machine learning is mainly in Python and uses PyTorch.

Pipeline-centric 130

Pipeline-centric Database-centric Algorithm Data 130

Data Engineering Podcast

MARCH 22, 2021

What are the factors that you need to consider when deciding whether to implement a CDC system for a given data integration? How does CDC fit into a broader data platform, particularly where there are likely to be other data integration pipelines in operation? What are the barriers to entry?

Data Warehouse 100

Data Warehouse Metadata Hadoop Data Lake 100

Precisely

MARCH 9, 2023

As cloud computing platforms make it possible to perform advanced analytics on ever larger and more diverse data sets, new and innovative approaches have emerged for storing, preprocessing, and analyzing information. Hadoop, Snowflake, Databricks and other products have rapidly gained adoption. They can be changed, but not easily.

Data Lake 59

Data Lake Data Warehouse Hadoop Raw Data 59

Data Engineering Podcast

SEPTEMBER 7, 2020

For analytical use cases you often want to combine data across multiple sources and storage locations. This frequently requires cumbersome and time-consuming data integration. For analytical use cases you often want to combine data across multiple sources and storage locations.

Architecture 100

Architecture Data Architecture SQL Engineering 100

Data Engineering Podcast

FEBRUARY 13, 2022

How would you characterize the position of Rudderstack in the current data ecosystem? How do you think about the application of Rudderstack compared to tools for data integration (e.g. How would you characterize the position of Rudderstack in the current data ecosystem? Singer, Stitch, Fivetran) and reverse ETL (e.g.

Building 100

Building Hadoop Data Pipeline Metadata 100

AltexSoft

MAY 14, 2021

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. As you can see, the Hadoop ecosystem consists of many components. Source: phoenixNAP. NoSQL databases. Apache Kafka.

Big Data 78

Big Data Data Analytics IT NoSQL 78

AltexSoft

OCTOBER 21, 2022

process data in real time and run streaming analytics. In other words, Kafka can serve as a messaging system, commit log, data integration tool, and stream processing platform. cloud data warehouses — for example, Snowflake , Google BigQuery, and Amazon Redshift. Cloudera , focusing on Big Data analytics.

Kafka 93

Kafka Hadoop Big Data ETL Tools 93

Data Engineering Weekly

MAY 26, 2024

[link] Tweeq: Tweeq Data Platform: Journey and Lessons Learned: Clickhouse, dbt, Dagster, and Superset Tweeq writes about its journey of building a data platform with cloud-agnostic open-source solutions and some integration challenges. It is refreshing to see an open stack after the Hadoop era.

Data Engineer 77

Data Engineer Data Engineering Engineering Google Cloud 77

AltexSoft

OCTOBER 30, 2021

Data scientists use different programming tools to extract data, build models, and create visualizations. Expected to be somewhat versed in data engineering, they are familiar with SQL, Hadoop, and Apache Spark. An overview of data engineer skills. Data warehousing. Machine learning techniques. Programming.

Data Engineer 98

Data Engineer Data Engineering Engineering Machine Learning 98

Cloudera

NOVEMBER 22, 2021

Rise in polyglot data movement because of the explosion in data availability and the increased need for complex data transformations (due to, e.g., different data formats used by different processing frameworks or proprietary applications). As a result, alternative data integration technologies (e.g.,

Hadoop 94

Hadoop Government Data Security Cloud 94

Christophe Blefari

DECEMBER 23, 2022

Original deep post that are exclusive to Data News members are something I'm willing to do more next year, to bring you additional value to this newsletter. In order to have it you'll have to activate Data Catalog/Dataplex. Let's go back to dbt. This is in public preview.

Data 100

Data Hadoop Data Engineer Data Engineering 100

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 120

Consulting Machine Learning Data Science Data Pipeline 120

Monte Carlo

MAY 28, 2024

Batch Processing Tools For batch processing, tools like Apache Hadoop and Spark are widely used. Hadoop handles large-scale data storage and processing, while Spark offers fast in-memory computing capabilities for further processing. Our promise: we will show you the product.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

Data Engineering Weekly

AUGUST 11, 2024

link] Uber: Enabling Security for Hadoop Data Lake on Google Cloud Storage Uber writes about securing a Hadoop-based data lake on Google Cloud Platform (GCP) by replacing HDFS with Google Cloud Storage (GCS) while maintaining existing security models like Kerberos-based authentication.

Data Engineer 58

Data Engineer Data Engineering Google Cloud Engineering 58

Knowledge Hut

APRIL 25, 2023

Data modeling: Data engineers should be able to design and develop data models that help represent complex data structures effectively. Data processing: Data engineers should know data processing frameworks like Apache Spark, Hadoop, or Kafka, which help process and analyze data at scale.

Data Engineer 52

Data Engineer Data Engineering Engineering Google Cloud 52

Knowledge Hut

DECEMBER 27, 2023

No doubt companies are investing in big data and as a career, it has huge potential. Many business owners and professionals are interested in harnessing the power locked in Big Data using Hadoop often pursue Big Data and Hadoop Training. What is Big Data? We are discussing here the top big data tools: 1.

Big Data Tools 59

Big Data Tools Big Data Hadoop Database-centric 59

Knowledge Hut

MARCH 7, 2024

Data analytics tools in big data includes a variety of tools that can be used to enhance the data analysis process. These tools include data analysis, data purification, data mining, data visualization, data integration, data storage, and management. Integrate.io - Integrate.io

Big Data 52

Big Data Data Analytics Data Mining MongoDB 52

ProjectPro

JANUARY 31, 2023

Typically, data processing is done using frameworks such as Hadoop, Spark, MapReduce, Flink, and Pig, to mention a few. How is Hadoop related to Big Data? Explain the difference between Hadoop and RDBMS. Data Variety Hadoop stores structured, semi-structured and unstructured data.

Big Data 52

Big Data Hadoop Relational Database AWS 52

Knowledge Hut

APRIL 23, 2024

The key characteristics of big data are commonly described as the three V's: volume (large datasets), velocity (high-speed data ingestion), and variety (data in different formats). Unlike big data warehouse, big data focuses on processing and analyzing data in its raw and unstructured form.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52