Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. Hadoop Platform Hadoop is an open-source software library created by the Apache Software Foundation.

Data Engineer 98

Data Engineer Data Engineering Engineering Hadoop 98

Snowflake

JULY 22, 2024

LTIMindtree’s PolarSled Accelerator helps migrate existing legacy systems, such as SAP, Teradata and Hadoop, to Snowflake. Additional processing capability with SQL, as well as Snowflake capabilities like Stored Procedures, Snowpark , and Streams and Tasks, help streamline operations.

Government 119

Government Data Cloud Hadoop 119

Data Engineering Weekly

DECEMBER 29, 2022

Data catalogs are the most expensive data integration systems you never intended to build. Data Catalog as a passive web portal to display metadata requires significant rethinking to adopt modern data workflow, not just adding “modern” in its prefix. How happy are you with your data catalogs?

Metadata 64

Metadata Data Warehouse ETL Tools Data Workflow 64

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

Databand.ai

AUGUST 30, 2023

Data Orchestration Data orchestration refers to the coordination and management of data workflows, from data ingestion to data processing and analysis. DataOps tools should offer powerful data orchestration capabilities, allowing organizations to build, schedule, and monitor data workflows with ease.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Monte Carlo

MAY 14, 2024

The “legacy” table formats The data landscape has evolved so quickly that table formats pioneered within the last 25 years are already achieving “legacy” status. It was designed to support high-volume data exchange and compatibility across different system versions, which is essential for streaming architectures such as Apache Kafka.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

AltexSoft

MARCH 14, 2023

Data orchestration involves managing the scheduling and execution of data workflows. As for this part, Apache Airflow is a popular open-source platform choice used for data orchestration across the entire data pipeline. A simplified diagram shows the major components of Airbnb’s data infrastructure stack.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Knowledge Hut

NOVEMBER 2, 2023

Data Aggregation Working with a sample of big data allows you to investigate real-time data processing, big data project design, and data flow. Learn how to aggregate real-time data using several big data tools like Kafka, Zookeeper, Spark, HBase, and Hadoop.

Data Engineer 52

Data Engineer Data Engineering Project Coding 52

Knowledge Hut

MAY 23, 2024

Users can also leverage it for generating interactive visualizations over data. It also comes with lots of automation techniques that qualify users to eliminate manual data workflows. It can analyze data in real-time and can perform cluster management. It is much faster than other analytic workload tools like Hadoop.

Data Science 52

Data Science MongoDB Programming Language Hadoop 52

Monte Carlo

JULY 27, 2023

Data quality engineers also need to have experience operating in cloud environments and using many of the modern data stack tools that are utilized in building and maintaining data pipelines. 78% of job postings referenced at least part of their environment was in a modern data warehouse, lake, or lakehouse.

Engineering 52

Engineering Healthcare Data Warehouse Scala 52

Monte Carlo

NOVEMBER 14, 2023

But even as the modern data stack continues to evolve, Airflow maintains its title as a perennial data orchestration favorite—and for good reason. Luigi’s strength lies in its ability to stitch together a variety of seemingly disparate tasks, be it a Hadoop job, a Hive query, or even a local data dump.

Pipeline-centric 40

Pipeline-centric Google Cloud Python Data Workflow 40

Knowledge Hut

SEPTEMBER 29, 2023

Why Should You Get an Azure Data Engineer Certification? Becoming an Azure data engineer allows you to seamlessly blend the roles of a data analyst and a data scientist. One of the pivotal responsibilities is managing data workflows and pipelines, a core aspect of a data engineer's role.

Certification 52

Certification Data Engineer Data Engineering Engineering 52

Knowledge Hut

MARCH 28, 2024

Role Level: Intermediate Responsibilities Design and develop big data solutions using Azure services like Azure HDInsight, Azure Databricks, and Azure Data Lake Storage. Implement data ingestion, processing, and analysis pipelines for large-scale data sets.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Warehouse 52

AltexSoft

SEPTEMBER 21, 2023

The Elastic Stacks Elasticsearch is integral within analytics stacks, collaborating seamlessly with other tools developed by Elastic to manage the entire data workflow — from ingestion to visualization. Accessible via a unified API, these new features enhance search relevance and are available on Elastic Cloud.

Engineering 52

Engineering NoSQL Programming Language Java 52

Monte Carlo

JUNE 14, 2023

5 Data pipeline architecture designs and their evolution The Hadoop era , roughly 2011 to 2017, arguably ushered in big data processing capabilities to mainstream organizations. Data then, and even today for some organizations, was primarily hosted in on-premises databases with non-scalable storage.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

ProjectPro

DECEMBER 21, 2021

This includes knowledge of data structures (such as stack, queue, tree, etc.), A Machine Learning professional needs to have a solid grasp on at least one programming language such as Python, C/C++, R, Java, Spark, Hadoop, etc. Machine Learning engineers are often required to collaborate with data engineers to build data workflows.

Machine Learning 52

Machine Learning Engineering Algorithm Data Science 52

phData: Data Engineering

JANUARY 3, 2022

phData Cloud Foundation is dedicated to machine learning and data analytics, with prebuilt stacks for a range of analytical tools, including AWS EMR, Airflow, AWS Redshift, AWS DMS, Snowflake, Databricks, Cloudera Hadoop, and more. This helps drive requirements and determines the right validation at the right time for the data.

IT 52

IT AWS Software Engineer Software Engineering 52

Christophe Blefari

SEPTEMBER 28, 2023

The era of Big Data was characterised by Hadoop, HDFS, distributed computing (Spark), above the JVM. That's why big data technologies got swooshed by the modern data stack when it arrived on the market—excepting Spark. We need to store, process and visualise data, everything else is just marketing.

Big Data 147

Big Data Cloud Storage Hadoop SQL 147

AltexSoft

NOVEMBER 7, 2022

DevOps tasks — for example, creating scheduled backups and restoring data from them. Airflow is especially useful for orchestrating Big Data workflows. Airflow is not a data processing tool by itself but rather an instrument to manage multiple components of data processing. When Airflow won’t work.

PostgreSQL 52

PostgreSQL Metadata Python MySQL 52