Knowledge Hut

SEPTEMBER 29, 2023

By combining data from various structured and unstructured data systems into structures, Microsoft Azure Data Engineers will be able to create analytics solutions. Why Should You Get an Azure Data Engineer Certification? Why Should You Get an Azure Data Engineer Certification?

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Cloudera

AUGUST 21, 2020

CDP is our enterprise data strategy which makes it possible for businesses to leverage complex data workflows, across any different environment and this makes it truly differentiating. This can extend to streaming analytics capabilities into any cloud environment.

Banking 61

Banking Kafka Cloud Storage Government 61

DataKitchen

JANUARY 3, 2022

A robust process hub is expressly designed to enable the data team to minimize the time spent maintaining working analytics and improve and update existing analytics with the least possible effort. Many large enterprises allow consultants and employees to keep tribal knowledge about the data architecture in their heads.

Business Analyst 98

Business Analyst Data Lake Consulting Data Analytics 98

Monte Carlo

MAY 14, 2024

As organizations seek greater value from their data, data architectures are evolving to meet the demand — and table formats are no exception. This development was crucial for enabling both batch and streaming data workflows in dynamic environments, ensuring consistency and durability in big data processing.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Data Engineering Podcast

APRIL 3, 2022

Summary The flexibility of software oriented data workflows is useful for fulfilling complex requirements, but for simple and repetitious use cases it adds significant complexity. In this episode Satish Jayanthi explains how he is building a framework to allow enterprises to move quickly while maintaining guardrails for data workflows.

Data Warehouse 100

Data Warehouse Data Workflow Data Architecture SQL 100

Data Engineering Weekly

JANUARY 15, 2023

. 🎯 I defined the modern data stack sometime back as; @sarahmk125 MDS is a set of vendor tools that solve niche data problems (lineage, orchestration, quality) with the side effect of creating a disjointed data workflow that makes data folks lives more complicated.","username":"ananthdurai","name":"at-ananth-at-data-folks

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Monte Carlo

JUNE 14, 2023

Apache Spark – Labeled as a unified analytics engine for large scale data processing, many leverage this open source solution for streaming use cases, often in conjunction with Databricks. Data orchestration Airflow : Airflow is the most common data orchestrator used by data teams. Now Go Build Some Data Pipelines!

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

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. They mainly belong in the software engineering background or database administration.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98