Data Engineering Podcast

JANUARY 7, 2024

Summary Data processing technologies have dramatically improved in their sophistication and raw throughput. Unfortunately, the volumes of data that are being generated continue to double, requiring further advancements in the platform capabilities to keep up. What do you have planned for the future of your academic research?

Data Process 147

Data Process Process Data Lake High Quality Data 147

Knowledge Hut

DECEMBER 28, 2023

Today, organizations seek skilled professionals who can harness data’s power to drive informed decisions. As technology evolves, cloud platforms have emerged as the cornerstone of modern data management. Its comprehensive suite of services can handle data at scale. What is the Azure Data Engineer Certification?

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Knowledge Hut

MARCH 28, 2024

Data Engineer Career: Overview Currently, with the enormous growth in the volume, variety, and veracity of data generated and the will of large firms to store and analyze their data, data management is a critical aspect of data science. That’s where data engineers are on the go.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Knowledge Hut

NOVEMBER 17, 2023

The demand for qualified experts who can make use of Azure's data capabilities, eventually promoting organizational efficiency, innovation, and informed decision-making through efficient data management and analytics, is what motivates employers to hire Azure Data Engineers. Why Do Companies Hire Azure Data Engineers?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Knowledge Hut

SEPTEMBER 29, 2023

Microsoft Data Engineer Certification is one such certification which is most sought after by professionals. By combining data from various structured and unstructured data systems into structures, Microsoft Azure Data Engineers will be able to create analytics solutions.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Data Engineering Podcast

JUNE 9, 2024

Summary Streaming data processing enables new categories of data products and analytics. Unfortunately, reasoning about stream processing engines is complex and lacks sufficient tooling. Data lakes are notoriously complex. My thanks to the team at Code Comments for their support.

Process 147

Process Data Lake High Quality Data Machine Learning 147

Databand.ai

AUGUST 30, 2023

DataOps , short for data operations, is an emerging discipline that focuses on improving the collaboration, integration, and automation of data processes across an organization. Accelerated Data Analytics DataOps tools help automate and streamline various data processes, leading to faster and more efficient data analytics.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Ascend.io

DECEMBER 11, 2023

Data orchestration is the process of efficiently coordinating the movement and processing of data across multiple, disparate systems and services within a company. It automates and optimizes data processes, reducing manual effort and the likelihood of errors. What formats does your data exist in?

Data Workflow 52

Data Workflow Data Pipeline Data Lake Data 52

Monte Carlo

MAY 14, 2024

Apache ORC (Optimized Row Columnar) : In 2013, ORC was developed for the Hadoop ecosystem to improve the efficiency of data storage and retrieval. 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

Databand.ai

AUGUST 30, 2023

These experts will need to combine their expertise in data processing, storage, transformation, modeling, visualization, and machine learning algorithms, working together on a unified platform or toolset. The post Unified DataOps: Components, Challenges, and How to Get Started appeared first on Databand.

Data Governance 40

Data Governance Data Cleanse Government Data Pipeline 40

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. Python: Python is, by far, the most widely used data science programming language. Big Data Tools 23.

Data Science 52

Data Science MongoDB Programming Language Hadoop 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. Prefect’s control panel also offers scheduling, automatic retries, and instant alerting, ensuring you always have a clear view of your data processes.

Pipeline-centric 40

Pipeline-centric Google Cloud Data Workflow Python 40

Meltano

OCTOBER 5, 2022

In the same way, a DataOps engineer designs the data assembly line that enables data scientists to derive insights from data analytics faster and with fewer errors. DataOps engineers improve the speed and quality of the data development process by applying DevOps principles to data workflow, known as DataOps.

Engineering 52

Engineering Raw Data Data Pipeline ETL Tools 52

DataKitchen

APRIL 13, 2021

Composable Analytics — A DataOps Enterprise Platform with built-in services for data orchestration, automation, and analytics. Reflow — A system for incremental data processing in the cloud. Dagster / ElementL — A data orchestrator for machine learning, analytics, and ETL. .

Consulting 120

Consulting Machine Learning Data Science Data Pipeline 120

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. Obviously, Big Data processing involves hundreds of computing units.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Ascend.io

MAY 31, 2023

In the modern world of data engineering, two concepts often find themselves in a semantic tug-of-war: data pipeline and ETL. Diverging Paths: The Key Differences While ETL and data pipelines share common processes, they diverge significantly in their capabilities and attributes.

Data Pipeline 52

Data Pipeline ETL Tools Pipeline-centric 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 are also accountable for communicating data trends. Let us now look at the three major roles of data engineers.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

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. Fluentd is a data collector and a lighter-weight alternative to Logstash.

Engineering 52

Engineering NoSQL Programming Language Java 52

Databand.ai

DECEMBER 29, 2022

He believes in making data do the work through proper data management based on strategic rationale and business alignment. On LinkedIn, he posts frequently about big data, master data, data science, data management, and data storytelling.

BI 52

BI Consulting Data Science Data Governance 52

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59