Knowledge Hut

MARCH 28, 2024

Job Role 1: Azure Data Engineer Azure Data Engineers develop, deploy, and manage data solutions with Microsoft Azure data services. They use many data storage, computation, and analytics technologies to develop scalable and robust data pipelines. GDPR, HIPAA), and industry standards.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Netflix Tech

NOVEMBER 14, 2023

We’ll discuss batch data processing, the limitations we faced, and how Psyberg emerged as a solution. Furthermore, we’ll delve into the inner workings of Psyberg, its unique features, and how it integrates into our data pipelining workflows. This is mainly used to identify new changes since the last update.

Data Engineering 105

Data Engineering Data Engineer Engineering Metadata 105

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

The Modern Data Company

JANUARY 31, 2023

This post highlights exactly how our founders taught us to think differently about data and why it matters. Here are the cornerstones of this new paradigm: Data ownership is a construct Data pipelines should be accessible to everyone Data products should adapt to the organization, not vice versa.

Retail 98

Retail Healthcare Data Architecture Data Pipeline 98

Knowledge Hut

NOVEMBER 17, 2023

The job of an Azure Data Engineer is really needed in the world of handling and studying data. As Azure Data Engineers, they'll be responsible for creating and looking after solutions that use data to help the company. Azure Data Factory stands at the forefront, orchestrating data workflows.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Ascend.io

FEBRUARY 28, 2024

Engineers ensure the availability of clean, structured data, a necessity for AI systems to learn from patterns, make accurate predictions, and automate decision-making processes. Through the design and maintenance of efficient data pipelines , data engineers facilitate the seamless flow and accessibility of data for AI processing.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Knowledge Hut

MARCH 20, 2024

The job description for Azure data engineer that I have elucidated below focuses more on foundational tasks while providing opportunities for learning and growth within the field: Data ingestion: This role involves assisting in the process of collecting and importing data from various sources into Azure storage solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

Ascend.io

NOVEMBER 21, 2023

The emergence of cloud data warehouses, offering scalable and cost-effective data storage and processing capabilities, initiated a pivotal shift in data management methodologies. This approach ensures that only processed and refined data is housed in the data warehouse, leaving the raw data outside of it.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

Knowledge Hut

MARCH 15, 2024

The job description for Azure data engineer that I have elucidated below focuses more on foundational tasks while providing opportunities for learning and growth within the field: Data ingestion: This role involves assisting in the process of collecting and importing data from various sources into Azure storage solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

AltexSoft

FEBRUARY 11, 2023

To get a better understanding of a data architect’s role, let’s clear up what data architecture is. Data architecture is the organization and design of how data is collected, transformed, integrated, stored, and used by a company. This privacy law must be kept in mind when building data architecture.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Knowledge Hut

NOVEMBER 17, 2023

They work with various stakeholders to provide real-time data analytics, maintain data quality and integrity, and deliver insightful data to the business. The main duties of an Azure Data Engineer are planning, developing, deploying, and managing the data pipelines.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Striim

NOVEMBER 8, 2023

This allows for two-way integration so that information can flow from one system to another in real-time. Striim is a cloud-native Data Mesh platform that offers features such as automated data mapping, real-time data integration, streaming analytics, and more.

Architecture 52

Architecture Generalist Government Datasets 52

Data Engineering Weekly

FEBRUARY 25, 2024

They focused on enhancing customer experiences and operational efficiency through customized AI models, addressing latency and data integrity challenges. This initiative reduced costs and enhanced computational efficiency, demonstrating the significant benefits of GPUs in big data environments.

Data Engineering 62

Data Engineering Data Engineer Engineering Kafka 62

Knowledge Hut

JUNE 30, 2023

The essential theories, procedures, and equipment for creating trustworthy and effective data systems are covered in this book. It explores subjects including data modeling, data pipelines, data integration, and data quality, offering helpful advice on organizing and implementing reliable data solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Cloudera

MARCH 23, 2022

In fact, we recently announced the integration with our cloud ecosystem bringing the benefits of Iceberg to enterprises as they make their journey to the public cloud, and as they adopt more converged architectures like the Lakehouse. 1: Multi-function analytics . 1: Multi-function analytics . Flexible and open file formats.

Metadata 90

Metadata Data Architecture BI Machine Learning 90

Silectis

JANUARY 3, 2021

Big Data Processing In order to extract value or insights out of big data, one must first process it using big data processing software or frameworks, such as Hadoop. Big Query Google’s cloud data warehouse. Data Catalog An organized inventory of data assets relying on metadata to help with data management.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Monte Carlo

JULY 27, 2023

The most common use case data quality engineers support are: Analytical dashboards : Mentioned in 56% of job postings Machine learning or data science teams : Mentioned in 34% of postings Gen AI : Mentioned in one job posting (but really emphatically).

Engineering 52

Engineering Healthcare Scala Data Warehouse 52

Striim

NOVEMBER 17, 2023

Striim serves as a real-time data integration platform that seamlessly and continuously moves data from diverse data sources to destinations such as cloud databases, messaging systems, and data warehouses, making it a vital component in modern data architectures.

Machine Learning 52

Machine Learning Data Process PostgreSQL Process 52

Silectis

JANUARY 22, 2021

Data Warehouses Have Boundaries Data warehouses do what they’re meant to, they provide a high-performance environment for data analytics. This is an important piece of a modern and reliable data architecture.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Monte Carlo

DECEMBER 8, 2023

Data lineage is useful for optimizing and troubleshooting data pipelines. Let’s dive deeper into the definitions of data provenance and data lineage, what they’re used for, and why they’re so important for data teams. Table of Contents What is data provenance? Image courtesy of The Morning Paper.

Metadata 52

Metadata Data Data Warehouse Government 52

Monte Carlo

DECEMBER 8, 2023

Data lineage is useful for optimizing and troubleshooting data pipelines. Let’s dive deeper into the definitions of data provenance and data lineage, what they’re used for, and why they’re so important for data teams. Table of Contents What is data provenance? Image courtesy of The Morning Paper.

Metadata 52

Metadata Data Data Warehouse Government 52

Monte Carlo

FEBRUARY 9, 2023

Over the past several years, data warehouses have evolved dramatically, but that doesn’t mean the fundamentals underpinning sound data architecture needs to be thrown out the window. Pie Insurance , a leading small business insurtech, leverages a data vault 2.0 How do you implement a data vault architecture?

Architecture 52

Architecture Raw Data Metadata Data Warehouse 52

ProjectPro

SEPTEMBER 26, 2021

Big Data Engineers are professionals who handle large volumes of structured and unstructured data effectively. They are responsible for changing the design, development, and management of data pipelines while also managing the data sources for effective data collection.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

Databand.ai

DECEMBER 13, 2022

1) Joseph Machado Senior Data Engineer at LinkedIn Joseph is an experienced data engineer, holding a Master’s degree in Electrical Engineering from Columbia University and having spent time on the teams at Annalect, Narrativ, and most recently LinkedIn. You can also watch the video recording.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

DataKitchen

DECEMBER 20, 2020

If the data team is always dealing with data errors and putting out fires, then they’ll be constantly pulled away from their highest priority projects. . You can transform your data analytics workflows by applying methodologies like agile development , DevOps , and lean manufacturing to data pipelines and analytics workflows.

Engineering 59

Engineering Manufacturing Data Analytics Data Workflow 59

AltexSoft

OCTOBER 30, 2021

They’re integral specialists in data science projects and cooperate with data scientists by backing up their algorithms with solid data pipelines. Juxtaposing data scientist vs engineer tasks. One data scientist usually needs two or three data engineers. An overview of data engineer skills.

Data Engineering 98

Data Engineering Data Engineer Engineering Machine Learning 98

Knowledge Hut

JANUARY 18, 2024

Automation and DataOps for Improved Data Analytics Automation and DataOps (Data Operations) are emerging technologies that improve data analytics by streamlining and automating various tasks involved in the data pipeline. Consequently, automation tools reduce manual effort and increase efficiency.

Data Analytics 52

Data Analytics Healthcare Machine Learning Algorithm 52

Cloudera

OCTOBER 7, 2021

In this blog, I will demonstrate the value of Cloudera DataFlow (CDF) , the edge-to-cloud streaming data platform available on the Cloudera Data Platform (CDP) , as a Data integration and Democratization fabric. Components of a Data Mesh. How CDF enables successful Data Mesh Architectures.

Architecture 124

Architecture Metadata Government Kafka 124

Databand.ai

JANUARY 24, 2023

In turn, this demand puts pressure on real-time access to data and increased automation, which then increases the need for AI. Supporting all of this requires a modern infrastructure and data architecture with appropriate governance. DataOps helps ensure organizations make decisions based on sound data. Enter DataOps.

Retail 52

Retail Banking Government Manufacturing 52

DataKitchen

JANUARY 23, 2023

It allows organizations to see how data is being used, where it is coming from, its quality, and how it is being transformed. DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. What is missing in data lineage? Are problems with data tests?

Data Governance 52

Data Governance Government Data Pipeline Data 52

Monte Carlo

SEPTEMBER 16, 2020

While our ability to collect, store, aggregate, and visualize this data has largely kept up with the needs of modern data teams (think: domain-oriented data meshes , cloud warehouses , data visualization tools , and data modeling solutions ), the mechanics behind data quality and data integrity has lagged.

Software Engineer 52

Software Engineer Software Engineering Data Data Pipeline 52

AltexSoft

MARCH 30, 2023

Databricks architecture Databricks provides an ecosystem of tools and services covering the entire analytics process — from data ingestion to training and deploying machine learning models. These improvements become possible due to the core components of the Databricks architecture — Delta Lake and Unity Catalog.

Scala 64

Scala Data Lake BI Google Cloud 64

phData: Data Engineering

JULY 18, 2023

This complexity often necessitates the involvement of numerous experts who specialize in these individual systems to effectively extract the data. Enter Fivetran Fivetran automates the data integration process, helping reduce the overall effort required to manage data movement from different sources into your data warehouse.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

Knowledge Hut

APRIL 20, 2023

Data ownership and accountability: It involves defining roles and responsibilities for managing data and ensuring that data ownership and accountability are clearly established. This may involve assigning data stewards and data custodians and implementing data governance committees.

Data Governance 59

Data Governance Government Data Cleanse Data Security 59

ProjectPro

FEBRUARY 16, 2023

Knowing SQL helps data engineers optimize data infrastructures for better performance and efficiency and also develop more effective data models and data warehousing solutions. Data integration will become highly significant as the amount of data globally grows in volume, variety, and complexity.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

Monte Carlo

MAY 17, 2023

Data Warehouse (Or Lakehouse) Migration 34. Integrate Data Stacks Post Merger 35. Know When To Fix Vs. Refactor Data Pipelines Improve DataOps Processes 37. Analyze Data Incident Impact and Triage 39. Transition To A Data Mesh (Or Other Data Team Structure) 40. Conduct Pre-Mortems 38.

Data 52

Data Data Pipeline Data Engineering Data Engineer 52

Monte Carlo

MAY 17, 2023

Data warehouse (or Lakehouse) migration 34. Integrate Data Stacks Post Merger 35. Know When To Fix Vs. Refactor Data Pipelines Improve DataOps Processes 37. Analyze Data Incident Impact and Triage 39. Transition To A Data Mesh (Or Other Data Team Structure) 40. Conduct Pre-Mortems 38.

Data Pipeline 52

Data Pipeline Data Data Engineering Data Engineer 52