Edureka

FEBRUARY 9, 2023

Azure Data Engineering is a rapidly growing field that involves designing, building, and maintaining data processing systems using Microsoft Azure technologies. Contents: What is the role of an Azure Data Engineer?

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Knowledge Hut

NOVEMBER 2, 2023

Azure Data engineering projects are complicated and require careful planning and effective team participation for a successful completion. While many technologies are available to help data engineers streamline their workflows and guarantee that each aspect meets its objectives, ensuring that everything works properly takes time.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

DareData

JANUARY 30, 2023

Learn the most important data engineering concepts that data scientists should be aware of. As the field of data science and machine learning continues to evolve, it is increasingly evident that data engineering cannot be separated from it. DigDag: An open-source orchestrator for data engineering workflows.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

Cloudera

OCTOBER 11, 2021

Modak, a leading provider of modern data engineering solutions, is now a certified solution partner with Cloudera. Customers can now seamlessly automate migration to Cloudera’s Hybrid Data Platform — Cloudera Data Platform (CDP) to dynamically auto-scale cloud services with Cloudera Data Engineering (CDE) integration with Modak Nabu.

Data Engineering 92

Data Engineering Data Engineer Cloud Engineering 92

Data Engineering Weekly

NOVEMBER 13, 2022

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. Sign up free to test out the tool today.

Data Engineering 52

Data Engineering Data Engineer Engineering Kafka 52

Cloudera

FEBRUARY 15, 2024

By leveraging cutting-edge technology and an efficient framework for managing, analyzing, and securing data, financial institutions can streamline operations and enhance their ability to meet compliance requirements efficiently, while maintaining a strong focus on risk management. This results in enhanced efficiency in compliance processes.

Insurance 86

Insurance Banking Data Architecture Data Ingestion 86

Edureka

FEBRUARY 7, 2023

An Azure Data Engineer is responsible for designing, implementing, and maintaining data management and data processing systems on the Microsoft Azure cloud platform. They work with large and complex data sets and are responsible for ensuring that data is stored, processed, and secured efficiently and effectively.

Data Engineering 52

Data Engineering Data Engineer Engineering Programming Language 52

ProjectPro

AUGUST 24, 2021

Nevertheless, that is not the only job in the data world. Data professionals who work with raw data like data engineers, data analysts, machine learning scientists , and machine learning engineers also play a crucial role in any data science project.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

FEBRUARY 21, 2023

With so many data engineering certifications available , choosing the right one can be a daunting task. There are over 133K data engineer job openings in the US, but how will you stand out in such a crowded job market? The answer is- by earning professional data engineering certifications! AWS or Azure?

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Knowledge Hut

APRIL 25, 2023

The tremendous growth in data generation, then the rise in data engineer jobs - there’s no arguing the fact that the big data industry is at its best pace and you, as an aspiring data engineer, have a lot to learn and make out of it - including some tools! What are Data Engineering Tools?

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

phData: Data Engineering

JANUARY 3, 2022

What is Data Engineering? Everything You Need to Know in 2022 Nick Goble January 4, 2022 It’s easy to overlook the amount of data that’s being generated every day — from your smartphone, your Zoom calls, to your Wi-Fi-connected dishwasher. Table of Contents What is Data Engineering What is Data Governance?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Databand.ai

AUGUST 30, 2023

The core philosophy of DataOps is to treat data as a valuable asset that must be managed and processed efficiently. It emphasizes the importance of collaboration between different teams, such as data engineers, data scientists, and business analysts, to ensure that everyone has access to the right data at the right time.

Data Governance 52

Data Governance Data Pipeline Government Data Cleanse 52

Data Engineering Podcast

JUNE 19, 2022

In order to level up their value a new trend of active metadata is being implemented, allowing use cases like keeping BI reports up to date, auto-scaling your warehouses, and automated data governance. Data teams are increasingly under pressure to deliver. In fact, while only 3.5% That’s where our friends at Ascend.io

Metadata 130

Metadata MongoDB Scala MySQL 130

Data Engineering Podcast

JUNE 5, 2022

In this episode Sean Falconer explains the idea of a data privacy vault and how this new architectural element can drastically reduce the potential for making a mistake with how you manage regulated or personally identifiable information. If you’re a data engineering podcast listener, you get credits worth $5,000 when you become a customer.

Data Security 100

Data Security Metadata MongoDB Scala 100

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. These tools help organizations implement DataOps practices by providing a unified platform for data teams to collaborate, share, and manage their data assets.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Monte Carlo

AUGUST 19, 2023

The data platform manages the collection, normalization, transformation, and application of data for a given data product—from business insights and dashboards to ML and AI engineering. So, with all that ambiguity, where’s a data engineer to start?Even We’ll cover: What is a data platform?

Building 52

Building BI Data Lake Data Governance 52

Towards Data Science

JULY 24, 2023

While there is no right answer, there is likely a sweet spot for most organizations’ data platforms. Photo by Kelly Sikkema on Unsplash Data engineers discovered the benefits of conscious uncoupling around the same time as Gwyneth Paltrow and Chris Martin in 2014. Take data governance for example.

Metadata 96

Metadata Data Warehouse Data Lake Data Science 96

Cloudera

JANUARY 12, 2018

I mentioned in an earlier blog titled, “Staffing your big data team, ” that data engineers are critical to a successful data journey. That said, most companies that are early in their journey lack a dedicated engineering group. Image 1: Data Engineering Skillsets.

Big Data 54

Big Data Data Engineering Data Engineer Engineering 54

Data Engineering Podcast

OCTOBER 12, 2020

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management What are the pieces of advice that you wish you had received early in your career of data engineering? If you hand a book to a new data engineer, what wisdom would you add to it?

Business Intelligence 100

Business Intelligence BI Consulting Data Ingestion 100

Data Engineering Podcast

NOVEMBER 16, 2020

Summary The core mission of data engineers is to provide the business with a way to ask and answer questions of their data. This often takes the form of business intelligence dashboards, machine learning models, or APIs on top of a cleaned and curated data set.

Data Management 100

Data Management Management BI Business Intelligence 100

Mutt Data

JULY 16, 2023

This would be a crucial step in becoming increasingly data-driven, while also enabling them to tackle any data governance concerns or data bottlenecks in their journey to insights.

Data Lake 40

Data Lake Data Ingestion Banking Data Pipeline 40

Mutt Data

JULY 16, 2023

This would be a crucial step in becoming increasingly data-driven, while also enabling them to tackle any data governance concerns or data bottlenecks in their journey to insights.

Data Lake 40

Data Lake AWS Data Ingestion Banking 40

The Modern Data Company

MAY 8, 2023

Potential downsides of data lakes include governance and integration challenges. Data lakes often lack robust data governance, leading to data quality, consistency, and security issues. It provides a flexible, scalable, and secure data infrastructure that can adapt to evolving business needs.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Potential downsides of data lakes include governance and integration challenges. Data lakes often lack robust data governance, leading to data quality, consistency, and security issues. It provides a flexible, scalable, and secure data infrastructure that can adapt to evolving business needs.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Potential downsides of data lakes include governance and integration challenges. Data lakes often lack robust data governance, leading to data quality, consistency, and security issues. It provides a flexible, scalable, and secure data infrastructure that can adapt to evolving business needs.

Data Management 52

Data Management Data Lake Management Data Governance 52

DataKitchen

OCTOBER 2, 2023

Data Teams and Their Types of Data Journeys In the rapidly evolving landscape of data management and analytics, data teams face various challenges ranging from data ingestion to end-to-end observability. It explores why DataKitchen’s ‘Data Journeys’ capability can solve these challenges.

Data Ingestion 40

Data Ingestion Data Government Datasets 40

Monte Carlo

NOVEMBER 14, 2023

How data observability can increase data trust in Iceberg tables What is Apache Iceberg? Apache Iceberg is an open source data lakehouse table format developed by the data engineering team at Netflix to provide a faster and easier way to process large datasets at scale. Limited data type support.

Data Lake 64

Data Lake Metadata Data Warehouse SQL 64

Knowledge Hut

JANUARY 3, 2024

DevOps Engineers ensure smooth integration of development and operations in Azure environments. Azure Data Engineer Azure Data Engineers are experts in the design and implementation of data solutions on Azure. Experience in data modeling, data ingestion, and data transformation.

Cloud Computing 52

Cloud Computing Recruitment Computer Science Education 52

Monte Carlo

MAY 25, 2023

Automated data orchestration removes data bottlenecks by eliminating the need for manual data preparation, enabling analysts to both extract and activate data in real-time. Improved data governance. Data orchestration enables data teams to easily understand, prepare, and manage pipelines at scale.

Data Pipeline 52

Data Pipeline Data Workflow Data Data Governance 52

AltexSoft

JUNE 26, 2023

Read our article on Hotel Data Management to have a full picture of what information can be collected to boost revenue and customer satisfaction in hospitality. While all three are about data acquisition, they have distinct differences. For this task, you need a dedicated specialist — a data engineer or ETL developer.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake BI Google Cloud 64

phData: Data Engineering

SEPTEMBER 19, 2023

Cost reduction by minimizing data redundancy, improving data storage efficiency, and reducing the risk of errors and data-related issues. Data Governance and Security By defining data models, organizations can establish policies, access controls, and security measures to protect sensitive data.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Monte Carlo

JUNE 14, 2023

Why is data pipeline architecture important? For example, data may be extracted from multiple sources, reorganized, and joined at different times before ultimately being served to its final destination. Why is data pipeline architecture important? They also recently acquired Apache Flink , another streaming solution.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Snowflake

MARCH 30, 2023

A 2016 data science report from data enrichment platform CrowdFlower found that data scientists spend around 80% of their time in data preparation (collecting, cleaning, and organizing of data) before they can even begin to build machine learning (ML) models to deliver business value. ML workflow, ubr.to/3EJHjvm

Engineering 84

Engineering Raw Data Data Science Scala 84

Monte Carlo

OCTOBER 5, 2023

Ownership of measurements Different teams can play different roles in measuring data quality, but you’ll want to be sure clear accountability is assigned and good communication channels are in place. Data quality standards for governance Data governance is the process of maintaining the availability, usability, privacy, and security of data.

Government 52

Government Data Governance Data Datasets 52

Ascend.io

JANUARY 10, 2024

This process ensures your data is accurate, complete, and consistently up-to-date — preventing any degradation that could mislead your AI, which can lead to erroneous outputs. Effective Data Governance: Lastly, let’s talk about governance. This is your rulebook for managing data.

Data Pipeline 52

Data Pipeline Government Data Governance Raw Data 52