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

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

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

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

Snowflake

AUGUST 16, 2023

Data comes in a continuous manner, and often a separate architecture is required to handle streaming data. What remains challenging is how streaming data is brought together with batch data. That’s why we built Snowpipe Streaming, now generally available to handle row-set data ingestion. Learn more here.

Scala 52

Scala Transportation Kafka Data Lake 52

Cloudera

FEBRUARY 16, 2022

In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage. Each project consists of a declarative series of steps or operations that define the data science workflow.

Machine Learning 85

Machine Learning Algorithm Government Metadata 85

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

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. Is your data lake a good fit for Iceberg?

Data Lake 64

Data Lake Metadata Data Warehouse SQL 64

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

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

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

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. RudderStack helps you build a customer data platform on your warehouse or data lake. In fact, while only 3.5%

Metadata 130

Metadata MongoDB Scala MySQL 130

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? Zero ETL is a bit of a misnomer.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

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. The project included: Setting up Databricks as the place to host the company data lake with delta tables to use as a single source of truth.

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. The project included: Setting up Databricks as the place to host the company data lake with delta tables to use as a single source of truth.

Data Lake 40

Data Lake AWS Data Ingestion Banking 40

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

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 94

Metadata Data Warehouse Data Lake Data Science 94

Ascend.io

MARCH 14, 2023

In this article, you’re going to learn the following: What a data mesh is Why it gained momentum The five core features of data mesh Why a company might consider building one Let’s dive in! What Is a Data Mesh? The magic of a data mesh is that it combines a data product mindset with a distributed data modeling technique.

Government 52

Government Architecture Data Lake Data 52

Ascend.io

MARCH 14, 2023

In this article, you’re going to learn the following: What a data mesh is Why it gained momentum The five core features of data mesh Why a company might consider building one Let’s dive in! What Is a Data Mesh? The magic of a data mesh is that it combines a data product mindset with a distributed data modeling technique.

Government 52

Government Architecture Data Lake Data 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 83

Engineering Raw Data Data Science Scala 83

AltexSoft

JULY 29, 2022

a runtime environment (sandbox) for classic business intelligence (BI), advanced analysis of large volumes of data, predictive maintenance , and data discovery and exploration; a store for raw data; a tool for large-scale data integration ; and. a suitable technology to implement data lake architecture.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

phData: Data Engineering

JANUARY 3, 2022

Software engineering practices define how to reliably and effectively build software and data products, delivering value faster to your customers. In this post, we will explore the complexities involved with software engineering with a focus on data engineering and data operations (DataOps).

IT 52

IT AWS Software Engineer Software 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 95

Data Engineering Data Engineer Cloud Engineering 95

Monte Carlo

JULY 18, 2023

Data engineers discovered the benefits of conscious uncoupling around the same time as Gwyneth Paltrow and Chris Martin in 2014. Of course, instead of life partners, engineers were starting to gleefully decouple storage and compute with emerging technologies like Snowflake (2012), Databricks (2013), and BigQuery (2010).

Metadata 52

Metadata Data Warehouse Data Lake Government 52

Monte Carlo

JULY 18, 2023

Data engineers discovered the benefits of conscious uncoupling around the same time as Gwyneth Paltrow and Chris Martin in 2014. Of course, instead of life partners, engineers were starting to gleefully decouple storage and compute with emerging technologies like Snowflake (2012), Databricks (2013), and BigQuery (2010).

Metadata 40

Metadata Data Warehouse Data Lake Government 40

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

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

AltexSoft

MARCH 14, 2023

Built around a cloud data warehouse, data lake, or data lakehouse. Modern data stack tools are designed to integrate seamlessly with cloud data warehouses such as Redshift, Bigquery, and Snowflake, as well as data lakes or even the child of the first two — a data lakehouse.

IT 59

IT Data Warehouse Data Governance Data Lake 59