Knowledge Hut

OCTOBER 3, 2023

Within the Microsoft Azure ecosystem, the role of an Azure data engineer stands out as one of the most sought-after positions. What Does an Azure Data Engineer Do? Azure Data engineers collaborate with Azure AI services built on top of Azure Cognitive Services APIs to offer end customers a variety of pre-built models.

Data Engineering 52

Data Engineering Data Engineer Engineering Cloud Computing 52

Ascend.io

DECEMBER 19, 2023

We’ll talk about when and why ETL becomes essential in your Snowflake journey and walk you through the process of choosing the right ETL tool. Our focus is to make your decision-making process smoother, helping you understand how to best integrate ETL into your data strategy. But first, a disclaimer.

ETL Tools 52

ETL Tools IT Data Pipeline Data Warehouse 52

Ascend.io

AUGUST 31, 2023

Still, these methods have been overshadowed by EtLT — the predominant approach reshaping today’s data landscape. In this article, we assess: The role of the data warehouse on one hand, and the data lake on the other; The features of ETL and ELT in these two architectures; The evolution to EtLT; The emerging role of data pipelines.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

ProjectPro

DECEMBER 7, 2021

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. Table of Contents What is a Data Pipeline? The Importance of a Data Pipeline What is an ETL Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

FEBRUARY 16, 2023

ETL is a critical component of success for most data engineering teams, and with teams harnessing it with the power of AWS, the stakes are higher than ever. Data Engineers and Data Scientists require efficient methods for managing large databases, which is why centralized data warehouses are in high demand.

AWS 52

AWS Data Management ETL Tools Management 52

Monte Carlo

DECEMBER 4, 2023

At the heart of data engineering lies the ETL process—a necessary, if sometimes tedious, set of operations to move data across pipelines for production. Loading ChatGPT ETL prompts can help write scripts to load data into different databases, data lakes, or data warehouses.

PostgreSQL 52

PostgreSQL Data Lake ETL Tools MySQL 52

Databand.ai

JULY 5, 2023

What Are Data Observability Tools? Data observability tools are software solutions that oversee, analyze, and improve the performance of data pipelines. By employing these tools, teams can proactively detect issues before they become larger problems that affect business operations.

Data Pipeline 52

Data Pipeline Data Lake Data Warehouse Datasets 52

Knowledge Hut

DECEMBER 26, 2023

Data Science is a combination of several disciplines including Mathematics and Statistics, Data Analysis, Machine Learning, and Computer Science. Data Science is a huge umbrella with a plethora of roles available in the field such as a Data Scientist, Data Engineer, BI Developer, Data and Analytics Manager, etc.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

DareData

JULY 5, 2023

The architecture of a data lake project may contain multiple components, including the Data Lake itself, one or multiple Data Warehouses or one or multiple Data Marts. The Data Lake acts as the central repository for aggregating data from diverse sources in its raw format.

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

ProjectPro

JANUARY 24, 2023

With over 20 pre-built connectors and 40 pre-built transformers, AWS Glue is an extract, transform, and load (ETL) service that is fully managed and allows users to easily process and import their data for analytics. You can leverage AWS Glue to discover, transform, and prepare your data for analytics.

AWS 52

AWS Data Lake ETL Tools Scala 52

Monte Carlo

SEPTEMBER 12, 2022

The field of data engineering has been growing at a breakneck pace. New frameworks, new challenges, and new technologies are constantly shifting how engineers think about their work and their roles within their organizations. Plus, he was one of the first data engineers at Facebook and Airbnb.

BI 52

BI Data Governance ETL Tools Data Warehouse 52

Monte Carlo

AUGUST 8, 2023

By applying rules and checks, data validation testing verifies the data meets predefined standards and business requirements to help prevent data quality issues and data downtime. From this perspective, the data validation process looks a lot like any other DataOps process.

Data Validation 52

Data Validation Data Pipeline SQL Data 52

Data Engineering Weekly

JANUARY 6, 2023

Recap could be part of a traditional data catalog, something you could use to build a data catalog, but it isn’t a data catalog. Data quality, data contract, data discovery, compliance, governance, and ETL tools all need metadata–row counts, cardinality, distribution, max, min, number of nulls, and so on.

Metadata 40

Metadata ETL Tools MySQL Data Lake 40

AltexSoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Knowledge Hut

MAY 3, 2023

With companies increasingly relying on data-driven insights to make informed decisions, there has never been a greater need for skilled specialists who can manage and evaluate vast amounts of data. The roles of data analyst and data engineer have emerged as two of the most in-demand professions in today's job market.

Data Engineering 98

Data Engineering Data Engineer Engineering Data Cleanse 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. Fast forward to the present day, and we now have data pipelines. However, they are not just an upgraded version of ETL. Yet, the technical problem is the same.

Data Pipeline 52

Data Pipeline ETL Tools Pipeline-centric Data Warehouse 52

AltexSoft

OCTOBER 30, 2021

If you’re an executive who has a hard time understanding the underlying processes of data science and get confused with terminology, keep reading. We will try to answer your questions and explain how two critical data jobs are different and where they overlap. Data science vs data engineering.

Data Engineering 98

Data Engineering Data Engineer Engineering Machine Learning 98

Meltano

OCTOBER 5, 2022

Interested in becoming a data engineer? The need for data experts in the U.S. job market is expected to grow by 22% in this decade, and according to LinkedIn’s 2020 report , a data engineer is listed as the 8th fastest growing job today. But what is data engineering exactly and what does a data engineer do?

Data Engineering 52

Data Engineering Data Engineer Engineering Raw Data 52

Edureka

FEBRUARY 9, 2023

The role of Azure Data Engineer is in high demand in the field of data management and analytics. As an Azure Data Engineer, you will be in charge of designing, building, deploying, and maintaining data-driven solutions that meet your organization’s business needs. Who is an Azure Data Engineer?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

Knowledge Hut

NOVEMBER 19, 2023

One of the most important responsibilities for experts in big data is configuring the cloud to store data and provide high availability. As a result, data engineers working with big data today require a basic grasp of cloud computing platforms and tools. What Are Azure Data Engineer Tools?

Data Engineering 52

Data Engineering Data Engineer Engineering PostgreSQL 52

ProjectPro

JANUARY 19, 2022

Planning to land a successful job as an Azure Data Engineer? Read this blog till the end to learn more about the roles and responsibilities, necessary skillsets, average salaries, and various important certifications that will help you build a successful career as an Azure Data Engineer.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

ProjectPro

SEPTEMBER 26, 2021

According to a survey, big data engineering job interviews increased by 40% in 2020 compared to only a 10% rise in Data science job interviews. Table of Contents Big Data Engineer - The Market Demand Who is a Big Data Engineer? Most of these are performed by Data Engineers.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

Grouparoo

SEPTEMBER 7, 2021

Operational analytics is the process of creating data pipelines and datasets to support business teams such as sales, marketing, and customer support. Data analysts and data engineers are responsible for building and maintaining data infrastructure to support many different teams at companies.

ETL Tools 52

ETL Tools Data Warehouse Business Intelligence Datasets 52

Databand.ai

JULY 19, 2023

A Beginner’s Guide [SQ] Niv Sluzki July 19, 2023 ELT is a data processing method that involves extracting data from its source, loading it into a database or data warehouse, and then later transforming it into a format that suits business needs. The data is loaded as-is, without any transformation.

Data Cleanse 52

Data Cleanse Raw Data Data Storage Data Warehouse 52

Edureka

FEBRUARY 7, 2023

If you want to become a data engineer, you should prepare for the interview process. To help you get a head start on your preparation, I’ve compiled a list of the Top 30+ Azure Data Engineer Interview Questions. When it comes to professionals, data engineers are the most in-demand in the IT industry.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Data Engineering Podcast

JANUARY 15, 2022

In this episode Brian McMillan shares his work on the book "Building Data Products" and how he is working to educate business users and data professionals about the combination of technical, economical, and business considerations that need to be blended for these projects to succeed.

Engineering 100

Engineering Electronics ETL Tools Data Pipeline 100

Knowledge Hut

APRIL 19, 2023

If you want to learn more about ETL processes check out this Data Engineer course. What is ETL? ETL stands for Extract, Transform, and Load. It is the process of extracting data from various sources, transforming it into a format suitable for analysis, and loading it into a target database or data warehouse.

Data Warehouse 52

Data Warehouse Business Intelligence ETL Tools Data Pipeline 52

Monte Carlo

APRIL 4, 2023

Today, I’m excited to announce Monte Carlo’s new Fivetran integration , giving mutual customers the ability to accelerate data incident detection and resolution by adding monitoring to data pipelines at the point of creation.

ETL Tools 52

ETL Tools Data Pipeline Business Intelligence Data Warehouse 52

Monte Carlo

APRIL 4, 2023

Today, I’m excited to announce Monte Carlo’s new Fivetran integration , giving mutual customers the ability to accelerate data incident detection and resolution by adding monitoring to data pipelines at the point of creation.

ETL Tools 52

ETL Tools Data Pipeline Business Intelligence Data Warehouse 52

AltexSoft

JANUARY 26, 2022

In recent years, it’s getting more common to see organizations looking for a mysterious analytics engineer. As you may guess from the name, this role sits somewhere in the middle of a data analyst and data engineer, but it’s really neither one nor the other. Here’s the video explaining how data engineers work.

Engineering 59

Engineering Software Engineer Software Engineering Data Warehouse 59

ProjectPro

FEBRUARY 18, 2022

This indicates that more businesses will adopt the tools and methodologies useful in big data analytics, including implementing the ETL pipeline. Data engineers are in charge of developing data models, constructing data pipelines, and monitoring ETL (extract, transform, load).

Project 52

Project AWS Kafka Healthcare 52

Ascend.io

SEPTEMBER 19, 2023

In the world of data engineering, the ETL (Extract, Transform, Load) approach has been the cornerstone for managing and processing data. However , the traditional methods of executing ETL are increasingly struggling to meet the escalating demands of today’s data-intensive environments.

ETL Tools 52

ETL Tools ETL Method Utilities Data Engineering 52

Monte Carlo

FEBRUARY 15, 2023

Cloud data warehouses solve these problems. Belonging to the category of OLAP (online analytical processing) databases, popular data warehouses like Snowflake, Redshift and Big Query can query one billion rows in less than a minute. What is a data warehouse?

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

ProjectPro

NOVEMBER 30, 2021

This guide provides definitions, a step-by-step tutorial, and a few best practices to help you understand ETL pipelines and how they differ from data pipelines. The crux of all data-driven solutions or business decision-making lies in how well the respective businesses collect, transform, and store data.

Process 52

Process Data Pipeline Data Warehouse AWS 52

Meltano

OCTOBER 5, 2022

DataOps, which is based on Agile methodology and DevOps best practices, is focused on automating data flow across an organization and the entire data lifecycle, from aggregation to reporting. The goal of DataOps is to speed up the process of deriving value from data. Using automation to streamline data processing.

Engineering 52

Engineering Raw Data Data Pipeline ETL Tools 52

Grouparoo

AUGUST 24, 2021

What you really want is a unified view of your data using Customer Data Integration so you can take action on it. Customer data integration here might include creating a data warehouse where you can house your accurate and complete dataset. How do you know your warehouse is up to date?

Data Integration 52

Data Integration Data Consolidation Data Warehouse ETL Tools 52

ProjectPro

JULY 27, 2021

This blog is your one-stop solution for the top 100+ Data Engineer Interview Questions and Answers. In this blog, we have collated the frequently asked data engineer interview questions based on tools and technologies that are highly useful for a data engineer in the Big Data industry.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40