Knowledge Hut

SEPTEMBER 26, 2023

The demand for knowledgeable data engineers that can plan, create, and maintain sophisticated data infrastructure is growing as the amount of data created by enterprises continues to increase dramatically. The success of our career as an Azure Data Engineer depends on our ability to master several different talents.

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Knowledge Hut

NOVEMBER 17, 2023

The demand for data-related professions, including data engineering, has indeed been on the rise due to the increasing importance of data-driven decision-making in various industries. Becoming an Azure Data Engineer in this data-centric landscape is a promising career choice.

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Data Engineering Data Engineer Engineering Scala 52

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.

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Data Engineering Data Engineer Engineering Cloud Computing 52

Netflix Tech

JULY 15, 2021

Data Engineers of Netflix?—?Interview Interview with Kevin Wylie This post is part of our “Data Engineers of Netflix” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Kevin, what drew you to data engineering?

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Data Engineering Data Engineer Engineering Entertainment 75

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.

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Ascend.io

AUGUST 31, 2023

Secondly , the rise of data lakes that catalyzed the transition from ELT to ELT and paved the way for niche paradigms such as Reverse ETL and Zero-ETL. Still, these methods have been overshadowed by EtLT — the predominant approach reshaping today’s data landscape.

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Data Lake ETL Tools Data Warehouse Data Pipeline 52

ProjectPro

FEBRUARY 8, 2023

ETL stands for Extract, Transform, and Load, which involves extracting data from various sources, transforming the data into a format suitable for analysis, and loading the data into a destination system such as a data warehouse. ETL developers play a significant role in performing all these tasks.

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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.

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AWS Data Management ETL Tools Management 52

Data Engineering Weekly

DECEMBER 29, 2022

I even authored a special edition capturing metadata tool’s history at Data Engineering Weekly. Data Engineering Weekly Data Engineering Weekly #21: Metadata Edition Welcome to the 21st edition of the data engineering newsletter. The pre-modern(?) What does that mean?

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Metadata Data Warehouse ETL Tools Data Workflow 62

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.

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PostgreSQL Data Lake ETL Tools MySQL 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.

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Data Science BI Business Intelligence Data Mining 97

Lyft Engineering

OCTOBER 3, 2023

In this post we will define data quality at a high-level and explore our motivation to achieve better data quality. We will then introduce our in-house product, Verity, and showcase how it serves as a central platform for ensuring data quality in our Hive Data Warehouse. What and Where is Data Quality?

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Big Data Metadata Data Warehouse Data 84

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.

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Data Pipeline Data Lake Data Warehouse Datasets 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.

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BI Data Governance ETL Tools Data Warehouse 52

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.

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Data Lake Building Raw Data ETL Tools 52

Grouparoo

JANUARY 26, 2022

Warehouse Storage Needs The foundation of Maslow’s hierarchy of needs is about physiological needs like having enough food, water, and sleep. In the world of the modern data stack, the parallel is having a data warehouse that can act as a foundation for the work to be done. This often accounts for the core business cases.

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Data Warehouse Food ETL Tools Raw 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.

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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.

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Data Lake Architecture IT Amazon Web Services 52

Knowledge Hut

JANUARY 29, 2024

ETL Aspect Data Wrangling ETL (Extract, Transform, Load) Purpose Preparing data for analysis Integrating, transforming, and loading data Users Data analysts, scientists, ETL developers, data engineers, business users IT professionals Data Structure Varied and complex data sets Structured or semi-structured data sets Use Case Exploratory data analysis (..)

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Raw Data Data Mining Data Preparation Structured Data 52

dbt Developer Hub

JUNE 12, 2023

Introduction ​ Most data modeling approaches for customer segmentation are based on a wide table with user attributes. This table only stores the current attributes for each user, and is then loaded into the various SaaS platforms via Reverse ETL tools.

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Building ETL Tools Data Warehouse Machine Learning 59

ProjectPro

DECEMBER 7, 2021

Generally, data pipelines are created to store data in a data warehouse or data lake or provide information directly to the machine learning model development. Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives.

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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. You should then document this information and even consider creating a data SLA.

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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.

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Data Science Blog: Data Engineering

SEPTEMBER 19, 2023

In the contemporary age of Big Data, Data Warehouse Systems and Data Science Analytics Infrastructures have become an essential component for organizations to store, analyze, and make data-driven decisions. So why using IaC for Cloud Data Infrastructures?

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Knowledge Hut

MAY 2, 2024

Data Warehousing: Data warehousing is another function where Apache Spark has is getting tremendous traction. Due to an increasing volume of data day by day, the tradition ETL tools like Informatic along with RDBMS are not able to meet the SLAs as they are not able to scale horizontally.

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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.

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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?

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Data Engineering Data Engineer Engineering Data Mining 52

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?

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Data Engineering Data Engineer Engineering Raw Data 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?

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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.

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Data Engineering Data Engineer Engineering Scala 52

Grouparoo

SEPTEMBER 7, 2021

Data analysts and data engineers are responsible for building and maintaining data infrastructure to support many different teams at companies. What did you do before Operational Analytics and Reverse ETL existed? The Modern Data Stack is a recent development in the data engineering space.

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ETL Tools Data Warehouse Business Intelligence Datasets 52

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. Data Ingestion Data ingestion is the first step of both ETL and data pipelines. The data sources themselves are not built to perform analytics.

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Data Pipeline ETL Tools Pipeline-centric Data Warehouse 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.

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Big Data Data Engineering Data Engineer Engineering 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.

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Data Engineering Data Engineer Engineering Data Lake 52

Ascend.io

DECEMBER 21, 2022

The last three years have seen a remarkable change in data infrastructure. ETL changed towards ELT. Now, data teams are embracing a new approach: reverse ETL. Cloud data warehouses, such as Snowflake and BigQuery, have made it simpler than ever to combine all of your data into one location.

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ETL Tools ETL System Data Warehouse Data Consolidation 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.

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