Knowledge Hut

APRIL 23, 2024

Software engineering is a rapidly growing field with vast career opportunities. With emerging technologies like AI, machine learning, and blockchain, the demand for software engineers has skyrocketed. With emerging technologies like AI, machine learning, and blockchain, the demand for software engineers has skyrocketed.

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ProjectPro

FEBRUARY 16, 2023

The demand for skilled data engineers who can build, maintain, and optimize large data infrastructures does not seem to slow down any sooner. At the heart of these data engineering skills lies SQL that helps data engineers manage and manipulate large amounts of data. use SQL, compared to 61.7%

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Knowledge Hut

DECEMBER 28, 2023

Its comprehensive suite of services can handle data at scale. It’s no surprise that the demand for certified Azure data engineers has skyrocketed. Today, Azure Data Engineer certification is an invaluable asset for those looking to excel in the field of data engineering. Who is an Azure Data Engineer?

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Data Engineering Weekly

JANUARY 15, 2023

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. The conversation around the Cost of Idle CPU in Snowflake is exciting to me in the blog.

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Knowledge Hut

OCTOBER 8, 2023

In the cloud services and data engineering space, Amazon Web Services (AWS) is the leader, with a market share of 32%. These companies are constantly looking out for professionals who are familiar with and can develop newer technologies and systems for larger volumes of data. Who is an AWS Data Engineer and What Do They Do?

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Knowledge Hut

JUNE 30, 2023

The demand for experienced data engineers continuously expands in today's data-driven environment. Books on data engineering serve as essential resources to guide you through the vast terrain of data engineering. What is Data Engineering? Who are Data Engineers?

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Maxime Beauchemin

JANUARY 7, 2018

In this post, we’ll explore how applying the functional programming paradigm to data engineering can bring a lot of clarity to the process. This post distills fragments of wisdom accumulated while working at Yahoo, Facebook, Airbnb and Lyft, with the perspective of well over a decade of data warehousing and data engineering experience.

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Snowflake

MARCH 30, 2023

Collecting, cleaning, and organizing data into a coherent form for business users to consume are all standard data modeling and data engineering tasks for loading a data warehouse. Feature engineering: Data is transformed to support ML model training. ML workflow, ubr.to/3EJHjvm

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ProjectPro

JANUARY 19, 2022

Data Engineering is gradually becoming a popular career option for young enthusiasts. Explore this page further and learn everything about data engineers to find the answer. We will cover it all, from its definition, skills, responsibilities to the significance of data engineer in an institution.

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Hepta Analytics

FEBRUARY 14, 2022

DE Zoomcamp 2.2.1 – Introduction to Workflow Orchestration Following last weeks blog , we move to data ingestion. We already had a script that downloaded a csv file, processed the data and pushed the data to postgres database. This week, we got to think about our data ingestion design.

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ProjectPro

JUNE 9, 2021

This blog on Data Science vs. Data Engineering presents a detailed comparison between the two domains. vs. What does a Data Engineer do? Are you a Data Scientist or a Data Engineer? Is data engineering more important than data science?

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Ascend.io

APRIL 5, 2023

One recent example is a relatively new role that sits one step “up the stack” from data engineers: the analytics engineer. What is an analytics engineer? Analytics engineers are specialists that bridge the gap between highly technical data engineering and outcome-driven analytics.

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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.

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DataKitchen

OCTOBER 5, 2021

A DataOps Engineer owns the assembly line that’s used to build a data and analytic product. While car companies lowered costs using mass production, companies in 2021 put data engineers and data scientists on the assembly line. Imagine if a car company asked the engineers who designed cars to also build them.

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Rockset

DECEMBER 9, 2019

As a data engineer, my time is spent either moving data from one place to another, or preparing it for exposure to either reporting tools or front end users. As data collection and usage have become more sophisticated, the sources of data have become a lot more varied and disparate, volumes have grown and velocity has increased.

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Workfall

SEPTEMBER 18, 2023

Pair this with Snowflake , the cloud data warehouse that acts as a vault for your insights, and you have a recipe for data-driven success. Get ready to explore the realm where data dreams become reality! In this blog, we will cover: What is Airbyte? With Airbyte and Snowflake, data integration is now a breeze.

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DataKitchen

DECEMBER 9, 2022

ChatGPT> DataOps, or data operations, is a set of practices and technologies that organizations use to improve the speed, quality, and reliability of their data analytics processes. Query> An AI, Chat GPT wrote this blog post, why should I read it? .

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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. What an analytics engineer is. Sounds interesting, right?

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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.

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Snowflake

FEBRUARY 21, 2023

I led the developer experience team and the Voice product (one of the main revenue engines), and I founded the AI/ML business unit. Sub-second response times: It provides a powerful cache that automatically syncs and serves your Snowflake data with blazing-fast queries to your apps. I started programming when I was 14. It adds up.

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dbt Developer Hub

MARCH 1, 2022

In this article, I will walk through forming the first analytics engineering team at Smartsheet including how momentum built around forming the team, the challenges we faced, and the solutions we developed within the first year. Introduction ​ Most writing about analytics engineering, or AE for short, assumes a team already exists.

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DataKitchen

AUGUST 9, 2021

The data industry has a wide variety of approaches and philosophies for managing data: Inman data factory, Kimball methodology, s tar schema , or the data vault pattern, which can be a great way to store and organize raw data, and more. Data mesh does not replace or require any of these.

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Cloudera

MAY 19, 2021

In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. RAPIDS brings the power of GPU compute to standard Data Science operations, be it exploratory data analysis, feature engineering or model building. Data Ingestion.

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Databand.ai

AUGUST 30, 2023

Unified DataOps represents a fresh approach to managing and synchronizing data operations across several domains, including data engineering, data science, DevOps, and analytics. Technical Challenges Choosing appropriate tools and technologies is critical for streamlining data workflows across the organization.

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Databand.ai

JUNE 8, 2023

Observability in Your Data Pipeline: A Practical Guide Eitan Chazbani June 8, 2023 Achieving observability for data pipelines means that data engineers can monitor, analyze, and comprehend their data pipeline’s behavior. Monitor total records processed or bytes transferred to ensure smooth operation.

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Databand.ai

JULY 6, 2023

Data pipelines are a series of data processing steps that enable the flow and transformation of raw data into valuable insights for businesses. Automating the processes of data engineering can ensure dependable and effective delivery of high-quality information to support decision making.

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Knowledge Hut

JANUARY 12, 2024

Cloud System Engineer A cloud system engineer is an IT professional responsible for building and maintaining an organization's cloud infrastructure. Education requirements: Individuals must have a Bachelor of Science degree in computer science, engineering or other related fields that provides similar skills to work in this role.

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Databand.ai

AUGUST 30, 2023

Data testing tools: Key capabilities you should know Helen Soloveichik August 30, 2023 Data testing tools are software applications designed to assist data engineers and other professionals in validating, analyzing and maintaining data quality. There are several types of data testing tools.

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Workfall

JULY 4, 2023

Reading Time: 8 minutes In the world of data engineering, a mighty tool called DBT (Data Build Tool) comes to the rescue of modern data workflows. Imagine a team of skilled data engineers on an exciting quest to transform raw data into a treasure trove of insights. Happy DBT-ing!

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Knowledge Hut

APRIL 25, 2023

Organizations build data ingestion architecture to make sense of the complexity in the data and derive more value from it. To learn more about it, you can check out this bootcamp for Data Engineers. What is Data Ingestion? Why Data Ingestion is Important? Why Data Ingestion is Important?

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Databand.ai

JULY 10, 2023

An observability platform is a comprehensive solution that allows data engineers to monitor, analyze, and optimize their data pipelines. By providing a holistic view of the data pipeline, observability platforms help teams rapidly identify and address issues or bottlenecks. 6 Observability Platforms You Should Know 1.

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DataKitchen

SEPTEMBER 21, 2023

Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability In a world where 97% of data engineers report burnout and crisis mode seems to be the default setting for data teams, a Zen-like calm feels like an unattainable dream.

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Workfall

JULY 18, 2023

With DBT’s materializations, our data transformations underwent a magical transformation themselves. In this blog, we’ll whisk you away on an enchanting journey through DBT materializations. So grab your wands (or keyboards), and let’s cast a spell of mastery over data transformations like never before.

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DataKitchen

MAY 4, 2023

The data industry is now adopting similar principles, such as data testing instead of test-driven development, data observability instead of observability, and functional data engineering instead of functional programming. Chris talks about the idea of a ‘domain’ as a principle of Data Mesh.

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Workfall

AUGUST 14, 2023

These tools, when combined, form a dynamic duo that streamlines and scales data engineering workflows. In this blog, we will explore the benefits of using DBT and Airflow together and how they make data pipeline management easier than ever before. In this blog, we will cover: Understanding DBT and Airflow What is DBT?

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Monte Carlo

FEBRUARY 9, 2023

In fact, with increasingly strict data regulations like GDPR and a renewed emphasis on optimizing technology costs, we’re now seeing a revitalization of “ Data Vault 2.0 ” data modeling. While data vault has many benefits, it is a sophisticated and complex methodology that can present challenges to data quality.

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ProjectPro

JULY 12, 2021

You can consider many other high-paying career options as a data enthusiast. This blog will take you through a relatively new career title in the data industry — AI Engineer. Table of Contents Why do you need to become an AI Engineer: Are AI Engineers in Demand? What is an AI Engineer?

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