Ascend.io

FEBRUARY 28, 2024

The rise of generative AI is changing more than just technology; it’s reshaping our professional landscapes — and yes, data engineering is directly experiencing the impact. How does AI recalibrate the workload and priorities of data teams? How can data engineers harness the power of AI?

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Monte Carlo

JANUARY 25, 2023

In this article, Chad Sanderson , Head of Product, Data Platform , at Convoy and creator of Data Quality Camp , introduces a new application of data contracts: in your data warehouse. In the last couple of posts , I’ve focused on implementing data contracts in production services.

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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?

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Data Engineering Data Engineer Engineering Google Cloud 52

Data Engineering Weekly

JUNE 4, 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. Can we test SQL business logic during the development phase itself?

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Data Engineering Data Engineer Engineering Medical 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.

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Data Engineering Data Engineer NoSQL Engineering 52

ProjectPro

AUGUST 11, 2021

“Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Data Warehouse Architecture What is a Data lake?

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Data Engineering Weekly

DECEMBER 18, 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. Given the characteristic, are we having a “Big Data” problem?

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Data Engineering Data Engineer Engineering Relational Database 52

Towards Data Science

DECEMBER 23, 2023

Photo by Ian Taylor on Unsplash This tutorial guides you through an analytics use case, analyzing semi-structured data with Spark SQL. We’ll start with the data engineering process, pulling data from an API and finally loading the transformed data into a data lake (represented by MinIO ).

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SQL Data Analytics Hadoop Raw Data 75

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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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

Knowledge Hut

DECEMBER 29, 2023

Data Engineering is the most demanding and fruitful career option, as most companies rely on their data to make significant growth decisions. First, they gather all the data from different resources and segregate it into fruitful data sets. The highlight feature of this data engineer toolkit is spark streaming.

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Knowledge Hut

MAY 4, 2023

Data engineering is a prominent yet emerging technological field that is currently enjoying high demand. Salaries for data engineers vary across the globe, depending on various factors such as location, experience, skills and Data Engineer training and certifications taken by the professionals.

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Data Engineering Data Engineer Engineering Banking 52

Monte Carlo

JANUARY 25, 2023

When it comes to the question of building or buying your data stack, there’s never a one-size-fits-all solution for every data team—or every component of your data stack. Data storage and compute are very much the foundation of your data platform. Let’s jump in! So, let’s take a look at each in a bit more detail.

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Data Engineering Podcast

JUNE 17, 2021

In this episode he shares the goals of the Unstruk Data Warehouse, how it is architected to extract asset metadata and build a searchable knowledge graph from the information, and the myriad ways that the system can be used. Hightouch is the easiest way to sync data into the platforms that your business teams rely on.

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Unstructured Data Data Warehouse Metadata Media 100

Silectis

JANUARY 3, 2021

If you’re new to data engineering or are a practitioner of a related field, such as data science, or business intelligence, we thought it might be helpful to have a handy list of commonly used terms available for you to get up to speed. Big Query Google’s cloud data warehouse.

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Data Engineering Data Engineer Engineering Hadoop 40

Knowledge Hut

FEBRUARY 16, 2023

Demand for data engineers is at a peak today globally due to the massive amount of data that companies accumulate and work with this data to draw actionable insights and make better business decisions. To do that, the generated data must be interpreted to be understood by the end user. What Does a Data Engineer Do?

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Data Engineering Data Engineer Engineering Healthcare 52

Rockset

JANUARY 5, 2022

So I don’t fault you for resisting my message, which is that the SQL database that came of age in the 80s still has a critical role to play today in moving data-driven companies from batch to real-time analytics. In many tech circles, SQL databases remain synonymous with old-school on-premises databases like Oracle or DB2.

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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.

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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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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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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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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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Monte Carlo

FEBRUARY 15, 2023

On the surface, the promise of scaling storage and processing is readily available for databases hosted on AWS RDS, GCP cloud SQL and Azure to handle these new workloads. Cloud data warehouses solve these problems. What is a data warehouse? Let’s imagine a scenario where you’re collecting orders information.

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Data Warehouse Unstructured Data AWS Business Intelligence 52

Cloudera

APRIL 1, 2024

Cloudera, a leader in big data analytics, provides a unified Data Platform for data management, AI, and analytics. Our customers run some of the world’s most innovative, largest, and most demanding data science, data engineering, analytics, and AI use cases, including PB-size generative AI workloads.

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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. Read More: What is ETL?

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ProjectPro

SEPTEMBER 26, 2021

Big Data Engineer is one of the most popular job profiles in the data industry. This blog on Big Data Engineer salary gives you a clear picture of the salary range according to skills, countries, industries, job titles, etc. Big Data gets over 1.2 What does a big data engineer do?

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phData: Data Engineering

SEPTEMBER 19, 2023

A rigid data model such as Kimball or Data Vault would ruin this flexibility and essentially transform your data lake into a data warehouse. However, some flexible data modeling techniques can be used to allow for some organization while maintaining the ease of new data additions.

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Knowledge Hut

SEPTEMBER 26, 2023

Microsoft Azure's Azure Synapse, formerly known as Azure SQL Data Warehouse, is a complete analytics offering. Designed to tackle the challenges of modern data management and analytics, Azure Synapse brings together the worlds of big data and data warehousing into a unified and seamlessly integrated platform.

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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.

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AltexSoft

JUNE 26, 2023

Both data integration and ingestion require building data pipelines — series of automated operations to move data from one system to another. For this task, you need a dedicated specialist — a data engineer or ETL developer. Data engineering explained in 14 minutes.

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Ascend.io

NOVEMBER 21, 2023

The emergence of cloud data warehouses, offering scalable and cost-effective data storage and processing capabilities, initiated a pivotal shift in data management methodologies. Extract The initial stage of the ELT process is the extraction of data from various source systems.

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Monte Carlo

JULY 19, 2023

Before you can model the data for your stakeholders, you need a place to collect and store it. In simple terms, data transformation refers to the process of converting all that data from a variety of disparate formats into something consistent and useful for modeling. million per year.

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Towards Data Science

JULY 21, 2023

Before you can model the data for your stakeholders, you need a place to collect and store it. In simple terms, data transformation refers to the process of converting all that data from a variety of disparate formats into something consistent and useful for modeling. Image courtesy of author. million per year.

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ProjectPro

JANUARY 24, 2023

With the global cloud data warehousing market likely to be worth $10.42 billion by 2026, cloud data warehousing is now more critical than ever. Cloud data warehouses offer significant benefits to organizations, including faster real-time insights, higher scalability, and lower overhead expenses.

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Knowledge Hut

MAY 31, 2023

Companies utilize different approaches to deal with data in order to extract information from structured, semi-structured, or unstructured data sets. Business Intelligence is one such approach that helps professionals to extract valuable information from structured data.

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Business Intelligence BI Business Analyst Consulting 52

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. Data warehouse vs. data lake in a nutshell.

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Data Lake Architecture IT Amazon Web Services 52

Knowledge Hut

JANUARY 29, 2024

In contrast, ETL is primarily employed by DW/ETL developers responsible for data integration between source systems and reporting layers. Data Structure: Data wrangling deals with varied and complex data sets, which may include unstructured or semi-structured data. Frequently Asked Questions (FAQs) 1.

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