Ascend.io

SEPTEMBER 14, 2023

The rise of data-intensive operations has positioned data engineering at the core of today’s organizations. As the demand to efficiently collect, process, and store data increases, data engineers have started to rely on Python to meet this escalating demand. Why Python for Data Engineering?

Data Engineering 52

Data Engineering Data Engineer Python Engineering 52

Knowledge Hut

JUNE 20, 2023

Let's find out the differences between a data scientist and a machine learning engineer below to make an informative decision. Data Engineer vs Machine Learning Engineer While there are similarities between a data engineer and a machine learning engineer, both play a key role in the technological world.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Knowledge Hut

NOVEMBER 28, 2023

The contemporary world experiences a huge growth in cloud implementations, consequently leading to a rise in demand for data engineers and IT professionals who are well-equipped with a wide range of application and process expertise. Data Engineer certification will aid in scaling up you knowledge and learning of data engineering.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

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?

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Cloud Academy

JANUARY 27, 2022

Data engineering is the process of designing and implementing solutions to collect, store, and analyze large amounts of data. The data then gets prepared in formats to be used by people such as business analysts, data analysts, and data scientists. What does a data engineer do?

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Certification Data Engineering Data Engineer Engineering 52

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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Data Engineering Data Engineer Engineering Data Warehouse 52

Towards Data Science

FEBRUARY 6, 2024

The disconnection between the operational teams immersed in the day-to-day functions and those extracting business value from data generated in the operational processes still remains a significant friction point. Searching for data Imagine being a data engineer/analyst tasked with identifying the top-selling products within your company.

Systems 76

Systems Raw Data Metadata Data Cleanse 76

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%

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

Ascend.io

APRIL 12, 2023

From this research, we developed a framework with a sequence of stages to implement data integrity quickly and measurably via data pipelines. Table of Contents Why does data integrity matter? At every level of a business, individuals must trust the data, so they can confidently make timely decisions. Let’s explore!

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Data Pipeline Data Integration Datasets Data 52

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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AWS Data Engineering Data Engineer Engineering 52

Knowledge Hut

FEBRUARY 27, 2023

A data engineer is a key member of an enterprise data analytics team and is responsible for handling, leading, optimizing, evaluating, and monitoring the acquisition, storage, and distribution of data across the enterprise. Data Engineers indulge in the whole data process, from data management to analysis.

Data Engineering 52

Data Engineering Data Engineer Database-centric Pipeline-centric 52

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.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Dataquest

APRIL 12, 2021

Data engineer, data analyst, and data scientist — these are job titles you’ll often hear mentioned together when people are talking about the fast-growing field of data science. There are plenty of other job titles in data science and data analytics too. What do data engineers do?

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Ascend.io

AUGUST 31, 2023

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. Their task is straightforward: take the raw data and transform it into a structured, coherent format.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Workfall

SEPTEMBER 18, 2023

Whether you need to integrate data from databases, APIs, cloud services, or other systems, Airbyte provides the tools to make it easier and more efficient. With its drag-and-drop interface, creating data pipelines becomes as easy as arranging blocks in a puzzle. Design your integration pipelines with flexibility in mind.

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Data Pipeline Raw Data Data Schemas Healthcare 93

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?

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

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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Pharmaceutical Raw Data Data Lake Data 98

WeCloudData

OCTOBER 19, 2021

Since 2016, WeCloudData has trained and helped thousands of students and clients level up their data skills and mature their data organizations. The client needed to build its own internal data pipeline with enough flexibility to meet the business requirements for a job market analysis platform & dashboard.

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 52

WeCloudData

OCTOBER 19, 2021

Since 2016, WeCloudData has trained and helped thousands of students and clients level up their data skills and mature their data organizations. The client needed to build its own internal data pipeline with enough flexibility to meet the business requirements for a job market analysis platform & dashboard.

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 52

Ascend.io

NOVEMBER 21, 2023

More importantly, we will contextualize ELT in the current scenario, where data is perpetually in motion, and the boundaries of innovation are constantly being redrawn. Extract The initial stage of the ELT process is the extraction of data from various source systems. What Is ELT? So, what exactly is ELT?

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

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.

Data Cleanse 52

Data Cleanse Data Pipeline Datasets Data Validation 52

Data Engineering Podcast

DECEMBER 11, 2021

In this episode he explains how it can be used to build rich and useful profiles of your users, the system architecture that powers it, and some of the ways that it is being integrated into an organization’s broader data ecosystem. constraints on data manipulation, security, privacy concerns, etc.)

Data Warehouse 100

Data Warehouse Raw Data Data Lake BI 100

Data Engineering Podcast

JUNE 26, 2022

Summary The most complicated part of data engineering is the effort involved in making the raw data fit into the narrative of the business. Your newly mimicked datasets are safe to share with developers, QA, data scientists—heck, even distributed teams around the world.

Data Management 100

Data Management Management MongoDB Scala 100

DareData

JULY 5, 2023

If you work at a relatively large company, you've seen this cycle happening many times: Analytics team wants to use unstructured data on their models or analysis. For example, an industrial analytics team wants to use the logs from raw data. If you need help to understand how these tools work, feel free to drop us a message!

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Data Lake Building Raw Data ETL Tools 52

Snowflake

AUGUST 3, 2023

Even consumer-facing businesses use Verivox’s ranking tables and tariff service to get the data they need to identify trends and better understand their customers. Prices rose massively during the recent energy crisis,” said Kevin Ruppert, Senior Data Engineer at Verivox.

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Telecommunication Insurance Raw Data Media 52

Databand.ai

AUGUST 30, 2023

Data Testing Tools: Key Capabilities and 6 Tools You Should Know Helen Soloveichik August 30, 2023 What Are Data Testing Tools? Data testing tools are software applications designed to assist data engineers and other professionals in validating, analyzing, and maintaining data quality.

Data Cleanse 52

Data Cleanse Data Validation Data Pipeline Datasets 52

Cloudera

DECEMBER 17, 2020

First and foremost, we designed the Cloudera Data Platform (CDP) to optimize every step of what’s required to go from raw data to AI use cases. CDP enables a fully integrated and seamless ML lifecycle — from data pipelines to production and everything in between. Laurence Goasduff, Gartner.

Machine Learning 83

Machine Learning Data Science Data Pipeline Raw Data 83

Databand.ai

AUGUST 30, 2023

Data Processing and Transformation Data processing and transformation involve the manipulation and conversion of raw data into a format suitable for analysis, modeling, and visualization. This may involve the use of data pipelines, data integration platforms, or data processing frameworks.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Ascend.io

JANUARY 10, 2024

This continuous adaptation ensures that your data management stays effective and compliant with current standards. Let’s dive into what this involves and how you can make it actionable in your own setting: Data Ingestion: First things first: getting the data into the system. Actionable tip? Why is this important?

Data Pipeline 52

Data Pipeline Government Data Governance Raw Data 52

Data Engineering Podcast

MARCH 4, 2018

Preamble Hello and welcome to the Data Engineering Podcast, the show about modern data infrastructure When you’re ready to launch your next project you’ll need somewhere to deploy it. To save 60% off your tickets go to dataengineeringpodcast.com/odsc-east-2018 and register.

Raw Data 100

Raw Data Machine Learning Data Pipeline Data 100

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

DataKitchen

OCTOBER 27, 2022

The first step in solving that pain is to observe what’s happening with your data and analytics ‘estate’ and stick little thermometers at various points in the process and measure. Have those thermometers check while your data and tools are running in production a few things, for example: Did the production process start?

Raw Data 52

Raw Data Data Pipeline Data Data Engineering 52

Data Engineering Podcast

JANUARY 14, 2017

Preamble Hello and welcome to the Data Engineering Podcast, the show about modern data infrastructure Go to dataengineeringpodcast.com to subscribe to the show, sign up for the newsletter, read the show notes, and get in touch. Interview with Daniel Whitenack Introduction How did you get started in the data engineering space?

Data Lake 100

Data Lake Raw Data Kafka Data Pipeline 100

Data Engineering Podcast

DECEMBER 16, 2019

Even if you already have a metadata repository this is worth a listen to learn more about the value that visibility of your data can bring to your organization. You work hard to make sure that your data is clean, reliable, and reproducible throughout the ingestion pipeline, but what happens when it gets to the data warehouse?

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Metadata PostgreSQL Datasets Data Warehouse 100

Monte Carlo

AUGUST 31, 2023

As the data analyst or engineer responsible for managing this data and making it usable, accessible, and trustworthy, rarely a day goes by without having to field some request from your stakeholders. But what happens when the data is wrong? In our opinion, data quality frequently gets a bad rep.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. What is Data Science? What are the roles and responsibilities of a Data Engineer? And many more.

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Data Engineering Data Engineer Engineering Pipeline-centric 98

Towards Data Science

MAY 3, 2023

Data Engineering Learn about slow change dimensions (SCD) and how to implement SCD Type 2 in VDK Photo by Joshua Sortino on Unsplash Data is the backbone of any organization, and in today’s fast-paced world, it is crucial to keep track of its versions. Join the #versatile-data-kit channel. Join the CNCF Slack workspace.

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Data Lake Data SQL Data Warehouse 80