Dataquest

NOVEMBER 4, 2019

If you’ve ever wanted to learn Python online with streaming data, or data that changes quickly, you may be familiar with the concept of a data pipeline. Data pipelines allow you transform data from one representation to another through a series of steps. We store the raw log data to a database.

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Data Pipeline Python Building Raw Data 52

DataKitchen

SEPTEMBER 21, 2023

This results in rallying 26 team members—likely the cream of the crop—to spend an entire day investigating the problem, only to discover that a single blank field passed through the data pipeline was the culprit. This existing paradigm fails to address the challenges and intricacies of “Data in Use.”

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Raw Data Data Business Intelligence High Quality Data 70

Ascend.io

FEBRUARY 6, 2023

At this level, users configure team members, connections to other systems, and event notifications. Data Flow – is an individual data pipeline. Data Flows include the ingestion of raw data, transformation via SQL and python, and sharing of finished data products.

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Cloud Data Ingestion Raw Data Data Pipeline 52

Ascend.io

FEBRUARY 6, 2023

At this level, users configure team members, connections to other systems, and event notifications. Data Flow – is an individual data pipeline. Data Flows include the ingestion of raw data, transformation via SQL and python, and sharing of finished data products.

Cloud 52

Cloud Data Ingestion Raw Data Data Pipeline 52

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. 2023 predictions from the panel are; Unified metadata becomes kingmaker.

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Data Engineering Data Engineer Engineering Metadata 52

AltexSoft

DECEMBER 23, 2022

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. Scalability. Incremental extraction.

Process 52

Process Building Raw Data Data Lake 52

Ascend.io

DECEMBER 11, 2023

Here’s the deal: for data to truly drive your business forward, you need a reliable and scalable system to keep it moving without hiccups. In other words, you need data orchestration. In this article, we’ll break down what data orchestration is, its significance, and how it differs from data pipeline orchestration.

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Monte Carlo

AUGUST 30, 2023

Run the test again to validate that the initial problem is solved and that your data meets your quality and accuracy standards. Schedule and automate Just like schema tests, custom data tests in dbt are typically not run just once but are incorporated into your regular data pipeline to ensure ongoing data quality.

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SQL Datasets Database High Quality Data 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.

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Process Data Pipeline Data Warehouse AWS 52

AltexSoft

JUNE 26, 2023

Data collection revolves around gathering raw data from various sources, with the objective of using it for analysis and decision-making. It includes manual data entries, online surveys, extracting information from documents and databases, capturing signals from sensors, and more.

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Data Collection Machine Learning Unstructured Data Non-relational Database 52

ProjectPro

AUGUST 11, 2021

The data warehouse layer consists of the relational database management system (RDBMS) that contains the cleaned data and the metadata, which is data about the data. The RDBMS can either be directly accessed from the data warehouse layer or stored in data marts designed for specific enterprise departments.

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Data Lake Data Warehouse Cloud Hadoop 52

ProjectPro

AUGUST 24, 2021

Within no time, most of them are either data scientists already or have set a clear goal to become one. Nevertheless, that is not the only job in the data world. And, out of these professions, this blog will discuss the data engineering job role. This big data project discusses IoT architecture with a sample use case.

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Data Engineering Data Engineer Coding Project 52

ProjectPro

JULY 8, 2021

Kafka Streams and Kafka Connect were used to keep track of the threat of the COVID-19 virus and analyze the data for a more thorough response on local, state, and federal levels. Kafka is an integral part of Netflix’s real-time monitoring and event-processing pipeline. Table of Contents Why is Apache Kafka so popular?

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Kafka Architecture IT Big Data 40

Data Engineering Podcast

JANUARY 28, 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% of your tickets go to data engineering podcast.com slash o d s c dash East dash 2018 and register.

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Data Project Electronics Data Management 100

ProjectPro

JANUARY 31, 2022

Provides Powerful Computing Resources for Data Processing Before inputting data into advanced machine learning models and deep learning tools, data scientists require sufficient computing resources to analyze and prepare it. They just need to deliver their data and hand it over to Snowflake to manage.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

DoorDash Engineering

APRIL 12, 2023

As we mentioned in our previous blog , we began with a ‘Bring Your Own SQL’ method, in which data scientists checked in ad-hoc Snowflake (our primary data warehouse) SQL files to create metrics for experiments, and metrics metadata was provided as JSON configs for each experiment.

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SQL Metadata Raw Data Government 82

AltexSoft

MARCH 14, 2023

Moreover, over 20 percent of surveyed companies were found to be utilizing 1,000 or more data sources to provide data to analytics systems. These sources commonly include databases, SaaS products, and event streams. Databases store key information that powers a company’s product, such as user data and product data.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Monte Carlo

AUGUST 19, 2023

Image courtesy of Fivetran While you may have heard the term “ zero-ETL ” in reference to integrating data from one location to another without the need for data pipelines, the widespread adoption of this practice is still quite a ways into the future. Image courtesy of Monte Carlo.

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Building BI Data Lake Data Governance 52