Ascend.io

AUGUST 22, 2023

The demands of building, scaling, and maintaining data pipelines have grown increasingly complex and error-prone. Data engineers are now drowning in repetitive tasks, aspiring to drive data-backed decisions. Traditional approaches to building these pipelines have showcased their vulnerabilities.

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DareData

JULY 29, 2020

With these points in mind, I argue that the biggest hurdle to the widespread adoption of these advanced techniques in the healthcare industry is not intrinsic to the industry itself, or in any way related to its practitioners or patients, but simply the current lack of high-quality data pipelines. What makes a good Data Pipeline?

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Data Pipeline Healthcare Medical Pipeline-centric 52

Workfall

AUGUST 14, 2023

Reading Time: 7 minutes In today’s data-driven world, efficient data pipelines have become the backbone of successful organizations. These pipelines ensure that data flows smoothly from various sources to its intended destinations, enabling businesses to make informed decisions and gain valuable insights.

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Grouparoo

OCTOBER 26, 2021

As a result, data has to be moved between the source and destination systems and this is usually done with the aid of data pipelines. What is a Data Pipeline? A data pipeline is a set of processes that enable the movement and transformation of data from different sources to destinations.

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Data Pipeline ETL Tools Data Warehouse ETL System 52

Databand.ai

JULY 6, 2023

7 Data Pipeline Examples: ETL, Data Science, eCommerce, and More Joseph Arnold July 6, 2023 What Are Data Pipelines? Data pipelines are a series of data processing steps that enable the flow and transformation of raw data into valuable insights for businesses.

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Data Pipeline Data Science Raw Data Media 52

ProjectPro

DECEMBER 7, 2021

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. Table of Contents What is a Data Pipeline? The Importance of a Data Pipeline What is an ETL Data Pipeline?

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Data Pipeline Architecture Kafka AWS 52

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. This is part of a series of articles about data observability.

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Ascend.io

JANUARY 2, 2024

But let’s be honest, creating effective, robust, and reliable data pipelines, the ones that feed your company’s reporting and analytics, is no walk in the park. From building the connectors to ensuring that data lands smoothly in your reporting warehouse, each step requires a nuanced understanding and strategic approach.

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Data Pipeline Building Raw Data Data Warehouse 52

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

Towards Data Science

FEBRUARY 6, 2024

As you do not want to start your development with uncertainty, you decide to go for the operational raw data directly. Accessing Operational Data I used to connect to views in transactional databases or APIs offered by operational systems to request the raw data. Does it sound familiar?

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Ascend.io

JULY 28, 2023

Data pipelines are integral to business operations, regardless of whether they are meticulously built in-house or assembled using various tools. As companies become more data-driven, the scope and complexity of data pipelines inevitably expand. Ready to fortify your data management practice?

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Data Pipeline Architecture Lambda Architecture Data Architecture 52

Monte Carlo

APRIL 24, 2023

Data ingestion When we think about the flow of data in a pipeline, data ingestion is where the data first enters our platform. There are two primary types of raw data. And data orchestration tools are generally easy to stand-up for initial use-cases. Missed Nishith’s 5 considerations?

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Data Pipeline Building Data Ingestion BI 52

Ascend.io

AUGUST 29, 2023

A star-studded baseball team is analogous to an optimized “end-to-end data pipeline” — both require strategy, precision, and skill to achieve success. Just as every play and position in baseball is key to a win, each component of a data pipeline is integral to effective data management.

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Data Pipeline Pipeline-centric Database-centric Data Ingestion 52

Snowflake

JUNE 6, 2024

Faster, easier AI/ML and data engineering workflows Explore, analyze and visualize data using Python and SQL. Discover valuable business insights through exploratory data analysis. Develop scalable data pipelines and transformations for data engineering.

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Netflix Tech

NOVEMBER 14, 2023

We’ll discuss batch data processing, the limitations we faced, and how Psyberg emerged as a solution. Furthermore, we’ll delve into the inner workings of Psyberg, its unique features, and how it integrates into our data pipelining workflows. The fact tables then feed downstream intraday pipelines that process the data hourly.

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Data Engineering Data Engineer Engineering Metadata 108

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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Snowflake

MAY 23, 2024

Right now we’re focused on raw data quality and accuracy because it’s an issue at every organization and so important for any kind of analytics or day-to-day business operation that relies on data — and it’s especially critical to the accuracy of AI solutions, even though it’s often overlooked.

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Data Pipeline Raw Data Data Schemas Technology 105

Hevo

FEBRUARY 15, 2023

After the hustle and bustle of extracting data from multiple sources, you have finally loaded all your data to a single source of truth like the Snowflake data warehouse. However, data modeling is still challenging and critical for transforming your raw data into any analysis-ready form to get insights.

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Data Pipeline Building Raw Data Data Warehouse 59

Monte Carlo

JUNE 14, 2023

In this post, we will help you quickly level up your overall knowledge of data pipeline architecture by reviewing: Table of Contents What is data pipeline architecture? Why is data pipeline architecture important? What is data pipeline architecture? Why is data pipeline architecture important?

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Data Pipeline Architecture Data Lake Data Warehouse 52

DataKitchen

JULY 27, 2023

The Ten Standard Tools To Develop Data Pipelines In Microsoft Azure. While working in Azure with our customers, we have noticed several standard Azure tools people use to develop data pipelines and ETL or ELT processes. We counted ten ‘standard’ ways to transform and set up batch data pipelines in Microsoft Azure.

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Data Pipeline BI Machine Learning Data Preparation 52

dbt Developer Hub

OCTOBER 7, 2024

In machine learning, a data scientist derives features from various data sources to build a model that makes predictions based on historical data. Integration with data pipelines — Teams that have already built data pipelines in dbt can continue to use these with the Snowflake Feature Store.

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Data Pipeline Datasets Machine Learning Python 52

Edureka

APRIL 14, 2025

Microsoft offers a leading solution for business intelligence (BI) and data visualization through this platform. It empowers users to build dynamic dashboards and reports, transforming raw data into actionable insights. Its flexibility suits advanced users creating end-to-end data solutions.

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BI Business Intelligence Raw Data Retail 40

Data Engineering Podcast

JANUARY 14, 2017

Given that you can version your data and track all of the modifications made to it in a manner that allows for traversal of those changesets, how much additional storage is necessary over and above the original capacity needed for the raw data? What are some things that users should be aware of to help mitigate this?

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Data Lake Raw Data Kafka Data Engineering 100

ThoughtSpot

MARCH 5, 2024

Managing complex data pipelines is a major challenge for data-driven organizations looking to accelerate analytics initiatives. When created, Snowflake materializes query results into a persistent table structure that refreshes whenever underlying data changes. Now, that’s changing.

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BI Datasets SQL Raw Data 111

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

ThoughtSpot

SEPTEMBER 6, 2023

Those coveted insights live at the end of a process lovingly known as the data pipeline. The pathway from ETL to actionable analytics can often feel disconnected and cumbersome, leading to frustration for data teams and long wait times for business users. Keep reading to see how it works.

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Data Workflow Raw Data Data Lake Business Intelligence 106

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. Go to dataengineeringpodcast.com to subscribe to the show, sign up for the newsletter, read the show notes, and get in touch.

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Raw Data Machine Learning Data Data Engineering 100

Workfall

SEPTEMBER 18, 2023

It’s designed to be user-friendly, customizable, and extensible, making it a valuable tool for data engineers, analysts, and data-driven organizations looking to streamline their data pipelines. With its drag-and-drop interface, creating data pipelines becomes as easy as arranging blocks in a puzzle.

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Data Pipeline Raw Data Data Schemas Healthcare 93

Towards Data Science

MAY 14, 2024

Dataform enables the application of software engineering best practices such as testing, environments, version control, dependencies management, orchestration and automated documentation to data pipelines. It is a serverless, SQL workflow orchestration workhorse within GCP.

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Data Engineering Podcast

DECEMBER 11, 2021

In the same way that application performance monitoring ensures reliable software and keeps application downtime at bay, Monte Carlo solves the costly problem of broken data pipelines. constraints on data manipulation, security, privacy concerns, etc.) How does Unomi help with the new third party data restrictions ?

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Cloudera

JANUARY 20, 2021

The six steps are: Data Collection – data ingestion and monitoring at the edge (whether the edge be industrial sensors or people in a brick and mortar retail store). Data Enrichment – data pipeline processing, aggregation & management to ready the data for further refinement.

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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 the role of a Data Engineer? Data scientists and data Analysts depend on data engineers to build these data pipelines.

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Data Engineering Data Engineer Engineering Hadoop 98

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.

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Machine Learning Data Science Data Pipeline Raw Data 82

WeCloudData

OCTOBER 19, 2021

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. The client intends to build on and improve this data pipeline by moving towards a more serverless architecture and adding DevOps tools & workflows.

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WeCloudData

OCTOBER 19, 2021

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. The client intends to build on and improve this data pipeline by moving towards a more serverless architecture and adding DevOps tools & workflows.

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Consulting Raw Data Data Lake Data Pipeline 52

Data Engineering Podcast

DECEMBER 16, 2019

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? Dataform picks up where your ETL jobs leave off, turning raw data into reliable analytics.

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Metadata PostgreSQL Datasets Data Warehouse 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.

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Data Management Management MongoDB MySQL 100