Monte Carlo

FEBRUARY 20, 2024

At the heart of every data-driven decision is a deceptively simple question: How do you get the right data to the right place at the right time? The growing field of data ingestion tools offers a range of answers, each with implications to ponder. Fivetran Image courtesy of Fivetran.

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Monte Carlo

MARCH 14, 2023

Data ingestion is the process of collecting data from various sources and moving it to your data warehouse or lake for processing and analysis. It is the first step in modern data management workflows. Table of Contents What is Data Ingestion? Decision making would be slower and less accurate.

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Databand.ai

JUNE 28, 2023

Data Pipeline Observability: A Model For Data Engineers Eitan Chazbani June 29, 2023 Data pipeline observability is your ability to monitor and understand the state of a data pipeline at any time. We believe the world’s data pipelines need better data observability.

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Databand.ai

JULY 19, 2023

Complete Guide to Data Ingestion: Types, Process, and Best Practices Helen Soloveichik July 19, 2023 What Is Data Ingestion? Data Ingestion is the process of obtaining, importing, and processing data for later use or storage in a database. In this article: Why Is Data Ingestion Important?

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Knowledge Hut

JULY 3, 2023

This is where real-time data ingestion comes into the picture. Data is collected from various sources such as social media feeds, website interactions, log files and processing. This refers to Real-time data ingestion. To achieve this goal, pursuing Data Engineer certification can be highly beneficial.

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Hevo

APRIL 19, 2024

A fundamental requirement for any data-driven organization is to have a streamlined data delivery mechanism. With organizations collecting data at a rate like never before, devising data pipelines for adequate flow of information for analytics and Machine Learning tasks becomes crucial for businesses.

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Data Engineering Podcast

SEPTEMBER 11, 2022

Building reliable data pipelines is a complex and costly undertaking with many layered requirements. In order to reduce the amount of time and effort required to build pipelines that power critical insights Manish Jethani co-founded Hevo Data. Data stacks are becoming more and more complex. In fact, while only 3.5%

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Team Data Science

MAY 10, 2020

I can now begin drafting my data ingestion/ streaming pipeline without being overwhelmed. With careful consideration and learning about your market, the choices you need to make become narrower and more clear.

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Ascend.io

DECEMBER 19, 2022

We hope the real-time demonstrations of Ascend automating data pipelines were a real treat—a long with the special edition T-Shirt designed specifically for the show (picture of our founder and CEO rocking the t-shirt below). Thank you to the hundreds of AWS re:Invent attendees who stopped by our booth!

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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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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. Data ingestion When we think about the flow of data in a pipeline, data ingestion is where the data first enters our platform.

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Snowflake

JUNE 4, 2024

Snowflake’s new Python API (GA soon) simplifies data pipelines and is readily available through pip install snowflake. Additionally, Dynamic Tables are a new table type that you can use at every stage of your processing pipeline. Interact with Snowflake objects directly in Python. Automate or code, the choice is yours.

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Ascend.io

MAY 31, 2023

In the modern world of data engineering, two concepts often find themselves in a semantic tug-of-war: data pipeline and ETL. Fast forward to the present day, and we now have data pipelines. Data Ingestion Data ingestion is the first step of both ETL and data pipelines.

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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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Ascend.io

MAY 8, 2023

The costs of developing and running data pipelines are coming under increasing scrutiny because the bills for infrastructure and data engineering talent are piling up. For data teams, it is time to ask: “How can we have an impact on these runaway costs and still deliver unprecedented business value?”

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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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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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Ascend.io

MARCH 17, 2023

These engineering functions are almost exclusively concerned with data pipelines, spanning ingestion, transformation, orchestration, and observation — all the way to data product delivery to the business tools and downstream applications. Pipelines need to grow faster than the cost to run them.

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Ascend.io

MARCH 17, 2023

These engineering functions are almost exclusively concerned with data pipelines, spanning ingestion, transformation, orchestration, and observation — all the way to data product delivery to the business tools and downstream applications. Pipelines need to grow faster than the cost to run them.

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Snowflake

JUNE 13, 2024

But at Snowflake, we’re committed to making the first step the easiest — with seamless, cost-effective data ingestion to help bring your workloads into the AI Data Cloud with ease. Like any first step, data ingestion is a critical foundational block. Ingestion with Snowflake should feel like a breeze.

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Snowflake

MARCH 2, 2023

Snowflake enables organizations to be data-driven by offering an expansive set of features for creating performant, scalable, and reliable data pipelines that feed dashboards, machine learning models, and applications. But before data can be transformed and served or shared, it must be ingested from source systems.

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Cloudera

AUGUST 13, 2021

Rather than collecting every single event and analyzing later, it would make sense to identify the important data as it is being collected. Let’s transform the first mile of the data pipeline. By modernizing the data flow, the enterprise got better insights into the business. What product can help collect events only?

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Cloudera

FEBRUARY 8, 2021

Below is the entire set of steps in the data lifecycle, and each step in the lifecycle will be supported by a dedicated blog post(see Fig. 1): Data Collection – data ingestion and monitoring at the edge (whether the edge be industrial sensors or people in a vehicle showroom).

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Ascend.io

MARCH 2, 2023

It won with ease of use by our analysts, the comprehensive scope of its automation, and the speed of end-to-end pipeline development. Terry Dougal Intelligent Data Pipelines at Audacy Instead of hiring more data engineers to patch over all the tooling with more bespoke code, Terry shifted gears and looked for a new solution.

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Ascend.io

MARCH 2, 2023

It won with ease of use by our analysts, the comprehensive scope of its automation, and the speed of end-to-end pipeline development. Terry Dougal Intelligent Data Pipelines at Audacy Instead of hiring more data engineers to patch over all the tooling with more bespoke code, Terry shifted gears and looked for a new solution.

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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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Rockset

OCTOBER 11, 2022

In this blog, we’ll compare and contrast how Elasticsearch and Rockset handle data ingestion as well as provide practical techniques for using these systems for real-time analytics. With the aliases API, it is still tricky to keep the new index in sync with the latest data.

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Data Engineering Weekly

SEPTEMBER 18, 2024

The advent of data lakes has changed the landscape of data infrastructure in two fundamental ways: 1. Decoupling of Storage and Compute : Data lakes allow observability tools to run alongside core data pipelines without competing for resources by separating storage from compute resources.

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Snowflake

OCTOBER 16, 2024

Digital advertiser switches from Teradata and boosts performance by 30% Core Digital Media originally relied on its outdated Teradata appliance for its increased MicroStrategy and Tableau reporting, data science activity, and evolving data pipeline. Core Digital Media’s BI team began evaluating infrastructure enhancements.

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DataKitchen

NOVEMBER 5, 2024

When data reaches the Gold layer, it is highly curated and structured, offering a single version of the truth for decision-makers across the organization. We have also seen a fourth layer, the Platinum layer , in companies’ proposals that extend the Data pipeline to OneLake and Microsoft Fabric.

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Ascend.io

AUGUST 15, 2023

You require a comprehensive solution that addresses every facet, from ingestion and transformation to orchestration and reverse ETL. It’s no surprise, then, that the quest for Fivetran alternatives is on the rise as organizations set their sights on a more holistic data approach.

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Analytics Vidhya

FEBRUARY 20, 2023

Introduction Azure data factory (ADF) is a cloud-based data ingestion and ETL (Extract, Transform, Load) tool. The data-driven workflow in ADF orchestrates and automates data movement and data transformation.

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Databand.ai

AUGUST 30, 2023

DataOps , short for data operations, is an emerging discipline that focuses on improving the collaboration, integration, and automation of data processes across an organization. These tools help organizations implement DataOps practices by providing a unified platform for data teams to collaborate, share, and manage their data assets.

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Data Engineering Podcast

NOVEMBER 20, 2022

Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code. Monitoring data quality, tracing incidents, and testing changes can be daunting and often takes hours to days or even weeks. And don’t forget to thank them for their continued support of this show!

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Snowflake

JANUARY 9, 2024

Data cloud integration: This comprehensive solution begins with the Snowflake Data Cloud as a persistent data layer, which makes data more accessible for organizations to get started with the platform. Data ingestion: Hakkoda leads the entire data ingestion process.

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Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows.

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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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