Cloudera

JULY 13, 2021

After the launch of CDP Data Engineering (CDE) on AWS a few months ago, we are thrilled to announce that CDE, the only cloud-native service purpose built for enterprise data engineers, is now available on Microsoft Azure. . CDP data lifecycle integration and SDX security and governance. Key features of CDP Data Engineering.

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Data Engineering Weekly

NOVEMBER 3, 2024

The blog emphasizes the importance of starting with a clear client focus to avoid over-engineering and ensure user-centric development. impactdatasummit.com Thumbtack: What we learned building an ML infrastructure team at Thumbtack Thumbtack shares valuable insights from building its ML infrastructure team.

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Data Engineering Data Engineer Engineering Pipeline-centric 62

Snowflake

APRIL 8, 2024

The list of Top 10 semi-finalists is a perfect example: we have use cases for cybersecurity, gen AI, food safety, restaurant chain pricing, quantitative trading analytics, geospatial data, sales pipeline measurement, marketing tech and healthcare. Our sincere thanks go out to everyone who participated in this year’s competition.

Pipeline-centric 131

Pipeline-centric Food Healthcare Unstructured Data 131

DareData

JULY 29, 2020

One paper suggests that there is a need for a re-orientation of the healthcare industry to be more "patient-centric". Furthermore, clean and accessible data, along with data driven automations, can assist medical professionals in taking this patient-centric approach by freeing them from some time-consuming processes.

Data Pipeline 52

Data Pipeline Healthcare Medical Pipeline-centric 52

Data Engineering Podcast

MAY 7, 2023

However, that's also something we're re-thinking with our warehouse-centric strategy. How does reverse ETL factor into the enrichment process for profile data? Rudderstack]([link] RudderStack provides all your customer data pipelines in one platform. Let us know if you have opinions there!

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Pipeline-centric Data Lake Machine Learning Data Warehouse 130

François Nguyen

MARCH 22, 2021

TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality. The next problem will be the diversity of these mini data platforms (because of the configuration) and you even go deeper in problems with managing different technologies or version.

Technology 130

Technology Architecture Google Cloud Metadata 130

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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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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Data Pipeline ETL Tools Pipeline-centric Data Warehouse 52

Christophe Blefari

APRIL 8, 2023

At the same time Maxime Beauchemin wrote a post about Entity-Centric data modeling. In the recent years dbt simplified and revolutionised the tooling to create data models. This week I discovered SQLMesh , a all-in-one data pipelines tool. I hope he will fill the gaps. dbt, as of today, is the leading framework.

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Christophe Blefari

APRIL 8, 2023

At the same time Maxime Beauchemin wrote a post about Entity-Centric data modeling. In the recent years dbt simplified and revolutionised the tooling to create data models. This week I discovered SQLMesh , a all-in-one data pipelines tool. I hope he will fill the gaps. dbt, as of today, is the leading framework.

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Pipeline-centric Database-centric Algorithm Data 130

Data Engineering Podcast

AUGUST 13, 2022

In this episode founder Shayan Mohanty explains how he and his team are bringing software best practices and automation to the world of machine learning data preparation and how it allows data engineers to be involved in the process. Data stacks are becoming more and more complex. Data stacks are becoming more and more complex.

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Machine Learning Pipeline-centric Database-centric MongoDB 100

Christophe Blefari

SEPTEMBER 13, 2024

NVidia released Eagle a vision-centric multimodal LLM — Look at the example in the Github repo, given an image and a user input the LLM is able to answer things like "Describe the image in detail" or "Which car in the picture is more aerodynamic" based on a drawing.

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Pipeline-centric Data Python Data Science 100

Cloudera

JANUARY 24, 2023

To this end, UBL embarked on a data analytics project that would achieve its goals for an improved data environment. Next, it needed to enhance the company’s customer-centric approach for a needs-based alignment of products and services. Mr. Kashif Riaz, head of data and AI at UBL, shared his thoughts on this project. “To

Banking 80

Banking Data Analytics Pipeline-centric IT 80

Cloudera

DECEMBER 13, 2023

To enable LGIM to better utilize its wealth of data, LGIM required a centralized platform that made internal data discovery easy for all teams and could securely integrate external partners and third-party outsourced data pipelines.

Pipeline-centric 89

Pipeline-centric Professional Services BI Datasets 89

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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Confluent

SEPTEMBER 25, 2019

Of course, this is not to imply that companies will become only software (there are still plenty of people in even the most software-centric companies), just that the full scope of the business is captured in an integrated software defined process. Here, the bank loan business division has essentially become software.

Database-centric 56

Database-centric Kafka Pipeline-centric Retail 56

DataKitchen

AUGUST 27, 2021

Without DataOps, companies can employ hundreds of data professionals and still struggle. The data pipelines must contend with a high level of complexity – over seventy data sources and a variety of cadences, including daily/weekly updates and builds. That’s the power of DataOps automation.

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Data Engineering Weekly

MARCH 3, 2024

Here is the agenda, 1) Data Application Lifecycle Management - Harish Kumar( Paypal) Hear from the team in PayPal on how they build the data product lifecycle management (DPLM) systems. 3) DataOPS at AstraZeneca The AstraZeneca team talks about data ops best practices internally established and what worked and what didn’t work!!!

Data Engineering 67

Data Engineering Data Engineer Engineering Pipeline-centric 67

Dataquest

JANUARY 25, 2017

A data scientist is only as good as the data they have access to. Most companies store their data in variety of formats across databases and text files. This is where data engineers come in — they build pipelines that transform that data into formats that data scientists can use.

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Data Engineering Data Engineer Pipeline-centric Database-centric 52

Netflix Tech

JANUARY 10, 2024

The Netflix video processing pipeline went live with the launch of our streaming service in 2007. By integrating with studio content systems, we enabled the pipeline to leverage rich metadata from the creative side and create more engaging member experiences like interactive storytelling.

Process 95

Process Pipeline-centric Media Metadata 95

Data Engineering Weekly

AUGUST 25, 2024

Take Astro (the fully managed Airflow solution) for a test drive today and unlock a suite of features designed to simplify, optimize, and scale your data pipelines. Try For Free → Conference Alert: Data Engineering for AI/ML This is a virtual conference at the intersection of Data and AI.

Data Engineering 70

Data Engineering Data Engineer Engineering Database-centric 70

Ascend.io

JUNE 8, 2023

Treating data as a product is more than a concept; it’s a paradigm shift that can significantly elevate the value that business intelligence and data-centric decision-making have on the business. Data pipelines Data integrity Data lineage Data stewardship Data catalog Data product costing Let’s review each one in detail.

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Pipeline-centric Database-centric Data Ingestion Data Pipeline 52

Monte Carlo

MARCH 28, 2024

In a nutshell, DataOps engineers are responsible not only for designing and building data pipelines, but iterating on them via automation and collaboration as well. So, does this mean you should choose DataOps engineering vs. data engineering when considering your next career move? What does a DataOps engineer do? It depends!

Engineering 75

Engineering Pipeline-centric BI Google Cloud 75

Cloudera

NOVEMBER 15, 2021

Data Cascades are said to be pervasive, to lack immediate visibility, but to eventually impact the world in a negative manner. Related to the neglect of data quality, it has been observed that much of the efforts in AI have been model-centric, that is, mostly devoted to developing and improving models , given fixed data sets.

Unstructured Data 90

Unstructured Data Pipeline-centric Database-centric Entertainment 90

DataKitchen

NOVEMBER 4, 2021

These limited-term databases can be generated as needed from automated recipes (orchestrated pipelines and qualification tests) stored and managed within the process hub. . The process hub capability of the DataKitchen Platform ensures that those processes that act upon data – the tests, the recipes – are shareable and manageable.

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Process Data Process Pharmaceutical Data Lake 98

Ascend.io

MAY 7, 2024

” Key Partnership Benefits: Cost Optimization and Efficiency : The collaboration is poised to reduce IT and data management costs significantly, including an up to 68% reduction in data stack spend and the ability to build data pipelines 7.5x ABOUT ASCEND.IO Learn more at Ascend.io or follow us @ascend_io.

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Pipeline-centric Data Cleanse Data Security Data Pipeline 52

Towards Data Science

MAY 19, 2023

Business users are unable to find and access data assets critical to their workflows. Data engineers spend countless hours troubleshooting broken pipelines. The data team is constantly burning out and has a high employee turnover. Stakeholders fail to see the ROI behind expensive data initiatives.

Pipeline-centric 104

Pipeline-centric Data Software Engineer Software Engineering 104

Monte Carlo

MAY 30, 2024

It can involve prompt engineering, vector databases like Pinecone , embedding vectors and semantic layers, data modeling, data orchestration, and data pipelines – all tailored for RAG. But when it’s done right, RAG can add an incredible amount of value to AI-powered data products. What is Fine Tuning?

Pipeline-centric 52

Pipeline-centric Database-centric Datasets Data Pipeline 52

Ascend.io

OCTOBER 20, 2023

The Nuances of Snowflake Costing Snowflake’s pricing strategy is an exemplification of its user-centric approach: pay for what you use. The Predictability of Pipelines In stark contrast to ad-hoc queries, pipelines are where cost optimization efforts can yield significant dividends.

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Pipeline-centric IT Data Pipeline Bytes 52

Pipeline Data Engineering

MARCH 2, 2022

Analytics Stacks for Startups Jan Katins, Senior IT Consultant/Data Engineer, kreuzwerker GmbH The stack should be relatively fast to implement (two weeks is possible), so you can quickly reap the benefits of having a data warehouse and BI Tooling in place or upload enriched data back to operational systems.

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Pipeline-centric BI Consulting Data Warehouse 52

Snowflake

JUNE 28, 2023

Streamlit gives data scientists and Python developers the ability to quickly turn data and models into interactive, enterprise-ready applications. Simplified streaming pipelines in Snowflake We are expanding our streaming capabilities with Dynamic Tables (public preview). We also announced the private preview of Snowflake CLI.

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Pipeline-centric Programming Language Python Government 59

Ascend.io

JUNE 21, 2023

Cost Savings : Insights derived from data products can directly lead to cost savings in the business. Risk Reduction : Data-centric decision-making can also contribute to risk reduction. In the case of data products, these are networks of data pipelines, which makes them an integral part of your modern operational machinery.

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Pipeline-centric Data Pipeline Metadata Data 52

Knowledge Hut

JUNE 20, 2023

Factors Data Engineer Machine Learning Definition Data engineers create, maintain, and optimize data infrastructure for data. In addition, they are responsible for developing pipelines that turn raw data into formats that data consumers can use easily. Assess the needs and goals of the business.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

ThoughtSpot

OCTOBER 18, 2024

It aims to explain how we transformed our development practices with a data-centric approach and offers recommendations to help your teams address similar challenges in your software development lifecycle. This approach ensured comprehensive data extraction while handling various edge cases and log formats.

Building 52

Building Process Pipeline-centric Database-centric 52

Data Engineering Weekly

JULY 2, 2023

Data Engineering Weekly Is Brought to You by RudderStack RudderStack Profiles takes the SaaS guesswork, and SQL grunt work out of building complete customer profiles, so you can quickly ship actionable, enriched data to every downstream team. See how it works today.

Data Engineering 52

Data Engineering Data Engineer Engineering Database-centric 52

The Modern Data Company

DECEMBER 29, 2022

This means moving beyond product-centric thinking to a data-driven customer experience model that’s consistent across all channels. Next, the wealth management industry is also shifting away from a product focus to a client-centric model. DataOS is the world’s first operating system.

Banking 52

Banking Pipeline-centric Building Finance 52

Knowledge Hut

NOVEMBER 2, 2023

An Azure Data Engineer is a professional responsible for designing, implementing, and managing data solutions using Microsoft's Azure cloud platform. They work with various Azure services and tools to build scalable, efficient, and reliable data pipelines, data storage solutions, and data processing systems.

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