Knowledge Hut

NOVEMBER 17, 2023

The demand for data-related professions, including data engineering, has indeed been on the rise due to the increasing importance of data-driven decision-making in various industries. Becoming an Azure Data Engineer in this data-centric landscape is a promising career choice.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Data Engineering Weekly

APRIL 16, 2023

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make collecting data from every application, website, and SaaS platform easy, then activating it in your warehouse and business tools. 🍒 We'll send exclusive The Data Stack Show swag just for participating!

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

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?

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Data Engineering Data Engineer Python 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.

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Data Engineering Data Engineer Database-centric Pipeline-centric 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

Grouparoo

OCTOBER 6, 2021

It was a fun experience and I think we made a good choice by picking 97 Things Every Data Engineer Should Know. This provided a nice overview of the breadth of topics that are relevant to data engineering including data warehouses/lakes, pipelines, metadata, security, compliance, quality, and working with other teams.

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Data Engineering Data Engineer Engineering Pipeline-centric 52

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.

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Data Engineering Podcast

AUGUST 13, 2022

Summary Data engineers have typically left the process of data labeling to data scientists or other roles because of its nature as a manual and process heavy undertaking, focusing instead on building automation and repeatable systems. Data stacks are becoming more and more complex.

Machine Learning 100

Machine Learning Pipeline-centric Database-centric MongoDB 100

Christophe Blefari

APRIL 8, 2023

The only normalisation I did was back at the engineering school while learning SQL with Normal Forms. Actually what I cared was physical storage, data formats, logical partitioning or indexing. I still firmly believe that this is not the role of a data engineer. Data modeling should not be a required data engineer skill.

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Christophe Blefari

APRIL 8, 2023

The only normalisation I did was back at the engineering school while learning SQL with Normal Forms. Actually what I cared was physical storage, data formats, logical partitioning or indexing. I still firmly believe that this is not the role of a data engineer. Data modeling should not be a required data engineer skill.

Pipeline-centric 130

Pipeline-centric Database-centric Algorithm Data 130

DataKitchen

FEBRUARY 21, 2023

On 24 January 2023, Gartner released the article “ 5 Ways to Enhance Your Data Engineering Practices.” Data team morale is consistent with DataKitchen’s own research. We surveyed 600 data engineers , including 100 managers, to understand how they are faring and feeling about the work that they are doing.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

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

Snowflake

JUNE 28, 2023

At Snowflake, we’re helping data scientists, data engineers, and application developers build faster and more efficiently in the Data Cloud. The end-to-end process requires collaboration across many data, engineering and business teams in order to capitalize on the value that can be captured from AI-powered insights.

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Pipeline-centric Programming Language Python Government 57

Pipeline Data Engineering

MARCH 2, 2022

Data engineering salon. News and interesting reads about the world of data. The Unbundling of Airflow Gorkem Yurtseven, Co-Founder, Features and Labels A diverse set of tools is unbundling Airflow and this diversity is causing substantial fragmentation in modern data stack. What the hell happened?

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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.

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Architecture Technology Google Cloud Metadata 130

ProjectPro

DECEMBER 16, 2021

Are you a newbie in the data science domain ready to embark on a rewarding journey but are confused between the roles of a Machine Learning Engineer vs Data Scientist? Read this article to understand the significant differences and similarities between a machine learning engineer and a data scientist.

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Machine Learning Engineering Pipeline-centric 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

Databand.ai

JULY 19, 2023

This helps to enhance data quality, facilitate data governance, and enable regulatory compliance. Notable Data Lineage Tools and Solutions Let’s take a look at several notable data lineage tools that can improve the quality and efficiency of your data pipeline.

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Pipeline-centric Data Governance Metadata Government 52

DataKitchen

AUGUST 27, 2021

It implemented hundreds of schema and data set changes per week without introducing errors. Arguably the most agile and effective data analytics capability in the pharmaceutical industry was accomplished cost-effectively, with a data engineering team of seven and another 10-12 data analysts.

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Pharmaceutical Pipeline-centric Data Lake Data Analytics 98

Cloudera

NOVEMBER 15, 2021

Now let’s explore some of the challenges that copious amounts of data bring to the AI, business, and engineering communities. The challenges of data. Data facilitates, incentivizes, and challenges AI. It facilitates AI because, to be useful, many AI models require large amounts of data for training. Conclusions.

Unstructured Data 90

Unstructured Data Pipeline-centric Database-centric Entertainment 90

DataKitchen

NOVEMBER 4, 2021

The typical pharmaceutical organization faces many challenges which slow down the data team: Raw, barely integrated data sets require engineers to perform manual , repetitive, error-prone work to create analyst-ready data sets. It often takes months to progress from a data lake to the final delivery of insights.

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Process Data Process Pharmaceutical Data Lake 98

Knowledge Hut

JULY 3, 2023

This process consists of feeding data from various sources and building it to be available for analysis, storage, or next processing. To achieve this goal, pursuing Data Engineer certification can be highly beneficial. What is Real-Time Data Ingestion? Why is Real-Time Data Ingestion Important?

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Data Ingestion Pipeline-centric Google Cloud Media 52

Monte Carlo

AUGUST 2, 2022

As I begin to plot our data mesh implementation plan at Sanne Group, a leading asset management services provider, I can see why this idea that was originally introduced in 2019 has gained so much mindshare, but so few fully formed meshes nearly four years later. They will be staffed accordingly.

Pipeline-centric 52

Pipeline-centric Government Finance Data 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

Monte Carlo

NOVEMBER 10, 2022

That means you have more API integrations and data pipelines that can fail. Often, by the time most marketing teams realize that their knight (the CDP) is a legacy data silo dressed in rusty armor, it’s too late. Reliable data + marketing creativity = ROI So where does the story end for the traditional, legacy CDP?

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Pipeline-centric Data Warehouse Data Data Ingestion 52

Monte Carlo

MARCH 28, 2024

In recent years, we’ve seen all sorts of new job titles emerge that would have been inscrutable just a decade or two ago – cloud architect, data reliability engineer , data product manager , director of hybrid working, and yes, DataOps engineer. So what exactly IS a DataOps engineer? It depends!

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Pipeline-centric Engineering BI Google Cloud 75

Knowledge Hut

JANUARY 30, 2024

Whether it's aggregating customer interactions, analyzing historical sales trends, or processing real-time sensor data, data extraction initiates the process. Machine Data: For IoT applications, sensor data extraction is used to collect information from devices, machinery, or sensors, enabling real-time monitoring and analysis.

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ETL Tools Database-centric Data Mining Data Cleanse 52

Cloudera

SEPTEMBER 17, 2020

With growing disparate data across everything from edge devices to individual lines of business needing to be consolidated, curated, and delivered for downstream consumption, it’s no wonder that data engineering has become the most in-demand role across businesses — growing at an estimated rate of 50% year over year.

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Data Pipeline Data Engineering Data Engineer Engineering 104

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

ProjectPro

JUNE 1, 2017

Datos IO has extended its on-premise and public cloud data protection to RDBMS and Hadoop distributions. RecoverX is described as app-centric and can back up applications data whilst being capable of recovering it at various granularity levels to enhance storage efficiency. now provides hadoop support.

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Ascend.io

MAY 7, 2024

to bring its cutting-edge automation platform that revolutionizes modern data engineering. This platform, combined with Wizeline’s deep AI expertise, provides a powerful foundation and offering for smarter, faster, and more secure data operations. “Our collaboration with Ascend.io ” The partnership enables Ascend.io

Pipeline-centric 52

Pipeline-centric Data Cleanse Data Security Data Pipeline 52

Data Engineering Podcast

APRIL 7, 2019

Summary How much time do you spend maintaining your data pipeline? This was a fascinating conversation with someone who has spent his entire career working on simplifying complex data problems. How does the data-centric approach of DataCoral differ from the way that other platforms think about processing information?

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Data Pipeline Pipeline-centric Database-centric AWS 100

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.

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Healthcare Data Pipeline Medical Pipeline-centric 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 Engineering Podcast

MAY 7, 2023

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management RudderStack helps you build a customer data platform on your warehouse or data lake. However, that's also something we're re-thinking with our warehouse-centric strategy.

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Data Engineering Weekly

JANUARY 8, 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. Pipelines for data in motion can quickly turn into DAG hell.

Data Engineering 40

Data Engineering Data Engineer Engineering Pipeline-centric 40

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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