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 Engineer 70

Data Engineer Data Engineering Engineering Database-centric 70

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

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.

Process 98

Process Data Process Pharmaceutical Data Lake 98

RandomTrees

SEPTEMBER 27, 2024

Data Factory, Data Activator, Power BI, Synapse Real-Time Analytics, Synapse Data Engineering, Synapse Data Science, and Synapse Data Warehouse are some of them. With One Lake serving as a primary multi-cloud repository, Fabric is designed with an open, lake-centric architecture.

Database-centric 52

Database-centric Pipeline-centric IT BI 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 the role of a Data Engineer? Let us now understand the basic responsibilities of a Data engineer.

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Data Engineer Data Engineering Engineering Hadoop 98

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

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

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.

Pipeline-centric 52

Pipeline-centric BI Consulting Data Warehouse 52

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.

Data Pipeline 52

Data Pipeline ETL Tools Pipeline-centric Data Warehouse 52

Meltano

JANUARY 25, 2023

He compared the SQL + Jinja approach to the early PHP era… […] “If you take the dataframe-centric approach, you have much more “proper” objects, and programmatic abstractions and semantics around datasets, columns, and transformations. There are many advantages!

Pipeline-centric 52

Pipeline-centric Database-centric SQL Data Warehouse 52

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.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52

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

Cloudera

OCTOBER 17, 2023

As organizations shift from the modernization of data-driven applications via Kafka towards delivering real-time insight and/or powering smart automated systems, Flink At Current, adoption of Flink was a hot topic and many of the vendors (Cloudera included) use Flink as the engine to power their stream processing offerings as well.

Kafka 79

Kafka Database-centric Pipeline-centric Database 79

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

Knowledge Hut

FEBRUARY 27, 2023

Engineers work with Data Scientists to help make the most of the data they collect and have deep knowledge of distributed systems and computer science. In large organizations, data engineers concentrate on analytical databases, operate data warehouses that span multiple databases, and are responsible for developing table schemas.

Data Engineer 52

Data Engineer Data Engineering Database-centric Pipeline-centric 52

Monte Carlo

NOVEMBER 10, 2022

Cookies unfortunately also enabled more nefarious actors to capture and share customer data that didn’t have consumers’ best interests in mind. Instead, it’s the enterprise data warehouse /lakehouse, and enriched first-party data, not the CDP nor the CRM, that must occupy the center of our marketing analytics kingdom.

Data Warehouse 52

Data Warehouse Pipeline-centric Data Cloud Computing 52

Grouparoo

OCTOBER 6, 2021

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. Open question: how to seed data in a staging environment? Test system with A/A test. Be adaptable.

Data Engineer 52

Data Engineer Data Engineering Engineering Pipeline-centric 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 Engineer Data Engineering Engineering 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 Engineer 52

Data Engineer Data Engineering Engineering Database-centric 52

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.

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Data Engineer Data Engineering 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. Redshift is no longer a true competitor in the warehouse space.

Data Engineer 52

Data Engineer Data Engineering Engineering Pipeline-centric 52

Databand.ai

JULY 19, 2023

Learn more in our detailed guide to data lineage visualization (coming soon) Integration with Multiple Data Sources Data lineage tools are designed to integrate with a wide range of data sources, including databases, data warehouses, and cloud-based data platforms.

Pipeline-centric 52

Pipeline-centric Data Governance Metadata Government 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 more tables you have, the kind of SQL queries you run, and the dimensions of your data warehouses are pivotal determinants. So Why Do Snowflake Costs Become Prohibitive?

Pipeline-centric 52

Pipeline-centric IT Data Pipeline Bytes 52

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 Engineer 40

Data Engineer Data Engineering Engineering Pipeline-centric 40

Monte Carlo

JANUARY 9, 2024

Tip #2: Accept that data quality is a war, not a battle — but we may be at a turning point Our data experts know that data downtime is an ancient enemy — relative to the age of the modern data stack, in any case. I think monitoring for software is a no-brainer, and I feel the same way about monitoring for data.

Pipeline-centric 52

Pipeline-centric Database-centric Data Manufacturing 52

Knowledge Hut

SEPTEMBER 26, 2023

Microsoft Azure's Azure Synapse, formerly known as Azure SQL Data Warehouse, is a complete analytics offering. Designed to tackle the challenges of modern data management and analytics, Azure Synapse brings together the worlds of big data and data warehousing into a unified and seamlessly integrated platform.

Data Lake 52

Data Lake Database-centric Machine Learning Pipeline-centric 52

Knowledge Hut

JANUARY 30, 2024

This data can be structured, semi-structured, or entirely unstructured, making it a versatile tool for collecting information from various origins. The extracted data is then duplicated or transferred to a designated destination, often a data warehouse optimized for Online Analytical Processing (OLAP).

ETL Tools 52

ETL Tools Database-centric Data Mining Raw Data 52

Airbnb Tech

JUNE 1, 2021

On the other hand, it burdened the centralized data engineering with the impossible task of gatekeeping and onboarding an endless stream of new datasets into new and existing core tables. Furthermore, pipelines built downstream of core_data created a proliferation of duplicative and diverging metrics. Stay tuned for our next post !

Datasets 52

Datasets Pipeline-centric Metadata Data Science 52

Databand.ai

DECEMBER 29, 2022

Benjamin shares similar advice on LinkedIn, posting regularly about big data, data infrastructure, data science, data engineering, and data warehousing. He provides AI strategy, data product strategy, transformation, and data organizational build-out services to clients like Airbus, Siemens, Walmart, and JPMC.

BI 52

BI Consulting Data Science Data Governance 52

Monte Carlo

DECEMBER 7, 2022

The GitLab data stack Using a cloud-based and modular data stack makes it easy for the data team to scale while serving distributed stakeholders. How does Rob know this customer-centric approach is working? He looks to the data, of course. Image courtesy of GitLab.

Building 52

Building Pipeline-centric Data Data Programming 52

phData: Data Engineering

JULY 18, 2023

With the birth of cloud data warehouses, data applications, and generative AI , processing large volumes of data faster and cheaper is more approachable and desired than ever. This typically results in long-running ETL pipelines that cause decisions to be made on stale or old data.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

RandomTrees

NOVEMBER 29, 2023

So, here the argument on what to use and where to use become an important topic to be considered and here we can rather focus on some of the adaptable and sensitive models and we begin to consider the data vaults’ technique. So, what is a data vault model or modelling approach? post which is the ML model trainings.

Data Warehouse 52

Data Warehouse Data Lake Database-centric Data Cleanse 52

DataKitchen

JUNE 24, 2021

Previously we would have a very laborious data warehouse or data mart initiative and it may take a very long time and have a large price tag. Be business-centric. Tyo pointed out, “Don’t do data for data’s sake. There is no data strategy, it’s only a business strategy.”.

Pipeline-centric 84

Pipeline-centric Education Manufacturing Data Cleanse 84

Edureka

JULY 3, 2024

ADF connects to various data sources, including on-premises systems, cloud services, and SaaS applications. It then gathers and relocates information to a centralized hub in the cloud using the Copy Activity within data pipelines. Transform and Enhance the Data: Once centralized, data undergoes transformation and enrichment.

Pipeline-centric 52

Pipeline-centric Data Lake Database-centric Data Pipeline 52

Edureka

JULY 4, 2024

Key Advantages of Azure Synapse No Code AI or Analytics Capabilities Azure Synapse takes a significant leap forward in democratizing data analytics and AI by offering robust no-code options. Lakehouse Architecture Pioneer Databricks brought the best elements of data lakes and data warehouses to create Lakehouse.

Data Lake 40

Data Lake Pipeline-centric Data Warehouse ETL Tools 40

Databand.ai

DECEMBER 20, 2022

Follow Eric on LinkedIn 10) Brian Femiano Senior Data Engineer at Apple Brian is a senior data engineer with nearly two decades of experience at companies like Booz Allen Hamilton, Magnetic, Pandora, and, most recently, Apple. Previously, he was the first data team hire at WeWork, where he built the data engineering infrastructure.

Data Analytics 52

Data Analytics Google Cloud Data Science Data Mining 52