Christophe Blefari

JANUARY 20, 2024

Learn data engineering, all the references ( credits ) This is a special edition of the Data News. But right now I'm in holidays finishing a hiking week in Corsica 🥾 So I wrote this special edition about: how to learn data engineering in 2024. The idea is to create a living reference about Data Engineering.

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

Data Engineering Podcast

JUNE 5, 2022

Summary The best way to make sure that you don’t leak sensitive data is to never have it in the first place. The team at Skyflow decided that the second best way is to build a storage system dedicated to securely managing your sensitive information and making it easy to integrate with your applications and data systems.

Data Security 100

Data Security Metadata MongoDB Scala 100

phData: Data Engineering

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. What is a Data Lake?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. Ingestion layer 2.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Cloudyard

MARCH 4, 2023

Read Time: 5 Minute, 16 Second As we know Snowflake has introduced latest badge “Data Cloud Deployment Framework” which helps to understand knowledge in designing, deploying, and managing the Snowflake landscape. Respective Cloud would consume/Store the data in bucket or containers. Snowpipe to automate the ingestion process.

Architecture 52

Architecture Cloud Metadata Data Ingestion 52

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. Ingestion layer 2.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

DataKitchen

OCTOBER 20, 2023

In today’s data-driven landscape, Data and Analytics Teams i ncreasingly face a unique set of challenges presented by Demanding Data Consumers who require a personalized level of Data Observability. Data Observability platforms often need to deliver this level of customization.

Insurance 67

Insurance Pharmaceutical Data Data Ingestion 67

Snowflake

NOVEMBER 29, 2023

Data cloud technology can accelerate FAIRification of the world’s biomedical patient data. In other instances, the concern is primarily the risk of potential patient re-identification that comes with longitudinal data enrichment.

Metadata 84

Metadata Healthcare Medical Data Storage 84

Data Engineering Weekly

MAY 16, 2023

In the first part of this series, we talked about design patterns for data creation and the pros & cons of each system from the data contract perspective. In the second part, we will focus on architectural patterns to implement data quality from a data contract perspective. Why is Data Quality Expensive?

Engineering 110

Engineering Kafka Data Pipeline Data Warehouse 110

Cloudera

AUGUST 26, 2021

Ozone natively provides Amazon S3 and Hadoop Filesystem compatible endpoints in addition to its own native object store API endpoint and is designed to work seamlessly with enterprise scale data warehousing, machine learning and streaming workloads. Learn more about the impacts of global data sharing in this blog, The Ethics of Data Exchange.

Data Science 111

Data Science Cloud Hadoop Metadata 111

Snowflake

FEBRUARY 13, 2024

Snowpark Updates Model management with the Snowpark Model Registry – public preview Snowpark Model Registry is an integrated solution to register, manage and use models and their metadata natively in Snowflake. When a pipe is in this state, it means the pipe will not accept new files for ingestion. Learn more here.

Data Ingestion 87

Data Ingestion AWS Python Metadata 87

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. What is data pipeline observability?

Data Pipeline 98

Data Pipeline Data Engineering Data Engineer Engineering 98

Monte Carlo

APRIL 4, 2023

The modern data stack consists of multiple interdependent data systems all working together. Data anomalies and incidents can be introduced across any point of this pipeline, which can make root cause analysis a fragmented and frustrating multi-tab process. Was it a query changed within Snowflake? A modified dbt model?

BI 64

BI Data Ingestion Metadata Data Pipeline 64

Cloudera

DECEMBER 20, 2021

The right set of tools helps businesses utilize data to drive insights and value. But balancing a strong layer of security and governance with easy access to data for all users is no easy task. Another option — a more rewarding one — is to include centralized data management, security, and governance into data projects from the start.

Government 89

Government Data Security Banking Metadata 89

Ascend.io

FEBRUARY 6, 2023

If you’ve read this week’s release notes , you’ll have seen “Added ability to configure or override connection details at the Data Service level in BigQuery and Databricks Data Planes.” Data Services Listing with BigQuery, Snowflake, and Databricks. Data Service – is a group of Data Flows.

Cloud 52

Cloud Data Ingestion Raw Data Data Pipeline 52

Ascend.io

FEBRUARY 6, 2023

If you’ve read this week’s release notes , you’ll have seen “Added ability to configure or override connection details at the Data Service level in BigQuery and Databricks Data Planes.” Data Services Listing with BigQuery, Snowflake, and Databricks. Data Service – is a group of Data Flows.

Cloud 52

Cloud Data Ingestion Raw Data Data Pipeline 52

Towards Data Science

DECEMBER 1, 2023

Pet Project for Data/Analytics Engineers: Explore Modern Data Stack Tools — dbt Core, Snowflake, Fivetran, GitHub Actions. This hands-on experience will allow you to develop an end-to-end data lifecycle, from extracting data from your Google Calendar to presenting it in a Snowflake analytics dashboard. See Github repo.

Data Engineering 71

Data Engineering Data Engineer Project Engineering 71

Data Engineering Weekly

OCTOBER 30, 2022

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. The highlights are that 59% of folks think data catalogs are sometimes helpful.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Ingestion 52

Cloudera

JUNE 30, 2022

We are excited to announce the general availability of Apache Iceberg in Cloudera Data Platform (CDP). These tools empower analysts and data scientists to easily collaborate on the same data, with their choice of tools and analytic engines. Why integrate Apache Iceberg with Cloudera Data Platform?

Data Lake 86

Data Lake Business Intelligence Metadata Data Warehouse 86

Cloudera

JUNE 16, 2022

The ability to perform analytics on data as it is created and collected (a.k.a. real-time data streams) and generate immediate insights for faster decision making provides a competitive edge for organizations. . CSP was recently recognized as a leader in the 2022 GigaOm Radar for Streaming Data Platforms report.

Kafka 86

Kafka Manufacturing Data Lake SQL 86

Cloudera

OCTOBER 11, 2021

Modak, a leading provider of modern data engineering solutions, is now a certified solution partner with Cloudera. Customers can now seamlessly automate migration to Cloudera’s Hybrid Data Platform — Cloudera Data Platform (CDP) to dynamically auto-scale cloud services with Cloudera Data Engineering (CDE) integration with Modak Nabu.

Data Engineering 92

Data Engineering Data Engineer Cloud Engineering 92

AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. What is a data lake?

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Netflix Tech

MARCH 25, 2019

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and Efficiency By: Di Lin , Girish Lingappa , Jitender Aswani Imagine yourself in the role of a data-inspired decision maker staring at a metric on a dashboard about to make a critical business decision but pausing to ask a question?—?“Can

Building 87

Building Metadata Transportation Data Ingestion 87

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. As a result, they can be slow, inefficient, and prone to errors.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Ascend.io

JUNE 8, 2023

Because of its transformative potential, data has graduated from being merely a by-product of business operations to a critical asset in its own right. Is it possible to treat data not just as a necessary operational output, but as a product that holds immense strategic value? Without them, data products can’t exist.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52

Cloudera

APRIL 22, 2021

Today’s enterprise data analytics teams are constantly looking to get the best out of their platforms. Storage plays one of the most important roles in the data platforms strategy, it provides the basis for all compute engines and applications to be built on top of it. Separates control and data plane enabling high performance.

Pipeline-centric 100

Pipeline-centric Data Lake Hadoop Metadata 100

Netflix Tech

DECEMBER 21, 2020

By Anupom Syam Background At Netflix, our current data warehouse contains hundreds of Petabytes of data stored in AWS S3 , and each day we ingest and create additional Petabytes. Use cases We found several use cases where a system like AutoOptimize can bring tons of value.

Data Warehouse 81

Data Warehouse Metadata Algorithm Data 81

DataKitchen

SEPTEMBER 21, 2023

Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability In a world where 97% of data engineers report burnout and crisis mode seems to be the default setting for data teams, a Zen-like calm feels like an unattainable dream. What is Data in Place?

Raw Data 67

Raw Data Data Business Intelligence High Quality Data 67

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?”

Data Pipeline 52

Data Pipeline Data Ingestion Metadata Data 52

Precisely

SEPTEMBER 11, 2023

At Precisely, we recognize the value and potential of AI to help our customers work faster and smarter, and make more powerful, confident decisions grounded in trusted data – supporting our overall mission of unlocking data integrity for organizations of all kinds.

Metadata 52

Metadata Data Integration Datasets Data Analysis Tools 52

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 82

Data Warehouse Database-centric Metadata Cloud 82

Data Engineering Podcast

AUGUST 6, 2022

Summary The optimal format for storage and retrieval of data is dependent on how it is going to be used. For analytical systems there are decades of investment in data warehouses and various modeling techniques. Data stacks are becoming more and more complex. Sifflet also offers a 2-week free trial.

Machine Learning 100

Machine Learning Database MySQL PostgreSQL 100

Monte Carlo

MARCH 28, 2023

If you don’t like change, data engineering is not for you. The most prominent, recent examples are Snowflake and Databricks disrupting the concept of the database and ushering in the modern data stack era. As part of this movement, Fivetran and dbt fundamentally altered the data pipeline from ETL to ELT.

Data Warehouse 126

Data Warehouse Raw Data Data Pipeline Software Engineer 126

Rockset

APRIL 18, 2023

We’re excited to introduce vector search on Rockset to power fast and efficient search experiences, personalization engines, fraud detection systems and more. Organizations have continued to accumulate large quantities of unstructured data, ranging from text documents to multimedia content to machine and sensor data.

Unstructured Data 105

Unstructured Data Metadata Machine Learning SQL 105

LinkedIn Engineering

DECEMBER 12, 2023

We will start with a general overview of differential privacy, the gold standard of enforcing privacy for data analytics, which we adopt in post analytics. We say that an algorithm is differentially private if any result of the algorithm cannot depend too much on any single data record in a dataset.

Algorithm 77

Algorithm Metadata SQL Datasets 77

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.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Towards Data Science

APRIL 3, 2023

The post-modern data stack is coming. If you don’t like change, data engineering is not for you. The most prominent, recent examples are Snowflake and Databricks disrupting the concept of the database and ushering in the modern data stack era. The answer is, yes of course we will have to rebuild our data systems.

Data Engineering 98

Data Engineering Data Engineer Engineering Data Warehouse 98