Edureka

MAY 6, 2024

However, building and deploying these models is just the beginning. MLOps is an emerging discipline that aims to unify and streamline the machine learning system development (Dev) and operations (Ops) lifecycle. But before we begin, Let’s have a look at what we will be covering in this blog: What is MLOPS?

Machine Learning 52

Machine Learning Metadata Programming Language Healthcare 52

Netflix Tech

MAY 4, 2023

Behind the scenes, a myriad of systems and services are involved in orchestrating the product experience. These backend systems are consistently being evolved and optimized to meet and exceed customer and product expectations. This blog series will examine the tools, techniques, and strategies we have utilized to achieve this goal.

Utilities 135

Utilities Systems Architecture Coding 135

Workfall

JUNE 12, 2023

In this blog, we will cover: What Is CDC and Its Benefits? It bridges gaps in data ecosystems, ensuring consistency and synchronisation across systems. Moreover, it facilitates the implementation of microservices architectures and event-driven systems, automating reactions to data changes without manual intervention.

Telecommunication 80

Telecommunication Metadata Healthcare Finance 80

LinkedIn Engineering

MARCH 21, 2023

One of the most exciting parts of our work is that we get to play a part in helping progress a skills-first labor market through our team’s ongoing engineering work in building our Skills Graph. Engineering vs PyTorch Figure 6: Sample Seed Skills Graph KGBert helps build a more accurate and complex taxonomy in less time.

Building 85

Building Recruitment Machine Learning Deep Learning 85

Data Engineering Podcast

SEPTEMBER 4, 2022

Monte Carlo is in the vanguard of companies who have been enabling data teams to observe and understand their complex data systems. Atlan is the metadata hub for your data ecosystem. Instead of locking your metadata into a new silo, unleash its transformative potential with Atlan’s active metadata capabilities.

IT 100

IT Metadata MongoDB MySQL 100

Data Engineering Weekly

NOVEMBER 11, 2022

Not too long ago, I worked for a famous messaging platform; You may be typing on it as you read this blog. I took a break from data engineering and focused on system monitoring and observability for some time. Little did I know I would be building data pipelines to measure system efficiency instead of measuring business efficiency.

Systems 40

Systems High Quality Data Consulting Metadata 40

Snowflake

APRIL 29, 2024

DORA: Building a More Secure Financial System DORA, enacted in January 2023, moves beyond reactive measures, requiring FEs and their service providers to proactively identify vulnerabilities, prevent disruptions and plan for swift recovery from incidents. Five Core Pillars of DORA 1.

Transportation 83

Transportation Data Governance Government Consulting 83

Data Engineering Weekly

MARCH 10, 2024

Google: Croissant- a metadata format for ML-ready datasets Google Research introduced Croissant, a new metadata format designed to make datasets ML-ready by standardizing the format, facilitating easier use in machine learning projects. This culminated in the creation of GenOS, an operating system for developing GenAI-powered features.

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

Christophe Blefari

DECEMBER 3, 2022

Joe Reis launched his Substack — Joe is the co-author of the great The Fundamentals of Data Engineering and his blog already have 2 articles I deeply recommend: No extra credit for complexity & Groundhog Days. Anna shares a good checklist to build data team foundations.

Kafka 130

Kafka BI Finance Data 130

Data Engineering Podcast

MARCH 22, 2021

For analytical systems, the only way to provide this reliably is by implementing change data capture (CDC). Unfortunately, this is a non-trivial undertaking, particularly for teams that don’t have extensive experience working with streaming data and complex distributed systems. What are the alternatives to CDC?

Data Warehouse 100

Data Warehouse Metadata Data Lake Hadoop 100

Tweag

MARCH 11, 2024

But CISA encouraged me to publish the answer as a separate blog post. I would go further and claim that for any software system that will be modified and reassembled — which is basically always — precise knowledge and control over the components and how they should be put together is crucial.

Metadata 60

Metadata Utilities Building Designing 60

Netflix Tech

MARCH 5, 2019

This operational component places some cognitive load on our engineers, requiring them to develop deep understanding of telemetry and alerting systems, capacity provisioning process, security and reliability best practices, and a vast amount of informal knowledge about the cloud infrastructure.

Cloud 73

Cloud Building Amazon Web Services Metadata 73

Christophe Blefari

JANUARY 20, 2024

The idea behind is to solve data problem by building software. Still, we can have a common ground when mixing software engineering, DevOps principles, Cloud — or on-prem — systems understanding and data literacy. Every company out there has his own definition for the data engineer role. Is it really modern?

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

LinkedIn Engineering

DECEMBER 19, 2023

The historical upgrade system couldn’t adapt to architectural changes like the introduction of an observer namenode (Now handling a massive influx of read requests – 150K QPS – from services such as Trino ), ZKFC auto-failover, HDFS federation , etc.

Big Data 92

Big Data Hadoop Metadata Data 92

Netflix Tech

NOVEMBER 13, 2023

In this blog post, we will introduce speech and music detection as an enabling technology for a variety of audio applications in Film & TV, as well as introduce our speech and music activity detection (SMAD) system which we recently published as a journal article in EURASIP Journal on Audio, Speech, and Music Processing.

Datasets 89

Datasets Metadata Algorithm Architecture 89

Knowledge Hut

MAY 9, 2024

In this blog post, we will look at some of the world's highest paying data science jobs, what they entail, and what skills and experience you need to land them. Data Scientist A data scientist is a professional who uses scientific methods, algorithms, and systems to extract insights from data. What is Data Science?

Data Science 52

Data Science Data Mining Data Architect Programming Language 52

Cloudera

AUGUST 26, 2021

In this blog post, we will ingest a real world dataset into Ozone, create a Hive table on top of it and analyze the data to study the correlation between new vaccinations and new cases per country using a Spark ML Jupyter notebook in CML. Learn more about the impacts of global data sharing in this blog, The Ethics of Data Exchange.

Data Science 109

Data Science Cloud Hadoop Metadata 109

Cloudera

MARCH 9, 2021

While Cloudera Data Platform (CDP) already supports the entire data lifecycle from ‘Edge to AI’, we at Cloudera are fully aware that enterprises have more systems outside of CDP. Atlas provides open metadata management and governance capabilities to build a catalog of all assets, and also classify and govern these assets.

Data Governance 93

Data Governance Government Metadata Datasets 93

Data Engineering Weekly

FEBRUARY 18, 2024

Modern data stack vendors chose speed, and never attempted to truly build something together. link] Mikkel Dengsøe: Data ownership - A practical guide Data Ownership is the fundamental construct to build reliable data engineering practices. I believe the data ownership problem is much deeper than simple metadata management.

Data Engineering 62

Data Engineering Data Engineer Engineering Data 62

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. I won’t bore you with the importance of data quality in the blog. The system can fail or apply a circuit breaker in the pipeline if the data contract fails.

Engineering 110

Engineering Kafka Data Pipeline Data Warehouse 110

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. LinkedIn write about Hoptimator for auto generated Flink pipeline with multiple stages of systems.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

Lyft Engineering

OCTOBER 3, 2023

Finally, as the subject of this blog post, we can assess data quality via batch compute analytics on our data warehouse, providing a comprehensive albeit slower evaluation compared to the previously mentioned methods. Verity Our solution was to build Verity, our in-house data quality platform.

Big Data 84

Big Data Metadata Data Warehouse Data 84

Cloudera

MARCH 22, 2023

Over the past handful of years, systems architecture has evolved from monolithic approaches to applications and platforms that leverage containers, schedulers, lambda functions, and more across heterogeneous infrastructures. There are many logs and metrics, and they are all over the place.

Data Governance 85

Data Governance Government Business Analyst Metadata 85

Cloudera

MARCH 14, 2023

In our previous DataFlow Designer blog post , we introduced you to the new user interface and highlighted its key capabilities. In this blog post we will put these capabilities in context and dive deeper into how the built-in, end-to-end data flow life cycle enables self-service data pipeline development.

Data Pipeline 81

Data Pipeline Designing Kafka Metadata 81

Cloudera

JANUARY 19, 2022

Gartner® recognized Cloudera in three recent reports – Magic Quadrant for Cloud Database Management Systems (DBMS), Critical Capabilities for Cloud Database Management Systems for Analytical Use Cases and Critical Capabilities for Cloud Database Management Systems for Operational Use Cases. Get started with CDP.

Database 87

Database Cloud Data Warehouse Data Lake 87

Databand.ai

AUGUST 30, 2023

It encompasses the systems, tools, and processes that enable businesses to manage their data more efficiently and effectively. These systems typically consist of siloed data storage and processing environments, with manual processes and limited collaboration between teams.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

AltexSoft

FEBRUARY 11, 2023

If you are not familiar with the above-mentioned concepts, we suggest you to follow the links above to learn more about each of them in our blog posts. The daily tasks of a data architect require more of a strategic thinking, while a data engineer’s workload is more about building the software infrastructure, which are technical tasks.

Data Architect 87

Data Architect Certification Generalist Big Data 87

DataKitchen

AUGUST 9, 2021

The data mesh is focused on building trust in data and promoting the use of data by business users who can benefit from it. The domain requires a team that creates/updates/runs the domain, and we can’t forget metadata: catalogs, lineage, test results, processing history, etc., …. Data mesh does not replace or require any of these.

Pharmaceutical 98

Pharmaceutical Raw Data Data Lake Data 98

Cloudera

JULY 15, 2021

This blog post provides an overview of best practice for the design and deployment of clusters incorporating hardware and operating system configuration, along with guidance for networking and security as well as integration with existing enterprise infrastructure. Operating System Disk Layouts. Role allocation. Networking .

Architecture 97

Architecture Cloud Kafka Hadoop 97

Snowflake

NOVEMBER 30, 2023

In this blog post, we’ll take a closer look at the details that can help decision-makers successfully plan and execute an optimal lift-and-shift cloud data migration strategy for their business. Increase extraction speed by using native extractors from the legacy system and staging extracted data on a staging server or NFS.

Data Warehouse 98

Data Warehouse Banking Data Cloud 98

Workfall

AUGUST 14, 2023

Two powerful tools that have emerged to simplify the management of data pipelines are DBT (Data Build Tool) and Airflow. In this blog, we will explore the benefits of using DBT and Airflow together and how they make data pipeline management easier than ever before. What is Airflow?

Data Pipeline 62

Data Pipeline Raw Data Data Database 62

Data Engineering Weekly

OCTOBER 30, 2022

The current state of these systems is inherently passive systems. The author narrates the data contract, why it is the foundation for building data mesh, and how it glue data catalogs, glossary and data quality systems. We saw in the Data Catalog poll how far it has to go to be helpful and active within a data workflow.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Ingestion 52

Data Engineering Podcast

JUNE 19, 2022

Summary Metadata is the lifeblood of your data platform, providing information about what is happening in your systems. A variety of platforms have been developed to capture and analyze that information to great effect, but they are inherently limited in their utility due to their nature as storage systems.

Metadata 130

Metadata MongoDB Scala MySQL 130

Data Engineering Podcast

JUNE 29, 2020

This was a great conversation about the complexities of working in a niche domain of data analysis and how to build a pipeline of high quality data from collection to analysis. Can you start by describing what you are building at Audio Analytic? What was your motivation for building an AI platform for sound recognition?

Data Collection 100

Data Collection Management High Quality Data Metadata 100

Rockset

JULY 8, 2020

Building a scalable, distributed, and real-time ETA prediction system is a tough task, but what if we could simplify its design? We’ll break our system into pieces such that each component is responsible for one primary job. Let’s take a look at components that constitute the system. Rockset satisfies all of them.

Kafka 40

Kafka Designing Systems Food 40

Cloudera

DECEMBER 10, 2020

Some data warehousing solutions such as appliances and engineered systems have attempted to overcome these problems, but with limited success. . In the above example, CDW could have cut costs by 18% for the duration that the system was idle. Its existing data warehousing service is a 40-node system and is quite static.

Data Warehouse 98

Data Warehouse Cloud Storage Metadata Data 98

Netflix Tech

OCTOBER 27, 2023

These orphaned pods represent real pain for our users, even if they are a small percentage of the total pods in the system. This blog post shows how to connect the dots from the worst case scenario (a kernel panic) through to Kubernetes (k8s) and eventually up to us operators so that we can track how and why our k8s nodes are going away.

Metadata 91

Metadata Cloud Coding Engineering 91