Edureka

MAY 6, 2024

MLOps is an emerging discipline that aims to unify and streamline the machine learning system development (Dev) and operations (Ops) lifecycle. Whether you are a newbie or an experienced individual, if you want to explore more about the concepts of MLOPS, then you just click on the right blog. Why do we need MLOPS?

Machine Learning 52

Machine Learning Metadata Programming Language Healthcare 52

Data Engineering Podcast

FEBRUARY 26, 2023

In this episode he shares that journey and the combination of technical and organizational challenges that he encountered in the process. What are the technical systems that you are relying on to power the different data domains? What are the technical systems that you are relying on to power the different data domains?

Building 147

Building Metadata Machine Learning Data Integration 147

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

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

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

Databand.ai

JULY 19, 2023

Data lineage tools provide a visual representation of your data’s journey across multiple systems and transformations. This allows businesses to identify any transformations or processes that may be compromising the data’s integrity.

Pipeline-centric 52

Pipeline-centric Data Governance Metadata Government 52

Cloudera

NOVEMBER 29, 2023

The Model Registry is designed to streamline these processes, offering a variety of tools and features. It simplifies recording model parameters, metadata, and metrics ensuring transparent bookkeeping. Its development is geared towards easing the transition between different cloud systems. What does the Model Registry offer?

Machine Learning 84

Machine Learning Metadata Cloud Project 84

LinkedIn Engineering

DECEMBER 19, 2023

These clusters are the backbone for storing and processing extensive data volumes, empowering us to deliver essential features and services to members, such as personalized recommendations, enhanced search functionality, and valuable insights.

Big Data 92

Big Data Hadoop Metadata Data 92

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

Netflix Tech

NOVEMBER 29, 2023

As noted in an earlier blog post , we began developing an HDR variant of VMAF; let’s call it HDR-VMAF. and based on content characteristics and/or metadata signaled in the bitstream. For a given rate-quality operating point, the DO process helps allocate bits among the various shots while maximizing an overall objective function.

Metadata 100

Metadata Electronics Algorithm Software Engineer 100

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

Christophe Blefari

JANUARY 20, 2024

Still, we can have a common ground when mixing software engineering, DevOps principles, Cloud — or on-prem — systems understanding and data literacy. batch — Batch processing is at the core of data engineering. stream — Stream processing can be seen as the evolution of the batch. This is not.

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

Cloudera

AUGUST 10, 2021

We understand that migrating your data platform to the latest version can be an intricate task, and at Cloudera we’ve worked hard to simplify this process for all our customers. . We expand on this feature later in this blog. With the release of CDP Private Cloud (PvC) Base 7.1.7, x, and 6.3.x, x, and 6.3.x,

Cloud 96

Cloud Kafka Metadata SQL 96

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

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

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. These flow through Kafka , our event streaming platform, before being processed by Flink , our streaming compute framework.

Big Data 84

Big Data Metadata Data Warehouse Data 84

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

Databand.ai

AUGUST 30, 2023

It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows. It encompasses the systems, tools, and processes that enable businesses to manage their data more efficiently and effectively. As a result, they can be slow, inefficient, and prone to errors.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

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. Let’s talk about the data processing types. Why is Data Quality Expensive?

Engineering 110

Engineering Kafka Data Pipeline Data Warehouse 110

Lyft Engineering

JUNE 28, 2023

In early 2022, Lyft already had a comprehensive Machine Learning Platform called LyftLearn composed of model serving , training , CI/CD, feature serving , and model monitoring systems. However, streaming data was not supported as a first-class citizen across many of the platform’s systems — such as training, complex monitoring, and others.

Machine Learning 115

Machine Learning Building Metadata Kafka 115

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 3, 2022

Data analytics and machine learning can become a business and a compliance risk if data security, governance, lineage, metadata management, and automation are not holistically applied across the entire data lifecycle and all environments. From Bad to Worse. Afterall, retrofitting good governance is a momentous task.

Data Governance 96

Data Governance Government Metadata Medical 96

Databand.ai

AUGUST 30, 2023

A data quality strategy details the processes, tools, and techniques employed to ensure your company’s data is accurate, consistent, complete, and up-to-date. This includes defining roles and responsibilities related to managing datasets and setting guidelines for metadata management.

Building 52

Building Data Cleanse Data Governance Datasets 52

Cloudera

JULY 14, 2023

In this blog, I will describe a few strategies one could undertake for various use cases. It could be much easier to simply stop all those jobs rather than allowing them to continue during the migration process. This will be discussed in a later blog. Hive creates Iceberg’s metadata files for the same exact table.

Metadata 69

Metadata Data Warehouse Big Data Ecosystem Java 69

Datakin

AUGUST 5, 2021

Blog A real-time approach to data lineage Written by Ross Turk on August 5, 2021 A data ecosystem that spans multiple pipelines, teams, and platforms can be overwhelming. Lineage metadata is the thread that connects it all together. However, there is more than one way to capture lineage metadata.

Metadata 52

Metadata Relational Database Datasets SQL 52

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. Each has their own stacked layers of enabling technologies, from operating systems to containers to resources.

Data Governance 85

Data Governance Government Business Analyst Metadata 85

Cloudyard

AUGUST 13, 2023

Read Time: 3 Minute, 24 Second In this blog post, we’ll explore a practical approach to ensure the accuracy of file counts before they’re ingested into Snowflake. In current scenario the source system sends data files to a UNIX environment, which is then utilized by downstream systems.

AWS 52

AWS SQL Metadata Utilities 52

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

SEPTEMBER 30, 2021

Our recent blog discussed the four paths to get from legacy platforms to CDP Private Cloud Base. In this blog and accompanying video, we will deep dive into the mechanics of running an in-place upgrade from CDH5 or CDH6 to CDP Private Cloud Base. The overall upgrade follows a seven-step process illustrated below. Ubuntu 18.04

Cloud 70

Cloud PostgreSQL Metadata MySQL 70

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

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

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

Confluent

MARCH 26, 2019

how long it takes to execute an operation) and additional metadata like annotations and tags. For the translation service to correlate its spans with the caller service traces, it receives tracing metadata via context propagation (i.e., reading metadata injected into HTTP headers). Let’s imagine a “Hello, World!”

Kafka 111

Kafka Transportation Metadata Consulting 111

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. Another important task is to evaluate the company’s hardware and software and identify if there is a need to replace old components and migrate data to a new system.

Data Architect 87

Data Architect Certification Generalist Big Data 87

DataKitchen

AUGUST 9, 2021

The domain requires a team that creates/updates/runs the domain, and we can’t forget metadata: catalogs, lineage, test results, processing history, etc., …. Figure 1 shows a simplified diagram of a domain receiving input data from an upstream source like an operational system (O) and supplying data (D) to a customer or consumer.

Pharmaceutical 98

Pharmaceutical Raw Data Data Lake Data 98

DataKitchen

OCTOBER 20, 2023

The Challenge: High Stakes in the Age of Personalized Data Observability The primary challenge stems from the requirement of Data Consumers for personalized monitoring and alerts based on their unique data processing needs. Data Observability platforms often need to deliver this level of customization.

Insurance 67

Insurance Pharmaceutical Data Data Ingestion 67

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. For example, . x 24 x 10 )+ ($1.44 X 24 x 10)). . CDW optimizes storage.

Data Warehouse 98

Data Warehouse Cloud Storage Metadata Data 98