Workfall

JUNE 12, 2023

So, embrace the power of Change Data Capture, and embark on a captivating journey where the magic of real-time data awaits. In this blog, we will cover: What Is CDC and Its Benefits? CDC also plays a crucial role in data integration and ETL processes. Where Is CDC Used and Who Uses It?

Telecommunication 80

Telecommunication Metadata Healthcare Finance 80

Data Engineering Weekly

MAY 16, 2023

In the second part, we will focus on architectural patterns to implement data quality from a data contract perspective. Why is Data Quality Expensive? I won’t bore you with the importance of data quality in the blog. Let’s talk about the data processing types.

Engineering 110

Engineering Kafka Data Pipeline Data Warehouse 110

Christophe Blefari

JANUARY 20, 2024

He wrote some years ago 3 articles defining data engineering field. Some concepts When doing data engineering you can touch a lot of different concepts. batch — Batch processing is at the core of data engineering. One of the major task is to move data from a source storage to a destination storage.

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

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

LinkedIn Engineering

JANUARY 19, 2024

This multi-entity handover process involves huge amounts of data updating and cloning. Data consistency, feature reliability, processing scalability, and end-to-end observability are key drivers to ensuring business as usual (zero disruptions) and a cohesive customer experience. Push for eventual success of the request.

Recruitment 88

Recruitment Data Process Process Kafka 88

Cloudera

AUGUST 26, 2021

In addition to big data workloads, Ozone is also fully integrated with authorization and data governance providers namely Apache Ranger & Apache Atlas in the CDP stack. While we walk through the steps one by one from data ingestion to analysis, we will also demonstrate how Ozone can serve as an ‘S3’ compatible object store.

Data Science 109

Data Science Cloud Hadoop Metadata 109

Cloudera

MARCH 3, 2022

Data users in these enterprises don’t know how data is derived and lack confidence in whether it’s the right source to use. . If data access policies and lineage aren’t consistent across an organization’s private cloud and public clouds, gaps will exist in audit logs. From Bad to Worse.

Data Governance 96

Data Governance Government Metadata Medical 96

Cloudera

MARCH 14, 2023

We just announced the general availability of Cloudera DataFlow Designer , bringing self-service data flow development to all CDP Public Cloud customers. In our previous DataFlow Designer blog post , we introduced you to the new user interface and highlighted its key capabilities.

Data Pipeline 81

Data Pipeline Designing Kafka Metadata 81

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

Data Engineering Podcast

JUNE 29, 2020

Summary We have machines that can listen to and process human speech in a variety of languages, but dealing with unstructured sounds in our environment is a much greater challenge. What are the unique challenges that you have faced in working with arbitrary sound data? What do you have planned for the future of the company?

Data Collection 100

Data Collection Management High Quality Data Metadata 100

Maxime Beauchemin

JANUARY 20, 2017

This discipline also integrates specialization around the operation of so called “big data” distributed systems, along with concepts around the extended Hadoop ecosystem, stream processing, and in computation at scale. Sure, there’s a need to abstract the complexity of data processing, computation and storage.

Data Engineering 130

Data Engineering Data Engineer Engineering ETL Tools 130

LinkedIn Engineering

DECEMBER 12, 2023

PEDAL also consists of a metadata store that holds various algorithmic parameters, including the scale of noise that we introduce and whether we should use one-shot or continual observation algorithms. The application may then choose to further post-process the result, but PEDAL ensures the result is private.

Algorithm 77

Algorithm Metadata SQL Datasets 77

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. Bad data management be like, Source: Makeameme Data architects are sometimes confused with other roles inside the data science team. Feel free to enjoy it.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Cloudera

JUNE 18, 2022

The first generation of the Hive Metastore attempted to address the performance considerations to run SQL efficiently on a data lake. It provided the concept of a database, schemas, and tables for describing the structure of a data lake in a way that let BI tools traverse the data efficiently.

Data Lake 90

Data Lake Data Warehouse BI SQL 90

Data Engineering Weekly

FEBRUARY 18, 2024

A recent survey from dbt shows that 43% of the respondents answered that ambiguous data ownership was their biggest challenge. The author writes about the basic construct of data ownership and how to utilize dbt to reduce friction. I believe the data ownership problem is much deeper than simple metadata management.

Data Engineering 62

Data Engineering Data Engineer Engineering Data 62

DataKitchen

AUGUST 9, 2021

The domain also includes code that acts upon the data, including tools, pipelines, and other artifacts that drive analytics execution. The domain requires a team that creates/updates/runs the domain, and we can’t forget metadata: catalogs, lineage, test results, processing history, etc., ….

Pharmaceutical 98

Pharmaceutical Raw Data Data Lake Data 98

Netflix Tech

OCTOBER 19, 2020

In our previous blog post we introduced Edgar, our troubleshooting tool for streaming sessions. Reconstructing a streaming session was a tedious and time consuming process that involved tracing all interactions (requests) between the Netflix app, our Content Delivery Network (CDN), and backend microservices.

Building 93

Building Transportation Metadata Java 93

Knowledge Hut

OCTOBER 26, 2023

In this blog, we will show some interesting AWS project ideas for all professionals, including beginners, intermediate, and advanced. blog) easily using any of your preferred CMS. You can use AWS SES (Simple Email Service) to send emails and AWS SNS (Simple Notification Service) to trigger the email-sending process.

AWS 52

AWS Coding Project Cloud Computing 52

Knowledge Hut

SEPTEMBER 29, 2023

Moreover, what benefits can you expect from a career in Azure Data Engineering? This blog aims to answer these questions, providing a straightforward and professional insight into the world of Azure Data Engineering. Join us on this journey through the exciting realm of Azure Data Engineering.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Cloudera

AUGUST 31, 2021

Running on CDW is fully integrated with streaming, data engineering, and machine learning analytics. It has a consistent framework that secures and provides governance for all data and metadata on private clouds, multiple public clouds, or hybrid clouds. Consideration of both data & metadata in the migration.

Data Warehouse 80

Data Warehouse Database-centric Metadata Cloud 80

Data Engineering Weekly

NOVEMBER 6, 2022

A data contract is a continuous and collaborative system because the business context and requirements won’t be static. I plan to write a series of blogs on Schemata and Data Contract in the coming weeks. Martin kindly stepped in for me to give the update for my promised blog posts.

Data Engineering 40

Data Engineering Data Engineer Engineering Machine Learning 40

Cloudera

JANUARY 5, 2023

With the right tools in place, distilling actionable insights from data to achieve business objectives or unlock new revenue streams is easily achievable for organizations of all sizes across industries, especially with the availability of self-serve functionalities that do not require specialized ops or cloud expertise.

Banking 52

Banking Machine Learning Insurance Data Architecture 52

Databand.ai

JUNE 28, 2023

It goes beyond basic monitoring to provide a deeper understanding of how data is moving and being transformed in a pipeline, and is often associated with metrics, logging, and tracing data pipelines. Data pipelines often involve a series of stages where data is collected, transformed, and stored.

Data Pipeline 98

Data Pipeline Data Engineering Data Engineer Engineering 98

Cloudera

SEPTEMBER 17, 2020

Having immediate access to a visualization tool that can query a highly scalable and flexible cloud-native data warehouse is key for most businesses to expedite experimentation and stay ahead in the market. Cloudera Data Visualization is the same visual tool used across: Structured data, processed by an optimized SQL query engine.

Unstructured Data 80

Unstructured Data Data Warehouse Pharmaceutical MySQL 80

Maxime Beauchemin

JANUARY 7, 2018

Batch data processing  — historically known as ETL —  is extremely challenging. In this post, we’ll explore how applying the functional programming paradigm to data engineering can bring a lot of clarity to the process. The greater the claim made using analytics, the greater the scrutiny on the process should be.

Data Engineering 183

Data Engineering Data Engineer Data Process Process 183

Cloudera

AUGUST 21, 2020

Businesses need to be able to ingest huge volumes of data from these data points as well as handle, process, and store this vast amount of data. Then they need to move to data separation so that they not only ingest the data but prepare the data so that it becomes processable.

Banking 60

Banking Kafka Cloud Storage Government 60

Cloudera

SEPTEMBER 1, 2020

The CrunchIndexerTool can use Spark to read data from HDFS files into Apache Solr for indexing, and run the data through a so-called morphline for extraction and transformation in an efficient way. Coordinates distribution of data and metadata, also known as shards. Before you Get Started.

Cloud Storage 67

Cloud Storage Unstructured Data AWS Analytics Application 67

Knowledge Hut

OCTOBER 26, 2023

In the world of machine learning, where data-driven solutions have the power to transform industries and empower individuals, if you're new to this exciting field and eager to embark on your machine-learning journey, you're in the right place. It helps you perform automated data visualization.

Machine Learning 52

Machine Learning Project Datasets Algorithm 52

Knowledge Hut

JULY 26, 2023

They enable organizations to use data as an asset, resulting in greater operational efficiency, improved decision-making, and an edge over competitors in today's data-driven corporate world. Database applications also help in data-driven decision-making by providing data analysis and reporting tools.

Database 52

Database NoSQL Telecommunication MongoDB 52

Netflix Tech

NOVEMBER 20, 2023

by Jun He , Yingyi Zhang , and Pawan Dixit Incremental processing is an approach to process new or changed data in workflows. The key advantage is that it only incrementally processes data that are newly added or updated to a dataset, instead of re-processing the complete dataset.

Process 84

Process Data Pipeline Datasets SQL 84

Cloudera

AUGUST 30, 2018

This is especially critical in a world where petabyte-scale data is commonplace, business demand is insatiable, and security and governance requirements are unavoidable. For more on the data-driven journey, I would encourage you to view our Cloudera Now presentation. The rest of this blog is focused on how Cloudera Enterprise 6.0

Unstructured Data 40

Unstructured Data Machine Learning Data Warehouse BI 40

LinkedIn Engineering

JUNE 15, 2023

However, we found that many of our workloads were bottlenecked by reading multiple terabytes of input data. To remove this bottleneck, we built AvroTensorDataset , a TensorFlow dataset for reading, parsing, and processing Avro data. If greater than one, records in files are processed in parallel.

Datasets 102

Datasets Bytes Process Data Ingestion 102

LinkedIn Engineering

MARCH 23, 2023

Co-Authors: Yuhong Cheng , Shangjin Zhang , Xinyu Liu, and Yi Pan Efficient data processing is crucial in reducing learning curves, simplifying maintenance efforts, and decreasing operational complexity. By unifying these pipelines, we have saved 94% of processing time. Samza , Spark and Apache Flink ).

Process 97

Process Lambda Architecture Kafka Datasets 97

Databand.ai

AUGUST 30, 2023

Data quality monitoring refers to the assessment, measurement, and management of an organization’s data in terms of accuracy, consistency, and reliability. It utilizes various techniques to identify and resolve data quality issues, ensuring that high-quality data is used for business processes and decision-making.

Data Cleanse 52

Data Cleanse Metadata High Quality Data Datasets 52

Rockset

JUNE 7, 2021

What Is Change Data Capture? Change data capture (CDC) is the process of recognising when data has been changed in a source system so a downstream process or system can action that change. A common use case is to reflect the change in a different target system so that the data in the systems stay in sync.

IT 40

IT Kafka Database MongoDB 40

Rockset

MARCH 18, 2024

Flink is one of the most popular stream processing technologies, ranked as a top five Apache project and backed by a diverse committer community including Alibaba and Apple. It powers steam processing at many companies including Uber, Netflix, and Linkedin.

Cloud 64

Cloud Building Metadata Kafka 64

Zalando Engineering

NOVEMBER 29, 2017

In this blog post, we share our experiences and lessons learned to run our real-time applications built with Kafka’s Streams API in production on Amazon Web Services (AWS). Ultimately we realised that the processing time for a record in these services could be very long (up to minutes) in some edge cases.

Kafka 40

Kafka AWS Amazon Web Services Utilities 40