Cloudera

SEPTEMBER 28, 2020

Modernize their architecture to ingest data in real-time using the new streaming features available in CDP Private Cloud Base in order to make the data available to their users quickly. Support Kafka connectivity to HDFS, AWS S3 and Kafka Streams. New Features CDH to CDP. Identifying areas of interest for Customer A. Phase 1: Planning.

Cloud 131

Cloud Kafka Professional Services Metadata 131

ProjectPro

FEBRUARY 21, 2023

Apache Spark is the most efficient, scalable, and widely used in-memory data computation tool capable of performing batch-mode, real-time, and analytics operations. The next evolutionary shift in the data processing environment will be brought about by Spark due to its exceptional batch and streaming capabilities.

Scala 52

Scala Programming Language Java Hadoop 52

Cloud Academy

JULY 16, 2019

Designing a streaming data pipeline presents many challenges, particularly around specific technology requirements. In this blog post, we will walk through some initial scoping steps and walk through an example. In this blog post, we will walk through some initial scoping steps and walk through an example.

Manufacturing 52

Manufacturing MySQL Data Cloud 52

Cloudera

JULY 21, 2022

Cloudera users can securely connect Rill to a source of event stream data, such as Cloudera DataFlow , model data into Rill’s cloud-based Druid service, and share live operational dashboards within minutes via Rill’s interactive metrics dashboard or any connected BI solution. Efficient batch data processing. Apache Hive.

BI 86

BI Digital Media Data Warehouse Kafka 86

Striim

NOVEMBER 30, 2022

Companies that can’t process and analyze it to glean useful insights for their operations are falling behind. We are excited to launch Striim Cloud on AWS: a real-time data integration and streaming platform that connects clouds, data and applications with unprecedented speed and simplicity.

AWS 52

AWS Cloud Management Google Cloud 52

Netflix Tech

AUGUST 30, 2021

By Benson Ma , Alok Ahuja Introduction At Netflix, hundreds of different device types, from streaming sticks to smart TVs, are tested every day through automation to ensure that new software releases continue to deliver the quality of the Netflix experience that our customers enjoy. In this blog post, we will focus on the latter feature set.

Management 85

Management Kafka Transportation Cloud 85

Pinterest Engineering

OCTOBER 31, 2023

We leverage Custom Resources (CR) to define the kinds of workloads supported by the platform, and the platform offers a range of workload orchestration capabilities which supports both batch jobs and long running services in various forms. It provides three groups of APIs: workload APIs, operation APIs, and insight APIs. G5 family).

Architecture 96

Architecture Pipeline-centric Accessible Accessibility 96

Knowledge Hut

JANUARY 22, 2024

Online vs. In-Person Delivery The choice between online and in-person delivery for data science courses depends on your learning preferences and situational factors. Key topics include data collection, storage formats like databases, data warehouses, data lakes, transforming and processing data using ETL, batch and stream processing.

Data Science 52

Data Science Certification Education Data Lake 52

Rockset

JUNE 7, 2021

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. Push vs Pull There are two main ways for change data capture systems to operate. What Is Change Data Capture?

IT 40

IT Kafka Database MongoDB 40

Zalando Engineering

JULY 12, 2017

While developing Zalando’s real-time business process monitoring solution, we encountered the need to generate complex events upon the detection of specific patterns of input events. In this blog post we describe the generation of such events using Apache Flink, and share our experiences and lessons learned in the process.

Process 40

Process Kafka AWS Architecture 40

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

Rockset

AUGUST 13, 2019

Organizations speak of operational reporting and analytics as the next technical challenge in improving business processes and efficiency. We consider several approaches, all of which use DynamoDB Streams but differ in how the dashboards are served: 1. DynamoDB Streams + Lambda + Kinesis Firehose + Redshift 2.

BI 40

BI NoSQL PostgreSQL AWS 40

Data Engineering Podcast

MARCH 25, 2023

Summary The promise of streaming data is that it allows you to react to new information as it happens, rather than introducing latency by batching records together. The peril is that building a robust and scalable streaming architecture is always more complicated and error-prone than you think it's going to be.

MySQL 130

MySQL Python Architecture Machine Learning 130

Confluent

SEPTEMBER 26, 2019

The significant difference today is that companies use Apache Kafka as an event streaming platform for building mission-critical infrastructures and core operations platforms. Batch processing and reports after minutes or even hours is not sufficient. Apache Kafka as an event streaming platform for real-time analytics.

Kafka 21

Kafka BI SQL Datasets 21

Snowflake

MARCH 2, 2023

That proves to be a difficult task for data engineering teams that have to manage separate infrastructure for batch data and streaming data. To address this challenge, we are happy to announce the public preview of Snowpipe Streaming as the latest addition to our Snowflake ingestion offerings. How does Snowpipe Streaming work?

Kafka 125

Kafka Data Ingestion Data Pipeline Cloud Storage 125

Rockset

MARCH 27, 2023

This is part two in Rockset’s Making Sense of Real-Time Analytics on Streaming Data series. In part 1 , we covered the technology landscape for real-time analytics on streaming data. In this post, we’ll explore the differences between real-time analytics databases and stream processing frameworks.

Database 52

Database Process Scala SQL 52

Monte Carlo

JANUARY 16, 2024

In this blog post, we’ll look at six innovations that are shaping the future of the data warehousing, as well as challenges and considerations that organizations should keep in mind. Easier to stream real-time data 3. Data lake and data warehouse convergence The data lake vs data warehouse question is constantly evolving.

Data Lake 52

Data Lake Data Warehouse Unstructured Data AWS 52

Lyft Engineering

MARCH 12, 2024

This highlights another strength of RL models — they optimize for the whole decision making process towards a target metric in potentially changing environments. More typically, we perform batch updates anywhere from every 10 minutes to 24 hours. The metric can be fairly high level, for example conversion or revenue.

Algorithm 66

Algorithm Machine Learning Datasets Food 66

Data Engineering Weekly

JANUARY 29, 2023

The conversation around data observability points out the growing gap in data observability [aka finding the things] vs. fixing the data quality. Upsolver SQLake lets you process fast-moving data by simply writing a SQL query. Streaming plus batch unified in a single platform.

Data Engineering 52

Data Engineering Data Engineer Engineering Deep Learning 52

Data Engineering Weekly

DECEMBER 18, 2022

The author writes an exciting blog, Modern data stack in a Box!! link] Confessions of a Data Guy: Dataframe Showdown – Polars vs. Spark vs. Pandas vs. DataFusion. Upsolver SQLake lets you process fast-moving data by simply writing a SQL query. Streaming plus batch unified in a single platform.

Data Engineering 52

Data Engineering Data Engineer Engineering Relational Database 52

Rockset

FEBRUARY 24, 2022

Which databases are optimized for ingesting streaming events and analyzing them in real time? We’ll start by evaluating three options for running real-time analytics on AWS Kinesis event streams. I’ll focus on the use of events to help understand, analyze and diagnose problems using various OLAP databases and AWS Kinesis data streams.

AWS 52

AWS Amazon Web Services Kafka SQL 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

AltexSoft

OCTOBER 21, 2022

Similar to Google in web browsing and Photoshop in image processing, it became a gold standard in data streaming, preferred by 70 percent of Fortune 500 companies. Apache Kafka is an open-source, distributed streaming platform for messaging, storing, processing, and integrating large data volumes in real time. Kafka APIs.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

Snowflake

MARCH 30, 2023

Just as a dimensional data model will transform data for human consumption, ML models need raw data transformed for ML model consumption through a process called “ feature engineering.” Based on Tecton blog So is this similar to data engineering pipelines into a data lake/warehouse?

Engineering 84

Engineering Raw Data Data Science Scala 84

Netflix Tech

JULY 26, 2021

Operational Reporting is a reporting paradigm specialized in covering high-resolution, low-latency data sets, serving detailed day-to-day activities¹ and processes of a business domain. Data Mesh is a fully managed, streaming data pipeline product used for enabling Change Data Capture (CDC) use cases. tactical) in nature.

Data 101

Data Data Pipeline MySQL Data Warehouse 101

Confluent

JUNE 26, 2019

In these projects, microservice architectures use Kafka as an event streaming platform. Domain-driven design is used to define the different bounded contexts which represent the various business processes that the application needs to perform. Apache Kafka – An event streaming platform for microservices. Microservices.

Kafka 109

Kafka Designing Architecture ETL Tools 109

Cloudera

AUGUST 16, 2021

In this blog post we’re revisiting the challenges that come with running Apache NiFi at scale before we take a closer look at the architecture and core features of CDF-PC. Since it supports both structured and unstructured data for streaming and batch integrations, Apache NiFi is quickly becoming a core component of modern data pipelines.

Cloud 119

Cloud Unstructured Data Utilities Metadata 119

Data Engineering Weekly

JANUARY 22, 2023

Editor’s Note: Update on our blog series One of the promises I made toward the end of 2022 is to publish more of my thoughts and industry observation of data engineering trends. Data Catalog - A broken promise A classic blog triggers a few conversations about Data Catalog and its future. Sign up free to test out the tool today.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Pipeline 52

Rockset

MARCH 26, 2023

To do this, Rockset has partnered with Confluent, the original creators of Kafka who provide the cloud-native data streaming platform Confluent Cloud. At Confluent I talked often about the fanciful sounding “Stream and Table Duality”. You can learn more about Confluent vs. Kafka over on Confluent’s site.

Cloud 52

Cloud PostgreSQL Kafka Database 52

ProjectPro

JANUARY 19, 2022

Read this blog till the end to learn more about the roles and responsibilities, necessary skillsets, average salaries, and various important certifications that will help you build a successful career as an Azure Data Engineer. Data engineers will be in high demand as long as there is data to process.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

ProjectPro

JUNE 16, 2022

Generally, it consists of three key elements: a source, processing step(s), and destination to streamline movement across digital platforms. This blog will teach you about AWS Data Pipeline, its architecture, components, and benefits. 2) What is AWS data pipeline vs. AWS glue? Table of Contents What is an AWS Data Pipeline?

Data Pipeline 59

Data Pipeline AWS Amazon Web Services Data Consolidation 59

Netflix Tech

DECEMBER 21, 2020

There are several benefits of such optimizations like saving on storage, faster query time, cheaper downstream processing, and an increase in developer productivity by removing additional ETLs written only for query performance improvement. We will publish a follow-up blog post about AutoAnalyze in the future.

Data Warehouse 81

Data Warehouse Metadata Algorithm Data 81

ProjectPro

AUGUST 24, 2021

And, out of these professions, this blog will discuss the data engineering job role. The data in Kafka is analyzed with Spark Streaming API, and the data is stored in a column store called HBase. This helps improve customer service, enhance customer loyalty, and generate new revenue streams for the airline.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

NOVEMBER 11, 2014

Confused over which framework to choose for big data processing - Hadoop MapReduce vs. Apache Spark. This blog helps you understand the critical differences between two popular big data frameworks. Spark vs. Hadoop MapReduce Comparison -The Bottomline Will Apache Spark Eliminate Hadoop MapReduce?

Hadoop 40

Hadoop Scala Machine Learning Java 40

Cloudera

JANUARY 19, 2021

Cloudera Flow Management , based on Apache NiFi and part of the Cloudera DataFlow platform , is used by some of the largest organizations in the world to facilitate an easy-to-use, powerful, and reliable way to distribute and process data at high velocity in the modern big data ecosystem. DataFlow Process Group. Flow Development .

Management 65

Management Big Data Ecosystem Kafka AWS 65

ProjectPro

FEBRUARY 8, 2023

Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. For e.g., Finaccel, a leading tech company in Indonesia, leverages AWS Glue to easily load, process, and transform their enterprise data for further processing. billion by 2026?

AWS 98

AWS Scala Metadata Data Lake 98

Netflix Tech

NOVEMBER 3, 2022

This blog post presents how our current iteration of Titus deals with high API call volumes by scaling out horizontally. We introduce a caching mechanism in the API gateway layer, allowing us to offload processing from singleton leader elected controllers without giving up strict data consistency and guarantees clients observe.

Systems 89

Systems Architecture Process AWS 89