Cloudera

FEBRUARY 9, 2021

Today’s customers have a growing need for a faster end to end data ingestion to meet the expected speed of insights and overall business demand. This ‘need for speed’ drives a rethink on building a more modern data warehouse solution, one that balances speed with platform cost management, performance, and reliability.

Data Warehouse 69

Data Warehouse Cloud Kafka Cloud Storage 69

Snowflake

MARCH 21, 2023

In February, Snowflake launched new features around streaming data ingestion and data governance and improved SQL experience and performance, with enhancements to Search Optimization Service and more. As a result, you should not rely on any forward-looking statements as predictions of future events. © 2023 Snowflake Inc.

Retail 72

Retail Healthcare Data Ingestion Consulting 72

Knowledge Hut

JUNE 26, 2023

When screening resumes, most hiring managers prioritize candidates who have actual experience working on data engineering projects. Top Data Engineering Projects with Source Code Data engineers make unprocessed data accessible and functional for other data professionals. Which queries do you have?

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Confluent

FEBRUARY 6, 2019

The blog posts How to Build and Deploy Scalable Machine Learning in Production with Apache Kafka and Using Apache Kafka to Drive Cutting-Edge Machine Learning describe the benefits of leveraging the Apache Kafka ® ecosystem as a central, scalable and mission-critical nervous system. For now, we’ll focus on Kafka.

Machine Learning 107

Machine Learning Python Kafka Java 107

Data Engineering Podcast

OCTOBER 12, 2020

Are you bogged down by having to manually manage data access controls, repeatedly move and copy data, and create audit reports to prove compliance? Learn how we streamline and accelerate manual processes to help you derive real results from your data at dataengineeringpodcast.com/immuta.

Business Intelligence 100

Business Intelligence BI Consulting Data Ingestion 100

Cloudera

JUNE 28, 2022

In a previous blog of this series, Turning Streams Into Data Products , we talked about the increased need for reducing the latency between data generation/ingestion and producing analytical results and insights from this data. containing data that may have to be used to enrich the streaming data.

Process 81

Process Kafka SQL Machine Learning 81

Rockset

AUGUST 30, 2021

Apache Kafka has made acquiring real-time data more mainstream, but only a small sliver are turning batch analytics, run nightly, into real-time analytical dashboards with alerts and automatic anomaly detection. But until this release, all these data sources involved indexing the incoming raw data on a record by record basis.

SQL 52

SQL Kafka MongoDB MySQL 52

AltexSoft

AUGUST 29, 2023

Examples of unstructured data can range from sensor data in the industrial Internet of Things (IoT) applications, videos and audio streams, images, and social media content like tweets or Facebook posts. Data ingestion Data ingestion is the process of importing data into the data lake from various sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

ProjectPro

DECEMBER 7, 2021

The second step for building etl pipelines is data transformation, which entails converting the raw data into the format required by the end-application. The transformed data is then placed into the destination data warehouse or data lake. It can also be made accessible as an API and distributed to stakeholders.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Pinterest Engineering

AUGUST 18, 2022

The HBase Ecosystem, though having various advantages like strong consistency at row level in high volume requests, flexible schema, low latency access to data, Hadoop integration, etc. However, the speed offered by TiDB backend mode is 50GB/hour so it’s only useful for data migration of smaller tables.

Data Ingestion 52

Data Ingestion Hadoop Database Kafka 52

Confluent

SEPTEMBER 26, 2019

In the early days, many companies simply used Apache Kafka ® for data ingestion into Hadoop or another data lake. However, Apache Kafka is more than just messaging. Some Kafka and Rockset users have also built real-time e-commerce applications , for example, using Rockset’s Java, Node.js

Kafka 21

Kafka BI SQL Datasets 21

Monte Carlo

MARCH 14, 2023

Data ingestion is the process of collecting data from various sources and moving it to your data warehouse or lake for processing and analysis. It is the first step in modern data management workflows. Table of Contents What is Data Ingestion? Decision making would be slower and less accurate.

Data Ingestion 52

Data Ingestion Data Warehouse Lambda Architecture Raw Data 52

Confluent

MAY 7, 2019

Every developer who uses Apache Kafka ® has used a Kafka consumer at least once. Although it is the simplest way to subscribe to and access events from Kafka, behind the scenes, Kafka consumers handle tricky distributed systems challenges like data consistency, failover and load balancing.

Kafka 111

Kafka Accessible Accessibility Metadata 111

Rockset

MAY 3, 2023

To find out, we decided to test the streaming ingestion performance of Rockset’s next generation cloud architecture and compare it to open-source search engine Elasticsearch , a popular sink for Apache Kafka. For this benchmark, we evaluated Rockset and Elasticsearch ingestion performance on throughput and data latency.

Data Ingestion 59

Data Ingestion Kafka Database Architecture 59

Rockset

OCTOBER 11, 2022

In this blog, we’ll compare and contrast how Elasticsearch and Rockset handle data ingestion as well as provide practical techniques for using these systems for real-time analytics. Logstash is an event processing pipeline that ingests and transforms data before sending it to Elasticsearch.

Data Ingestion 52

Data Ingestion Kafka Relational Database PostgreSQL 52

Rockset

NOVEMBER 6, 2019

Events are messages that are sent by a system to notify operators or other systems about a change in its domain. With event-driven architectures powered by systems like Apache Kafka becoming more prominent, there are now many applications in the modern software stack that make use of events and messages to operate effectively.

Kafka 40

Kafka Data Lake SQL Hadoop 40

Monte Carlo

APRIL 24, 2023

In this article, we’ll dive deep into the data presentation layers of the data stack to consider how scale impacts our build versus buy decisions, and how we can thoughtfully apply our five considerations at various points in our platform’s maturity to find the right mix of components for our organizations unique business needs.

Data Pipeline 52

Data Pipeline Building Data Ingestion BI 52

Rockset

APRIL 29, 2019

The setup requires metrics and monitoring to ensure that it is correctly processing events from the DynamoDB stream and able to write into Elasticsearch. In addition, Rockset takes care of security, encryption of data, and role-based access control for managing access to it.

NoSQL 52

NoSQL PostgreSQL AWS SQL 52

Rockset

OCTOBER 4, 2022

Streaming data feeds many real-time analytics applications, from logistics tracking to real-time personalization. Event streams, such as clickstreams, IoT data and other time series data, are common sources of data into these apps. Flink, Kafka and MySQL. The software was subsequently open sourced in 2016.

MySQL 52

MySQL Kafka Aggregated Data Architecture 52

Cloudera

FEBRUARY 10, 2022

Apache NiFi’s rich processor library provides Azure focused processors like ADLS Gen2, Event Hub, Blob Storage or Cosmos DB out of the box. Figure 2: Moving application log data from Azure Event Hub to ADLS Gen2 and SIEM systems. Figure 3: Moving data from Azure Event Hub to ADLS Gen2. SIEM Optimization.

Cloud 114

Cloud Kafka AWS Data Ingestion 114

ProjectPro

AUGUST 24, 2021

Data Engineering Project for Beginners If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of data engineering project examples below. This big data project discusses IoT architecture with a sample use case.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Edureka

FEBRUARY 9, 2023

As the demand for data engineers grows, having a well-written resume that stands out from the crowd is critical. Azure data engineers are essential in the design, implementation, and upkeep of cloud-based data solutions. It is also crucial to have experience with data ingestion and transformation.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Cloudera

JANUARY 11, 2021

I want to thank you all for joining and attending these events! I received hundreds of questions during these events, and my colleagues and I tried to answer as many as we could. Why use NiFi when one can use Kafka as an entry point to the cluster. Here are ways you can determine when to use NiFi and when to use Kafka. .

Kafka 60

Kafka Data Cleanse Java Datasets 60

Data Engineering Weekly

NOVEMBER 13, 2022

Streaming and batch unified in a single platform No Airflow - orchestration inferred from the data $99 / TB of data ingested | transformations free Start Your 30 Day Trial Wealthfront: Event Tracking System at Wealthfront A robust event-tracking system is critical for an efficient data management platform.

Data Engineering 52

Data Engineering Data Engineer Engineering Kafka 52

ProjectPro

JANUARY 25, 2022

Features of PySpark Features that contribute to PySpark's immense popularity in the industry- Real-Time Computations PySpark emphasizes in-memory processing, which allows it to perform real-time computations on huge volumes of data. PySpark is used to process real-time data with Kafka and Streaming, and this exhibits low latency.

Big Data 52

Big Data Data Process Process Kafka 52

Monte Carlo

JUNE 14, 2023

This frequently involves, in some order, extraction (from a source system), transformation (where data is combined with other data and put into the desired format), and loading (into storage where it can be accessed). Most organizations deploy some or all of these data pipeline architectures.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Confluent

OCTOBER 10, 2019

A key challenge, however, is integrating devices and machines to process the data in real time and at scale. Apache Kafka ® and its surrounding ecosystem, which includes Kafka Connect, Kafka Streams, and KSQL, have become the technology of choice for integrating and processing these kinds of datasets. Example: Severstal.

Kafka 20

Kafka Google Cloud Architecture Machine Learning 20

Confluent

MAY 22, 2019

In light of this, we’ll share an emerging machine-to-machine (M2M) architecture pattern in which MQTT, Apache Kafka ® , and Scylla all work together to provide an end-to-end IoT solution. Sensors generate data points while actuators are mechanical components that may be controlled through commands. What is Apache Kafka?

Kafka 97

Kafka Google Cloud NoSQL Entertainment 97

ProjectPro

DECEMBER 28, 2021

Managing, processing, and streamlining large datasets in real-time is a key functionality of big data analytics in an enterprise to enhance decision-making. Data analytics also helps organizations understand their customers better, narrow down their target audiences, and improve marketing campaigns.

Architecture 52

Architecture Kafka Java Scala 52

Netflix Tech

MARCH 25, 2019

Nonetheless, Netflix data landscape (see below) is complex and many teams collaborate effectively for sharing the responsibility of our data system management. As a result, a single consolidated and centralized source of truth does not exist that can be leveraged to derive data lineage truth. push or pull.

Building 87

Building Metadata Transportation Data Ingestion 87

Rockset

NOVEMBER 28, 2022

Today, I’m excited to share a few product updates we’ve been working on related to real-time Change Data Capture (CDC), including early access for popular templates and 3rd-party CDC platforms. First, CDC theoretically allows companies to analyze and react to data in real time, as it’s generated.

Data Warehouse 52

Data Warehouse PostgreSQL MongoDB Data Pipeline 52

Rockset

JUNE 8, 2023

Many development teams turn to DynamoDB for building event-driven architectures and user-friendly, performant applications at scale. The cost of provisioned write capacity grows linearly with the number of GSIs configured, making it cost prohibitive to use many GSIs to support many access patterns.

NoSQL 52

NoSQL AWS SQL Database 52

Monte Carlo

JUNE 14, 2022

A few people trickle in on day one, a bit more at the welcome event. After Day One, these events slowly lose steam until only the most fanatical conference warriors are roaming exhibitor booths late Thursday morning. Christian then announced a new way to ingest data in Snowflake: Snowpipe streaming.

Cloud 52

Cloud Data Ingestion Government Python 52

Rockset

DECEMBER 20, 2018

We live in a world where diverse systems—social networks, monitoring, stock exchanges, websites, IoT devices—all continuously generate volumes of data in the form of events, captured in systems like Apache Kafka and Amazon Kinesis. You need to have a Twitter developer account in order to get access to the Twitter Streaming API.

AWS 52

AWS Kafka Data Ingestion Data 52

Confluent

OCTOBER 16, 2019

Trains are an excellent source of streaming data—their movements around the network are an unbounded series of events. Using this data, Apache Kafka ® and Confluent Platform can provide the foundations for both event-driven applications as well as an analytical platform. Ingesting the data.

Kafka 19

Kafka Building Data Coding 19

Snowflake

MARCH 30, 2023

3EJHjvm Once a business need is defined and a minimal viable product ( MVP ) is scoped, the data management phase begins with: Data ingestion: Data is acquired, cleansed, and curated before it is transformed. Feature engineering: Data is transformed to support ML model training. ML workflow, ubr.to/3EJHjvm

Engineering 82

Engineering Raw Data Data Science Scala 82

phData: Data Engineering

JANUARY 3, 2022

The big data analytics market is set to reach $103 billion by 2023 , with poor data quality costing the US economy up to $3.1 Fortune 1000 companies can gain more than $65 million additional net income, only by increasing their data accessibility by 10%. What is Data Governance? trillion yearly.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52