ProjectPro

JUNE 28, 2016

Apache Kafka is breaking barriers and eliminating the slow batch processing method that is used by Hadoop. This is just one of the reasons why Apache Kafka was developed in LinkedIn. Kafka was mainly developed to make working with Hadoop easier. This data is constantly changing, and is voluminous.

Kafka 40

Kafka Systems Hadoop Big Data 40

Cloudera

FEBRUARY 16, 2021

Integrated across the Enterprise Data Lifecycle . Cloudera Operational Database (COD) plays the crucial role of a data store in the enterprise data lifecycle. You can use COD with: Cloudera DataFlow to ingest and aggregate data from various sources. Cloudera Data Warehouse to perform ETL operations.

Database 83

Database Machine Learning Kafka Aggregated Data 83

Lyft Engineering

JUNE 28, 2023

At the time of writing, a Mapping team is working to utilize theEvent Driven Decisions product to rebuild Lyft’s Traffic infrastructure by aggregating data per geohash and applying a model. Shortly after we built it, it was utilized by another pod within our team to build a Real-time Anomaly Detection product.

Machine Learning 120

Machine Learning Building Kafka Metadata 120

Cloudera

FEBRUARY 9, 2023

The sudden failing of a complex data pipeline can lead to devastating consequences — especially if it goes unnoticed. This is why we build job notifications functionality into SSB, to deliver maximum reliability in your complex real-time data pipelines.

SQL 79

SQL Kafka Aggregated Data Architecture 79

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

Netflix Tech

JULY 12, 2019

Gatekeeper accomplishes its prescribed task by aggregating data from multiple upstream systems, applying some business logic, then producing an output detailing the status of each video in each country. If a message from the Kafka topic contains the exact same data as already reflected in the Hollow dataset, no action is taken.

Datasets 73

Datasets Kafka Architecture Computer Science 73

Striim

JULY 31, 2024

Why Striim Stands Out As detailed in the GigaOm Radar Report, Striim’s unified data integration and streaming service platform excels due to its distributed, in-memory architecture that extensively utilizes SQL for essential operations such as transforming, filtering, enriching, and aggregating data.

Aggregated Data 52

Aggregated Data Data Ingestion Java Kafka 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. The broad adoption of Apache Kafka has helped make these event streams more accessible.

MySQL 52

MySQL Kafka Aggregated Data Architecture 52

Rockset

APRIL 18, 2023

Rockset offers a number of benefits along with vector search support to create relevant experiences: Real-Time Data: Ingest and index incoming data in real-time with support for updates. Feature Generation: Transform and aggregate data during the ingest process to generate complex features and reduce data storage volumes.

Unstructured Data 105

Unstructured Data Metadata Machine Learning SQL 105

LinkedIn Engineering

DECEMBER 20, 2023

The feedback loop serves as a critical component of a dynamic defense strategy, constantly monitoring and aggregating data from abuse reports, member feedback, and reviewer input. By scrutinizing patterns with abuse data, we pinpoint emerging trends, allowing us to fine-tune our models and systems in real-time.

Building 91

Building Algorithm Kafka Machine Learning 91

DoorDash Engineering

OCTOBER 17, 2023

We stream these events to Kafka and then store them in Snowflake. Users can query this data to troubleshoot their experiments. We then send this aggregated data to another Kafka topic. Next, we had to save the data that is aggregated by the time-window into a datastore. For this we used Apache Pinot.

Education 87

Education Kafka Algorithm Data Warehouse 87

ProjectPro

DECEMBER 7, 2021

In other words, you will write codes to carry out one step at a time and then feed the desired data into machine learning models for training sentimental analysis models or evaluating sentiments of reviews, depending on the use case. You can use big-data processing tools like Apache Spark , Kafka , and more to create such pipelines.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

LinkedIn Engineering

DECEMBER 19, 2023

This framework operates on the scheduler, periodically polls relevant metrics, aggregates data, and determines which nodes have drifted. This process continuously sends metadata information to Kafka , including health reports and version data, among other details.

Big Data 92

Big Data Hadoop Metadata Data 92

Lyft Engineering

SEPTEMBER 27, 2022

It produces high-quality signals and publishes them to Kafka topics. The second type of pipeline ingests Kafka topics and aggregates data into standard ML features. The first type of pipeline was mainly for event ingestion, filtration, hydration, and metadata tagging.

Kafka 52

Kafka Aggregated Data Machine Learning Architecture 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

Rockset

NOVEMBER 1, 2022

Step 1: Data Acquisition Elasticsearch is rarely the system of record which means the data in it comes from somewhere else for real-time analytics. Rockset has built-in connectors to stream real-time data for testing and simulating production workloads including Apache Kafka , Kinesis and Event Hubs.

Database-centric 52

Database-centric SQL Pipeline-centric Aggregated Data 52

Rockset

FEBRUARY 16, 2024

Furthermore, Rockset’s ability to pre-aggregate data at ingestion time reduced the cost of storage and sped up queries, making the solution cost-effective at scale. With Rockset’s flexible data model , the team could easily define new metrics, add new data and onboard customers without significant engineering resources.

Architecture 59

Architecture SQL Data Warehouse Database 59

ProjectPro

AUGUST 24, 2021

This architecture shows that simulated sensor data is ingested from MQTT to Kafka. The data in Kafka is analyzed with Spark Streaming API, and the data is stored in a column store called HBase. Finally, the data is published and visualized on a Java-based custom Dashboard. This is called Hot Path.

Data Engineer 52

Data Engineer Data Engineering Coding Project 52

AltexSoft

MARCH 14, 2023

Additionally, this modularity can help prevent vendor lock-in, giving organizations more flexibility and control over their data stack. Many components of a modern data stack (such as Apache Airflow, Kafka, Spark, and others) are open-source and free. Offered as open-source with active support by communities.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Edureka

FEBRUARY 6, 2023

To supervise real-time business metric aggregation, data warehousing and querying, schema and data management, and related duties, familiarity with the computer coding languages python, java, Kafka, hive, or storm may be required.

Data Engineer 52

Data Engineer Data Engineering Engineering Amazon Web Services 52

Ascend.io

SEPTEMBER 14, 2023

Use Case: Storing data with PostgreSQL (example) import psycopg2 conn = psycopg2.connect(dbname="mydb", Tailored libraries like PySpark Streaming and Kafka-Python have made real-time data analysis and event processing a streamlined affair in Python. csv') data_excel = pd.read_excel('data2.xlsx')

Data Engineer 52

Data Engineer Data Engineering Python Engineering 52

ProjectPro

NOVEMBER 15, 2021

It was built from the ground up for interactive analytics and can scale to the size of Facebook while approaching the speed of commercial data warehouses. Presto allows you to query data stored in Hive, Cassandra, relational databases, and even bespoke data storage. CMAK is developed to help the Kafka community.

Big Data 52

Big Data Project Metadata Programming Language 52

Rockset

FEBRUARY 25, 2021

Rockset, on the other hand, provides full-featured SQL and an API endpoint interface that allows developers to quickly join across data sources like DynamoDB and Kafka. With the many data sources in today’s modern architecture, this can be difficult. From there, you can join and aggregate data without using complex code.

SQL 40

SQL Data Pipeline Kafka Database 40

Knowledge Hut

NOVEMBER 17, 2023

To be an Azure Data Engineer, you must have a working knowledge of SQL (Structured Query Language), which is used to extract and manipulate data from relational databases. You should be able to create intricate queries that use subqueries, join numerous tables, and aggregate data.

Data Engineer 52

Data Engineer Data Engineering Engineering Scala 52

AltexSoft

SEPTEMBER 21, 2023

Resource intensive tool While Elasticsearch excels in speed and performance, it’s important to note that it can be CPU-intensive, especially when handling multiple tasks like indexing, searching, and aggregating data concurrently. Framework Programming The Good and the Bad of Node.js

Engineering 52

Engineering NoSQL Programming Language Java 52

phData: Data Engineering

JANUARY 3, 2022

This likely requires you to aggregate data from your ERP system, your supply chain system, potentially third-party vendors, and data around your internal business structure. Once the data has been collected from each system, a data engineer can determine how to optimally join the data sets.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Governance 52

Rockset

DECEMBER 22, 2020

By using Rockset, we may have to Tokenize our search fields on ingestion however we make up for it in firstly, the simplicity of processing this data on ingestion as well as easier querying, joining, and aggregating data. Read more about how Rockset compares to Elasticsearch and explore how to migrate to Rockset.

SQL 40

SQL Data MongoDB Building 40

Rockset

SEPTEMBER 13, 2022

Further, data is king, and users want to be able to slice and dice aggregated data as needed to find insights. Users don't want to wait for data engineers to provision new indexes or build new ETL chains. They want unfettered access to the freshest data available.

SQL 52

SQL Database Relational Database NoSQL 52

ProjectPro

JULY 27, 2021

It involves creating a visual representation of an entire system of data or a part of it. The process of data modeling begins with stakeholders providing business requirements to the data engineering team. Data warehouse Operational database Data warehouses generally support high-volume analytical data processing - OLAP.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

Picnic Engineering

SEPTEMBER 8, 2022

We use the RabbitMQ Source connector for Apache Kafka Connect. One may wonder why don’t we replace RabbitMQ with Apache Kafka everywhere? In order to answer the first question, we should take a closer look at the difference between RabbitMQ and Apache Kafka in terms of services parallelism.

Kafka 52

Kafka Metadata AWS Java 52

Rockset

APRIL 15, 2022

Explosion in Streaming Data Before Kafka, Spark and Flink, streaming came in two flavors: Business Event Processing (BEP) and Complex Event Processing (CEP). Many (Kafka, Spark and Flink) were open source. Rockset not only continuously ingests data, but also can “rollup” the data as it is being generated.

Analytics Application 52

Analytics Application Data Warehouse Kafka Database 52

ProjectPro

APRIL 20, 2017

There are various kinds of hadoop projects that professionals can choose to work on which can be around data collection and aggregation, data processing, data transformation or visualization. You will be introduced to exciting Big Data Tools like AWS, Kafka, NiFi, HDFS, PySpark, and Tableau.

Hadoop 40

Hadoop Big Data Coding Project 40