Workfall

JUNE 27, 2023

In this blog, we’ll explore how to harness the power of Kafka to streamline event streaming within a microservices architecture and unlock its full potential for building scalable and responsive systems. Event-Driven Architectures: Kafka is a natural fit for building event-driven architectures. Let’s get started!

Kafka 75

Kafka Architecture AWS Transportation 75

Knowledge Hut

JUNE 30, 2023

Master the art of data modeling and developing scalable data architectures. With helpful illustrations and thorough explanations, it assists readers in comprehending how to use Spark for big data processing and analytics applications. Key Benefits and Takeaways: Learn the core concepts of big data systems.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Data Science Blog: Data Engineering

NOVEMBER 15, 2023

New big data architectures and, above all, data sharing concepts such as Data Mesh are ideal for creating a common database for many data products and applications. The Event Log Data Model for Process Mining Process Mining as an analytical system can very well be imagined as an iceberg. Click to enlarge!

Architecture 52

Architecture Database-centric Process BI 52

Cloudera

FEBRUARY 9, 2021

A typical approach that we have seen in customers’ environments is that ETL applications pull data with a frequency of minutes and land it into HDFS storage as an extra Hive table partition file. In this way, the analytic applications are able to turn the latest data into instant business insights. Cost-Effective.

Data Warehouse 69

Data Warehouse Cloud Kafka Cloud Storage 69

Rockset

MARCH 19, 2020

Intro In recent years, Kafka has become synonymous with “streaming,” and with features like Kafka Streams, KSQL, joins, and integrations into sinks like Elasticsearch and Druid, there are more ways than ever to build a real-time analytics application around streaming data in Kafka.

Kafka 40

Kafka Database Process SQL 40

Knowledge Hut

JULY 26, 2023

Database applications also help in data-driven decision-making by providing data analysis and reporting tools. In this blog, we will deep dive into database system applications in DBMS, and their components and look at a list of database applications. What are Database Applications? Spatial Database (e.g.-

Database 52

Database NoSQL Telecommunication MongoDB 52

ProjectPro

FEBRUARY 16, 2023

If you are still wondering whether or why you need to master SQL for data engineering, read this blog to take a deep dive into the world of SQL for data engineering and how it can take your data engineering skills to the next level. Did you know SQL is the top skill listed in 73.4% of data engineer job postings on Indeed?

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

Cloudera

NOVEMBER 7, 2023

Are you struggling to manage the ever-increasing volume and variety of data in today’s constantly evolving landscape of modern data architectures? This blog post is intended to provide guidance to Ozone administrators and application developers on the optimal usage of the bucket layouts for different applications.

Systems 100

Systems Hadoop Unstructured Data Media 100

Cloudera

FEBRUARY 8, 2024

Overview This blog post describes support for materialized views for the Iceberg table format. Apache Iceberg is a high-performance open table format for petabyte-scale analytic datasets. In a future blog, we will evaluate the incremental versus full rebuild performance. These tables are created as Iceberg tables.

Metadata 88

Metadata Data Warehouse BI AWS 88

Rockset

OCTOBER 26, 2023

That’s why JetBlue innovates with real-time analytics and AI, using over 15 machine learning applications in production today for dynamic pricing, customer personalization, alerting applications, chatbots and more. BlueML has been central to supporting LLM-based applications and JetBlue’s AI & ML real-time products.

Machine Learning 64

Machine Learning Data Science Architecture Data Warehouse 64

ProjectPro

FEBRUARY 11, 2021

Translate the machine learning models defined by data scientists from environments like Python and R notebooks to analytic applications. Before we end this blog, we’d like to answer a few common questions that revolve around becoming a machine learning engineer. How to become a machine learning engineer without a degree?

Machine Learning 40

Machine Learning Engineering Programming Language Portfolio 40

Rockset

FEBRUARY 24, 2023

Introduction Let’s get this out of the way at the beginning: understanding effective streaming data architectures is hard, and understanding how to make use of streaming data for analytics is really hard. There’s enough content here for its own blog post, but we’ll cover the high-level differences briefly. Kafka or Kinesis ?

Kafka 52

Kafka AWS Amazon Web Services Programming Language 52

Cloudera

SEPTEMBER 15, 2022

In this blog post, we will talk about a single Ozone cluster with the capabilities of both Hadoop Core File System (HCFS) and Object Store (like Amazon S3). A unified storage architecture that can store both files and objects and provide a flexible, scalable, and high-performance system. Bringing files and objects under one roof.

Systems 86

Systems Hadoop Metadata Telecommunication 86

Cloudera

AUGUST 13, 2021

Whether it is consuming log files, sensor metrics, and other unstructured data, most enterprises manage and deliver data to the data lake and leverage various applications like ETL tools, search engines, and databases for analysis. What is the impact on the business? Learn more about Cloudera Edge and Flow Management.

Data Pipeline 108

Data Pipeline Data Lake ETL Tools Unstructured Data 108

Rockset

MAY 3, 2023

In scenarios involving analytics on massive data streams, we’re often asked the maximum throughput and lowest data latency Rockset can achieve and how it stacks up to other databases. In this blog, we’ll walk through the benchmark framework, configuration and results. Rockset achieved up to 4x higher throughput and 2.5x

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Data Ingestion Kafka Database Architecture 59

Rockset

MARCH 15, 2021

The Demands of Real-Time Analytics Real-time analytics applications have specific demands (i.e., and your solution will only be able to provide valuable real-time analytics if you are able to meet them. Indexing Efficiency Indexing data is another crucial requirement for real-time analytics applications.

MongoDB 40

MongoDB Data Ingestion Analytics Application Kafka 40

Cloudera

NOVEMBER 2, 2020

Data streamed in is queryable in conjunction with historical data, avoiding need for Lambda Architecture. Figure 1 below shows a standard architecture for a Real-Time Data Warehouse. Basic Architecture for Real-Time Data Warehousing. These include stream processing/analytics, batch processing, tiered storage (i.e.

Data Warehouse 91

Data Warehouse Kafka Lambda Architecture Telecommunication 91

AltexSoft

OCTOBER 21, 2022

The number of possible applications tends to grow due to the rise of IoT , Big Data analytics , streaming media, smart manufacturing, predictive maintenance , and other data-intensive technologies. Kafka architecture. Kafka cluster architecture. Or stay here to make sense of Kafka’s concepts and structure.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

Rockset

FEBRUARY 25, 2021

Joins are often used in real-time analytics applications to combine streaming data (usually representing events) with static data (like customer information). 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

Cloudera

APRIL 2, 2019

This is achieved through an architecture that fundamentally separates compute from storage. Apache HBase® is one of many analytics applications that benefit from the capabilities of Intel Optane DC persistent memory. Intel Optane DC persistent memory mitigates the I/O bottlenecks associated with these bifurcated environments.

NoSQL 47

NoSQL Google Cloud Hadoop Machine Learning 47

Cloudera

DECEMBER 7, 2017

Now we are releasing the reference architecture for you build your own self-managed SDX foundation for all your cloud-based data and analytics applications. Cloud data that can efficiently drive all your machine learning and analytics initiatives. It’s time for a new approach to analytics in the cloud.

Building 40

Building Management Government BI 40

Cloudera

NOVEMBER 8, 2022

It enables cloud-native applications to store and process mass amounts of data in a hybrid multi-cloud environment and on premises. These could be traditional analytics applications like Spark, Impala, or Hive, or custom applications that access a cloud object store natively. Conclusion.

Metadata 80

Metadata Algorithm Hadoop Cloud 80

Cloudera

SEPTEMBER 10, 2018

IaaS and private cloud are already supported through our reference architecture. Using a team of just three administrators (rather than the 15 they needed before) and thanks to SDX providing single consistent context, they can now deploy their Cloudera analytics applications to no fewer than three public clouds in less than an hour.

Data Warehouse 40

Data Warehouse Metadata Retail Cloud 40

Cloudera

MAY 16, 2018

This post describes how native visual analytics on a Cloudera Enterprise Data Hub is the keystone that supports a holistic trade surveillance program. The post Cross-Functional Trade Surveillance appeared first on Cloudera Blog. Author: Paul Lashmet, Practice Lead and Advisor for Financial Services at North Castle Integration LLC.

Data Lake 41

Data Lake Electronics Media Unstructured Data 41

phData: Data Engineering

MAY 11, 2023

In this blog post, we’ll discuss use cases for Zero-Code Development Life Cycle (ZDLC) in Matillion. Analytics platforms have highly repeatable functional stages that lend themselves to being broken down into separate functional processes. Finally, several Google Sheets are managed as reference data in their architecture.

Coding 52

Coding Software Engineer Software Engineering Government 52

ProjectPro

JANUARY 31, 2023

In this blog, we'll dive into some of the most commonly asked big data interview questions and provide concise and informative answers to help you ace your next big data job interview. Architecture Testing: This testing verifies that data processing is proper and fulfills business requirements. What are the components of Apache HBase?

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

SEPTEMBER 6, 2021

AWS vs. GCP blog compares the two major cloud platforms to help you choose the best one. Table of Contents AWS vs. GCP - The Cloud Battle AWS vs. Popular instances where GCP is used widely are machine learning analytics, application modernization, security, and business collaboration. Let’s get started!

AWS 52

AWS Amazon Web Services Google Cloud Cloud Storage 52

ProjectPro

MAY 23, 2015

.”- said Arun Prasath, a Principal Engineer at WalmartLabs Social Genome Social Genome is a big data analytics solution developed by WalmartLabs that analyses millions and billions of Facebook messages, tweets, YouTube videos, blog postings and more. Walmart Hadoop Interview Questions 1) Explain about Hadoop architecture.

Big Data 52

Big Data Data Analysis Hadoop Retail 52

Cloudera

JUNE 16, 2022

This blog aims to answer two questions as illustrated in the diagram below: How have stream processing requirements and use cases evolved as more organizations shift to “streaming first” architectures and attempt to build streaming analytics pipelines? Conclusion. Not in the manufacturing space? Not to worry.

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Kafka Manufacturing Data Lake SQL 84

Rockset

APRIL 15, 2022

We'll be publishing more posts in the series in the near future, so subscribe to our blog so you don't miss them! We also combined the underlying RocksDB storage engine with our Aggregator-Tailer-Leaf (ALT) architecture so that our indexes are instantly, fully mutable.

Analytics Application 52

Analytics Application Data Warehouse Raw Data Kafka 52

ProjectPro

MAY 31, 2021

This blog lists over 20 big data projects you can work on to showcase your big data skills and gain hands-on experience in big data tools and technologies. Snowflake Real-Time Data Warehouse Project for Beginners Snowflake provides a cloud-based analytics and data storage service called "data warehouse-as-a-service."

Big Data 52

Big Data Coding Project Hadoop 52

Cloudera

NOVEMBER 22, 2021

In addition, how can we enable different application development teams to efficiently collaborate and apply agile DevOps disciplines when they leverage different programming constructs (e.g., different analytical frameworks) for complex use cases that span different stages across the data lifecycle? public, private, hybrid cloud)?

Government 89

Government Hadoop Data Security Data Warehouse 89

phData: Data Engineering

JULY 18, 2023

CDWs are designed for running large and complex queries across vast amounts of data, making them ideal for centralizing an organization’s analytical data for the purpose of business intelligence and data analytics applications.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52