Cloudera

DECEMBER 1, 2022

For analytic applications to properly leverage a hybrid, multi-cloud ecosystem to support modern data architectures, data observability has become even more important. The post You Can’t Hit What You Can’t See appeared first on Cloudera Blog. Source: IDC .

Data Lake 81

Data Lake Data Pipeline Data Governance Analytics Application 81

Snowflake

MAY 4, 2023

The way we’d normally design analytical applications is to build something outside of our data environment, manage the infrastructure and compute, connect to Snowflake for the data, take the data back to the compute platform, and give an interface to our users. Click here for all the details.

Portfolio 52

Portfolio Cloud Analytics Application Data Security 52

Rockset

FEBRUARY 18, 2021

times faster than Druid in the latest performance blog post. Real-time analytics is all about deriving insights and taking actions as soon as data is produced. When broken down into its core requirements, real-time analytics means two things: access to fresh data and fast responses to queries. Learn how Rockset is 1.67

Analytics Application 52

Analytics Application SQL Database Structured Data 52

Rockset

MARCH 10, 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! If you want to see all of the key requirements of real-time analytics databases, watch my recent talk at the Hive on Designing the Next Generation of Data Systems for Real-Time Analytics , available below.

Data Analytics 52

Data Analytics Data Warehouse Medical MySQL 52

Rockset

MAY 17, 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!

SQL 52

SQL NoSQL Hadoop MongoDB 52

Rockset

JULY 6, 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!

NoSQL 52

NoSQL SQL Systems PostgreSQL 52

U-Next

SEPTEMBER 21, 2022

And while employing it is a fairly new technology, it already has a wide range of applications. This blog will look at the best contemporary applications of Artificial Intelligence in business. . Applications of AI in Business Operations . Artificial Intelligence in Business .

Insurance 40

Insurance Finance Transportation Machine Learning 40

Knowledge Hut

JUNE 30, 2023

With helpful illustrations and thorough explanations, it assists readers in comprehending how to use Spark for big data processing and analytics applications. Continuously Learn and Stay Curious To broaden your knowledge and skills, read books, follow blogs, join online communities, and engage in data engineering initiatives.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Striim

NOVEMBER 8, 2023

A data mesh is technology-agnostic and underpins four main principles described in-depth in this blog post by Zhamak Dehghani. The four data mesh principles aim to solve major difficulties that have plagued data and analytics applications for a long time.

Architecture 52

Architecture Generalist Government Datasets 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.

Data Warehouse 69

Data Warehouse Cloud Kafka Cloud Storage 69

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

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

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

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. Conclusion In this blog, we demonstrated how we can introduce Kafka as a message broker into a microservices architecture.

Kafka 75

Kafka Architecture AWS Transportation 75

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

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. Most traditional analytics applications like Hive, Spark, Impala, YARN etc.

Systems 100

Systems Hadoop Unstructured Data Media 100

ProjectPro

MAY 20, 2015

There are several big data and business analytics companies that offer a novel kind of big data innovation through unprecedented personalization and efficiency at scale. Which big data analytic companies are believed to have the biggest potential?

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 40

Data Science Blog: Data Engineering

NOVEMBER 15, 2023

An object-centric data model is a big deal because it offers the opportunity for a holistic approach and as a database a single source of truth for Process Mining but also for other types of analytical applications. The post Object-centric Process Mining on Data Mesh Architectures appeared first on Data Science Blog (English only).

Architecture 52

Architecture Database-centric Process BI 52

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

Cloudera

AUGUST 13, 2021

The ability to manage how the data flows and transforms during the first mile of the data pipeline and control the data distribution can accelerate the performance of all analytic applications. The post Why Modernizing the First Mile of the Data Pipeline Can Accelerate all Analytics appeared first on Cloudera Blog.

Data Pipeline 108

Data Pipeline Data Lake ETL Tools Unstructured Data 108

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

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

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.

Machine Learning 64

Machine Learning Data Science Architecture Data Warehouse 64

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). Please refer to our earlier Cloudera blog for more details about Ozone’s performance benefits and atomicity guarantees. The same data can be read as an object, or a file.

Systems 86

Systems Hadoop Metadata Telecommunication 86

Rockset

JANUARY 23, 2024

When building applications on change data capture (CDC) data using Elasticsearch, you’ll want to architect the system to handle frequent updates or modifications to the existing documents in an index. In this blog, we’ll walk through the different options available for updates including full updates, partial updates and scripted updates.

Metadata 52

Metadata Coding Analytics Application Python 52

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

NOVEMBER 2, 2020

In the meantime, if you want to learn more, please check out this video, which shows how to build an end-to-end Event Analytics application in CDP, using Apache Kafka, Apache Druid, Apache Hive, and Cloudera DataViz. The post An Overview of Real Time Data Warehousing on Cloudera appeared first on Cloudera Blog.

Data Warehouse 91

Data Warehouse Kafka Lambda Architecture Telecommunication 91

Cloudera

MARCH 6, 2018

This leads to extra cost, effort, and risk to stitch together a sub-optimal platform for multi-disciplinary, cloud-based analytics applications. The post Altus SDX: Shared services for cloud-based analytics appeared first on Cloudera Blog. Further, much of the value of cloud is for elastic workloads.

Cloud 40

Cloud Metadata Big Data AWS 40

Rockset

MAY 3, 2023

In this blog, we’ll walk through the benchmark framework, configuration and results. We’ll also delve under the hood of the two databases to better understand why their performance differs when it comes to search and analytics on high-velocity data streams. Rockset achieved up to 4x higher throughput and 2.5x

Data Ingestion 59

Data Ingestion Kafka Database Architecture 59

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). Other blogs in this Elasticsearch or Rockset for Real-Time Analytics series: Part 1: Managing Clusters vs Going Serverless Part 2: How Much Query Flexibility Do You Have?

SQL 40

SQL Data Pipeline Kafka Database 40

Rockset

DECEMBER 9, 2019

It continuously ingests raw data from multiple sources--data lakes, data streams, databases--into its storage layer and allows fast SQL access from both visualisation tools and analytic applications.

Data Engineering 40

Data Engineering Data Engineer Raw Data Engineering 40

Cloudera

NOVEMBER 13, 2017

Cloud PaaS takes this a step further and allows users to focus directly on building data pipelines, training machine learning models, developing analytics applications — all the value creation efforts, vs the infrastructure operations. The post The Future of Cloud-based Analytics (Part 3) appeared first on Cloudera Blog.

Cloud 40

Cloud Big Data Metadata Machine Learning 40

Cloudera

APRIL 2, 2019

Apache HBase® is one of many analytics applications that benefit from the capabilities of Intel Optane DC persistent memory. HBase is a distributed, scalable NoSQL database that enterprises use to power applications that need random, real time read/write access to semi-structured data.

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. It’s time for SDX.

Building 40

Building Management Government BI 40

Cloudera

MAY 16, 2018

Arcadia Enterprise runs within the Cloudera data platform and enables business intelligence (BI) and rich visual analytic applications to be built for hundreds of business users working on data in Hadoop. The post Cross-Functional Trade Surveillance appeared first on Cloudera Blog.

Data Lake 41

Data Lake Electronics Media Unstructured Data 41

Cloudera

SEPTEMBER 10, 2018

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. With that in place, what will be your first project?

Data Warehouse 40

Data Warehouse Metadata Retail Cloud 40

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. When Is ZDLC Better Than SDLC?

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Coding Software Engineer Software Engineering Government 52