ProjectPro

FEBRUARY 16, 2023

The demand for skilled data engineers who can build, maintain, and optimize large data infrastructures does not seem to slow down any sooner. Even Fortune 500 businesses (Facebook, Google, and Amazon) that have created their own high-performance database systems also typically use SQL to query data and conduct analytics.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

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. Postgres), and maybe even data lake (i.e.

Kafka 40

Kafka Database Process SQL 40

ProjectPro

FEBRUARY 11, 2021

Having that designation means you can build end-to-end machine learning solutions , which is a highly marketable skill set considering the fact that it has been the fastest-growing job title in the world since 2019. That’s very savvy because machine learning engineers are the Swiss Army Knife of the data world.

Machine Learning 40

Machine Learning Engineering Programming Language Portfolio 40

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? Employees get add on dental, health benefits, a wellness program.

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 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. Rockset provides the speed and scale required of ML applications accessed daily by over 2,000 employees at JetBlue.

Machine Learning 64

Machine Learning Data Science Architecture Data Warehouse 64

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

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

Cloudera

NOVEMBER 2, 2020

As an example of this, in this post we look at Real Time Data Warehousing (RTDW), which is a category of use cases customers are building on Cloudera and which is becoming more and more common amongst our customers. They chose to build their RTDW on Cloudera. Optimized access to both full fidelity raw data and aggregations.

Data Warehouse 91

Data Warehouse Kafka Lambda Architecture Telecommunication 91

Rockset

FEBRUARY 25, 2021

Often this lack of structure forces developers to spend a lot of their time engineering ETL and data pipelines so that analysts can access the complex datasets. Joins, in particular, are rarely well supported by alternative real-time analytics solutions. Instead, this data is often semi-structured in JSON or arrays.

SQL 40

SQL Data Pipeline Kafka Database 40

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. Altus SDX enables companies to more easily build and deploy high-value applications for customer analytics, IoT, cyber-security, and more.

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

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. This simplifies the process and in turn makes it more flexible to change later on.

Data Engineering 40

Data Engineering Data Engineer Raw Data Engineering 40

Cloudera

APRIL 2, 2019

Cloudera and Intel have a long history of innovation, driving big data analytics and machine learning into the enterprise with unparalleled performance and security. We are pleased to build upon that direction with our collaboration on Intel® Optane DC persistent memory. Intel does not guarantee any costs or cost reduction.

NoSQL 47

NoSQL Google Cloud Hadoop Machine Learning 47

phData: Data Engineering

MAY 11, 2023

The next-generation Matillion Designer SaaS offering balances accessibility with a very minor learning curve on Git. ZDLC is a time-honored practice among data professionals who have grown their careers with the productivity tools available to most business users, such as Microsoft Excel and Access. When Is ZDLC Better Than SDLC?

Coding 52

Coding Software Engineer Software Engineering Government 52

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. We’re here to help.

Cloud 40

Cloud Big Data Metadata Machine Learning 40

Cloudera

MAY 16, 2018

Not moving data mitigates data loss, ensuring data integrity and if the platform security of the data lake is inherited, then the data will only be viewed by those with proper access. Native visual analytics on a data lake improves the economics of a holistic trade surveillance strategy. Going Forward: Improved Economics. Conclusion.

Data Lake 41

Data Lake Electronics Media Unstructured Data 41

AltexSoft

OCTOBER 21, 2022

Banks, car manufacturers, marketplaces, and other businesses are building their processes around Kafka to. process data in real time and run streaming analytics. However, there is a range of open-source client libraries enabling you to build Kafka data pipelines with practically any popular programming language or framework.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

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. The Hadoop MapReduce architecture has a Distributed Cache feature that allows applications to cache files.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Cloudera

NOVEMBER 9, 2018

Armed with those personal data, cybercrooks could use them to illegally access a victim’s bank account or create a composite of the individual to commit offline crimes such as burglary, extortion, or fraud. Building the foundation of safe cities. Drive real-time processing and analytics to IoT data – both in motion and at rest.

Machine Learning 56

Machine Learning Banking Government Media 56

ProjectPro

MAY 23, 2015

Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization Walmart was the world’s largest retailer in 2014 in terms of revenue. We want to know who every person in the world is. And we want to have the ability to connect them together in a transaction.”

Big Data 52

Big Data Data Analysis Hadoop Retail 52

Cloudera

JUNE 16, 2022

The ability to perform analytics on data as it is created and collected (a.k.a. Organizations are increasingly building low-latency, data-driven applications, automations, and intelligence from real-time data streams. CSP was recently recognized as a leader in the 2022 GigaOm Radar for Streaming Data Platforms report.

Kafka 84

Kafka Manufacturing Data Lake SQL 84

Cloudera

OCTOBER 12, 2020

Eventador, based in Austin, TX, was founded by Erik Beebe and Kenny Gorman in 2016 to address a fundamental business problem – make it simpler to build streaming applications built on real-time data. This typically involved a lot of coding with Java, Scala or similar technologies. Stay tuned for more product updates coming soon!

Cloud 131

Cloud Process Scala Kafka 131

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. To build a big data project, you should always adhere to a clearly defined workflow. The first crucial step to launching your project initiative is to have a solid project plan.

Big Data 52

Big Data Coding Project Hadoop 52

Cloudera

MARCH 2, 2021

However, in the typical enterprise, only a small team has the core skills needed to gain access and create value from streams of data. Contrast that with the skills honed over decades for gaining access, building data warehouses, performing ETL, creating reports and/or applications using structured query language (SQL).

SQL 111

SQL Data Lake Java Scala 111

phData: Data Engineering

JULY 18, 2023

Imagine a world where all of your data is organized, easily accessible, and routinely leveraged to drive impactful outcomes. With the birth of cloud data warehouses, data applications, and generative AI , processing large volumes of data faster and cheaper is more approachable and desired than ever.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

Cloudera

NOVEMBER 22, 2021

For example, organizations with existing on-premises environments that are trying to extend their analytical environment to the public cloud and deploy hybrid-cloud use cases need to build their own metadata synchronization and data replication capabilities. benchmarking study conducted by independent 3rd party ). Conclusion .

Government 89

Government Hadoop Data Security Data Warehouse 89