Striim

NOVEMBER 8, 2023

Data Mesh is revolutionizing event streaming architecture by enabling organizations to quickly and easily integrate real-time data, streaming analytics, and more. In this article, we will explore the advantages and limitations of data mesh, while also providing best practices for building and optimizing a data mesh with Striim.

Architecture 52

Architecture Generalist Government Datasets 52

Knowledge Hut

JUNE 30, 2023

The demand for experienced data engineers continuously expands in today's data-driven environment. Books on data engineering serve as essential resources to guide you through the vast terrain of data engineering. What is Data Engineering? Who are Data Engineers? Who are Data Engineers?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Rockset

JANUARY 30, 2024

In 2023, Rockset announced a new cloud architecture for search and analytics that separates compute-storage and compute-compute. With this architecture, users can separate ingestion compute from query compute, all while accessing the same real-time data. minutes to batch load the data. minutes Ingestion compute saving (1-(( 16.7

Data Ingestion 64

Data Ingestion Utilities Architecture SQL 64

Cloudera

DECEMBER 1, 2022

Full-stack observability is a critical requirement for effective modern data platforms to deliver the agile, flexible, and cost-effective environment organizations are looking for. RI is a global leader in the design and deployment of large-scale, production-level modern data platforms for the world’s largest enterprises.

Data Lake 84

Data Lake Data Pipeline Data Governance Analytics Application 84

Snowflake

MAY 4, 2023

The market volatility we’ve seen in recent years has only underscored the value of using data to model and analyze market behavior and avoid to manage risk for the Street. In the end, we want all of DTCC’s data securely accessible to our internal and external stakeholders. This presents what I like to call an “efficiency opportunity.”

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.

Analytics Application 52

Analytics Application SQL Database Structured Data 52

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 72

Data Warehouse Cloud Kafka Cloud Storage 72

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. At the heart of these data engineering skills lies SQL that helps data engineers manage and manipulate large amounts of data. of data engineer job postings on Indeed?

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

Rockset

MAY 17, 2022

This is the fourth post in a series by Rockset's CTO Dhruba Borthakur on Designing the Next Generation of Data Systems for Real-Time Analytics. We'll be publishing more posts in the series in the near future, so subscribe to our blog so you don't miss them! As a result, the use cases remained firmly in batch mode.

SQL 52

SQL NoSQL Hadoop MongoDB 52

Rockset

JULY 6, 2022

This is the fifth post in a series by Rockset's CTO and Co-founder Dhruba Borthakur on Designing the Next Generation of Data Systems for Real-Time Analytics. We'll be publishing more posts in the series in the near future, so subscribe to our blog so you don't miss them! Traditionally, schemas are strictly enforced.

NoSQL 52

NoSQL SQL Systems PostgreSQL 52

U-Next

SEPTEMBER 21, 2022

It is becoming vital in new ways, from anticipating customer behavior to decreasing data entry. . 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. . Human failings are a fact.

Insurance 40

Insurance Finance Transportation Machine Learning 40

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 have become vital in current business environments because they enable effective data management, integration, privacy, collaboration, analysis, and reporting. Database applications also help in data-driven decision-making by providing data analysis and reporting tools.

Database 52

Database NoSQL Telecommunication MongoDB 52

ProjectPro

MAY 20, 2015

It is difficult to stay up-to-date with the latest developments in IT industry especially in a fast growing area like big data where new big data companies, products and services pop up daily. With the explosion of Big Data, Big data analytics companies are rising above the rest to dominate the market.

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 40

Data Science Blog: Data Engineering

NOVEMBER 15, 2023

In addition to Business Intelligence (BI), Process Mining is no longer a new phenomenon, but almost all larger companies are conducting this data-driven process analysis in their organization. The Event Log Data Model for Process Mining Process Mining as an analytical system can very well be imagined as an iceberg.

Architecture 52

Architecture Database-centric Process BI 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. Apache Iceberg forms the core foundation for Cloudera’s Open Data Lakehouse with the Cloudera Data Platform (CDP).

Metadata 91

Metadata Data Warehouse BI AWS 91

Workfall

JUNE 27, 2023

Reading Time: 7 minutes The world of creating real-time applications can get complex when we have to consider latency, fault tolerance, scalability, and possible data losses. Traditionally, web sockets were the go-to option when it came to real-time applications, but think of a situation whereby there’s server downtime.

Kafka 75

Kafka Architecture AWS Transportation 75

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 105

Systems Hadoop Unstructured Data Media 105

Cloudera

AUGUST 13, 2021

Every enterprise is trying to collect and analyze data to get better insights into their business. 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.

Data Pipeline 111

Data Pipeline Data Lake ETL Tools Unstructured Data 111

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. What Is Streaming Data? We’re going to start with a basic question: what is streaming data? Kafka or Kinesis ?

Kafka 52

Kafka AWS Amazon Web Services Programming Language 52

ProjectPro

FEBRUARY 11, 2021

That’s very savvy because machine learning engineers are the Swiss Army Knife of the data world. Before we forget, we want to make sure you know about our end-to-end solved data science and machine learning projects that are designed to help any mid-career professional kick-start their machine learning career.

Machine Learning 40

Machine Learning Engineering Programming Language Portfolio 40

Cloudera

NOVEMBER 2, 2020

Users today are asking ever more from their data warehouse. 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. Ingest 100s of TB of network event data per day .

Data Warehouse 97

Data Warehouse Kafka Lambda Architecture Telecommunication 97

Rockset

OCTOBER 26, 2023

JetBlue is the data leader in the airline industry using data to offer industry-leading customer experiences and disruptive low fares to popular destinations around the world. The complexity of the data and situation can be hard to quickly comprehend and take action on without the assistance of machine learning.

Machine Learning 64

Machine Learning Data Science Architecture Data Warehouse 64

Rockset

MAY 3, 2023

Rockset is a database used for real-time search and analytics on streaming data. 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. Why measure streaming data ingestion?

Data Ingestion 59

Data Ingestion Kafka Database Architecture 59

Rockset

MARCH 15, 2021

This includes making the data available for query as soon as it is ingested, creating proper indexes on the data so that the query latency is very low, and much more. Before it can be ingested, there’s usually a data pipeline for transforming incoming data. latency, indexing, etc.), Let’s look at some examples.

MongoDB 40

MongoDB Data Ingestion Analytics Application Kafka 40

Cloudera

SEPTEMBER 15, 2022

Apache Ozone is a distributed, scalable, and high-performance object store , available with Cloudera Data Platform (CDP), that can scale to billions of objects of varying sizes. Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases. Diversity of workloads.

Systems 87

Systems Hadoop Metadata Telecommunication 87

Rockset

DECEMBER 9, 2019

As a data engineer, my time is spent either moving data from one place to another, or preparing it for exposure to either reporting tools or front end users. As data collection and usage have become more sophisticated, the sources of data have become a lot more varied and disparate, volumes have grown and velocity has increased.

Data Engineering 40

Data Engineering Data Engineer Raw Data Engineering 40

Rockset

JANUARY 23, 2024

Elasticsearch is an open-source search and analytics engine based on Apache Lucene. 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. million on average.

Metadata 52

Metadata Coding Analytics Application Python 52

Cloudera

DECEMBER 7, 2017

Cloud promises many advantages as an environment for machine learning and analytics. Cloud makes it fast and easy to spin up resources for new applications. Cloud offers elasticity of those resources to efficiently support transient analytics workloads and data pipelines. There is a better way.

Building 40

Building Management Government BI 40

Cloudera

NOVEMBER 8, 2022

Ozone is able to scale to billions of objects and hundreds petabytes of data. It enables cloud-native applications to store and process mass amounts of data in a hybrid multi-cloud environment and on premises. Current releases of Ozone in the Cloudera Data Platform (CDP) are using the write pipeline V1.

Metadata 84

Metadata Algorithm Hadoop Cloud 84

Cloudera

MARCH 6, 2018

The real power in machine learning and analytics is when multiple analytics disciplines are able to work together in concert, sharing data in service of solving more complex and more valuable questions. Instead, they have separate data stores and inconsistent (if any) frameworks for data governance, management, and security.

Cloud 40

Cloud Metadata Big Data AWS 40

Rockset

FEBRUARY 25, 2021

It’s difficult to create data analytics systems that can easily query across your various data sources while maintaining fast performance and real-time capabilities. Two of these real-time analytics solutions are Elasticsearch and Rockset. Instead, this data is often semi-structured in JSON or arrays.

SQL 40

SQL Data Pipeline Kafka Database 40

phData: Data Engineering

MAY 11, 2023

Practices centered on software engineering principles can create a barrier to entry for teams with skilled data wranglers looking to take their infrastructure to the next level with cloud-native tools like Matillion for the Snowflake Data Cloud. This can be achieved by “widening the aperture of users who can make data business-ready.”

Coding 52

Coding Software Engineer Software Engineering Government 52

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. When in memory mode, the data is not saved in the event of a power loss. This is achieved through an architecture that fundamentally separates compute from storage.

NoSQL 48

NoSQL Google Cloud Hadoop Machine Learning 48

Cloudera

NOVEMBER 13, 2017

As the market moves toward cloud-based big data and analytics, three qualities emerge as vital for success. End-user focused tools accelerate daily tasks like job submission, performance tuning, and workload analytics. The net result is much improved productivity for data engineers, data scientists, and analysts.

Cloud 40

Cloud Big Data Metadata Machine Learning 40

Cloudera

NOVEMBER 9, 2018

Reflect back on the recent SingHealth breach in Singapore, in which non-medical personal data of 1.5 Although the hackers did not amend the compromised records, the stolen data – such as patients’ names, national identification numbers, and home addresses – could have been sold to the dark web.

Machine Learning 57

Machine Learning Banking Government Media 57

ProjectPro

MAY 23, 2015

It takes in approximately $36 million dollars from across 4300 US stores everyday.This article details into Walmart Big Data Analytical culture to understand how big data analytics is leveraged to improve Customer Emotional Intelligence Quotient and Employee Intelligence Quotient. How Walmart is tracking its customers?

Big Data 52

Big Data Data Analysis Hadoop Retail 52