Snowflake

MAY 4, 2023

DTCC stands at the center of global trading activity, processing trillions of dollars of securities transactions on a daily basis. This year, DTCC celebrates its 50th anniversary, and over the past five decades we’ve led the financial services industry through unprecedented historical events and market disruptions.

Portfolio 52

Portfolio Cloud Analytics Application Data Security 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!

SQL 52

SQL NoSQL Hadoop MongoDB 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. First, an obligatory aside on real-time analytics.

Kafka 40

Kafka Database Process SQL 40

Striim

NOVEMBER 8, 2023

Data mesh technology also employs event-driven architectures and APIs to facilitate the exchange of data between different systems. This allows for two-way integration so that information can flow from one system to another in real-time. Marketing teams should have easy access to the analytical data they need for campaigns.

Architecture 52

Architecture Generalist Government Datasets 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

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? Columnar Database (e.g.-

Database 52

Database NoSQL Telecommunication MongoDB 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 . AI for Applications in Marketing and E-Commerce .

Insurance 40

Insurance Finance Transportation Machine Learning 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. This aspect can be applied well to Process Mining, hand in hand with BI and AI. This is where the processes are filtered and analyzed.

Architecture 52

Architecture Database-centric Process BI 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. Your SQL skills as a data engineer are crucial for data modeling and analytics tasks.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 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

Cloudera

SEPTEMBER 15, 2022

Retail, where big data is used across all stages of the retail process—from product development, pricing, demand forecasting, and for inventory optimization in the stores. 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).

Systems 86

Systems Hadoop Metadata Telecommunication 86

ProjectPro

FEBRUARY 11, 2021

Implement statistical analysis and machine learning into highly available and high performance production level systems to provide ease of access to users. Automate feature engineering , model training, and evaluation process. Train and re-train machine learning systems as and when required.

Machine Learning 40

Machine Learning Engineering Programming Language Portfolio 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. We want to always have unified data which is broadcasted to all the client applications simultaneously without any latency.

Kafka 75

Kafka Architecture AWS Transportation 75

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. Stream processing or an OLAP database? Third, events on their own are not ideal for understanding the current state of a system.

Kafka 52

Kafka AWS Amazon Web Services Programming Language 52

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? “It’s not a “butt in seat” culture.

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 40

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. It’s too costly to move the data to another application. What is the impact on the business?

Data Pipeline 108

Data Pipeline Data Lake ETL Tools Unstructured Data 108

Rockset

MARCH 15, 2021

When working with a real-time analytics system you need your database to meet very specific requirements. You want this pipeline to take as little time as possible, because stale data doesn’t provide any value in a real-time analytics system. Logically then, latency has to be as low as possible for real-time analytics.

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. A core enabler of the speed of ML development with BlueML is the flexibility of the underlying database system.

Machine Learning 64

Machine Learning Data Science Architecture Data Warehouse 64

AltexSoft

OCTOBER 21, 2022

Similar to Google in web browsing and Photoshop in image processing, it became a gold standard in data streaming, preferred by 70 percent of Fortune 500 companies. Apache Kafka is an open-source, distributed streaming platform for messaging, storing, processing, and integrating large data volumes in real time. What is Kafka?

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

phData: Data Engineering

MAY 11, 2023

For Matillion ETL, the Git integration requires a stronger understanding of the workflows and systems to effectively manage a larger team. An analytics program’s maturity curve is not navigated by all members at the same rate. In this blog post, we’ll discuss use cases for Zero-Code Development Life Cycle (ZDLC) in Matillion.

Coding 52

Coding Software Engineer Software Engineering Government 52

Cloudera

NOVEMBER 2, 2020

On the technical side, it is cheaper and easier than ever to instrument everything and send that data in real-time through a messaging system. An AdTech company in the US provides processing, payment, and analytics services for digital advertisers. Data processing and analytics drive their entire business.

Data Warehouse 91

Data Warehouse Kafka Lambda Architecture Telecommunication 91

Rockset

MAY 3, 2023

Throughput measures the rate at which data is processed, impacting the database's ability to efficiently support high-velocity data streams. In this blog, we’ll walk through the benchmark framework, configuration and results. We found that Rockset beat Elasticsearch on both throughput and end-to-end latency at the 99th percentile.

Data Ingestion 59

Data Ingestion Kafka Database Architecture 59

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

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. This takes a lot of time and is often a slow process that doesn’t work well for anybody.

SQL 40

SQL Data Pipeline Kafka Database 40

Cloudera

APRIL 2, 2019

Available to customers running 2nd Generation Intel® Xeon® Scalable processors, Intel Optane DC persistent memory can significantly enhance the performance of real-time and streaming applications. In memory mode, done with a simple BIOS change, the operating system simply sees the memory as a large pool of volatile memory similar to DRAM.

NoSQL 47

NoSQL Google Cloud Hadoop Machine Learning 47

Rockset

DECEMBER 9, 2019

The raw data is consistently added to the staging area and then picked up and processed by downstream processes. 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

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. This process involves data collection from multiple sources, such as social networking sites, corporate software, and log files.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Cloudera

MAY 16, 2018

This approach also relates to monitoring internal fiduciary risk by tying separate events together, such as a large position (relative to historic norms) being taken immediately after the risk model that would have flagged it was modified in a separate system. Problem: Fragmented Surveillance. Conclusion.

Data Lake 41

Data Lake Electronics Media Unstructured Data 41

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

Cloudera

NOVEMBER 9, 2018

Since this suggests that the impact of smart cities depends on the use of technology, it is crucial to prevent the misuse of digital tools and systems. These digital tools will allow them to: Effectively aggregate data from various systems and organizations to support multi-functional analytic applications.

Machine Learning 56

Machine Learning Banking Government Media 56

ProjectPro

MAY 23, 2015

The big data ecosystem at Walmart processes multiple Terabytes of new data and petabytes of historical data every day. With Mupd8, stream processing applications could emphasize on the quality of generated data. Walmart has a broad big data ecosystem.

Big Data 52

Big Data Data Analysis Hadoop Retail 52

Cloudera

JUNE 16, 2022

Use cases like fraud detection, network threat analysis, manufacturing intelligence, commerce optimization, real-time offers, instantaneous loan approvals, and more are now possible by moving the data processing components up the stream to address these real-time needs. . Faster ingestion was needed to reduce overall analytics latency. .

Kafka 84

Kafka Manufacturing Data Lake SQL 84

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. Understand the Business Goals The first step of any good big data analytics project is understanding the business or industry that you are working on.

Big Data 52

Big Data Coding Project Hadoop 52

Rockset

APRIL 15, 2022

This is the second 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!

Analytics Application 52

Analytics Application Data Warehouse Raw Data Kafka 52

Cloudera

MARCH 2, 2021

They no longer need to ask a small subset of the organization to provide them with information, rather, they have tooling, systems, and capabilities to get the data they need. Streaming data systems are a relatively new addition to enterprise data systems, and have evolved to providing business-critical roles.

SQL 111

SQL Data Lake Java Scala 111

phData: Data Engineering

JULY 18, 2023

As an AI and data analytics consulting company, phData is on a mission to become the world leader in delivering data services and products on a modern data platform. While rarely a straightforward process, we’ve hit nearly every bump along the way and have learned so much, and we’re excited to share those insights with you!

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. Introduction. CRM platforms).

Government 89

Government Hadoop Data Security Data Warehouse 89