Rockset

JANUARY 30, 2024

In 2023, Rockset announced a new cloud architecture for search and analytics that separates compute-storage and compute-compute. It also unlocks ways to make it easier and cheaper to build applications on Rockset. Rockset’s cloud-native architecture contrasts with the tightly coupled architecture of Elasticsearch.

Data Ingestion 64

Data Ingestion Utilities Architecture SQL 64

Knowledge Hut

MARCH 15, 2024

It holds the second-largest proportion of the cloud market. You can work as a developer, cloud architect, admin, or solutions specialist for Azure. Since every business is gradually moving to the cloud, you may work in any field. It may be used to prepare for Microsoft Azure or cloud services tests.

Cloud Computing 52

Cloud Computing Algorithm Certification SQL 52

Snowflake

MAY 4, 2023

Expanding the DTCC ecosystem with Snowflake Native Apps To explain how DTCC is leveraging Snowflake Native Apps, I first need to paint the broader picture of the DTCC Data Cloud on Snowflake. Snowflake Native Apps allow my team to manage the application layer in much the same way that we manage our Data Cloud layer.

Portfolio 52

Portfolio Cloud Analytics Application Data Security 52

Cloudera

SEPTEMBER 1, 2020

DDE is a new template flavor within CDP Data Hub in Cloudera’s public cloud deployment option (CDP PC). It is designed to simplify deployment, configuration, and serviceability of Solr-based analytics applications. The advantage with cloud is of course the transient allocation of resources. What does DDE entail?

Cloud Storage 68

Cloud Storage Unstructured Data AWS Analytics Application 68

Knowledge Hut

MARCH 29, 2024

In my opinion, the Azure Solution Architect training for cheat sheets enables clients to maximize productivity while taking full advantage of Azure's powerful cloud computing features with their organized sections, which include short instructions. What is the Azure Cheat Sheet?

Cloud Computing 52

Cloud Computing SQL Database Accessible 52

Snowflake

JULY 13, 2023

Brown’s team replaced its Cloudera cluster running the analytics application with Snowflake in January 2022. In the future, Brown is looking forward to unlocking more capabilities enabled by the Snowflake Data Cloud.

Medical 92

Medical Hospitality Scala Transportation 92

Christophe Blefari

JANUARY 7, 2023

Introducing ADBC: Database Access for Apache Arrow — When I see "minimal-overhead alternative to JDBC/ODBC for analytical applications" I'm instantly in. They had obviously been challenged by the cloud vendors and the modern data stack vision that does not include them. Qlik and Talend are two old BI giants.

Data 130

Data Data Science BI Kafka 130

Rockset

MARCH 3, 2022

This data has material financial value when it’s both fresh and easy to access, however, customers commonly face scalability challenges running both transactional and analytical applications on the same database. Transactional databases must be write-optimized and analytical applications require low-latency reads.

Amazon Web Services 52

Amazon Web Services Data Warehouse SQL AWS 52

Knowledge Hut

JUNE 26, 2023

Hundreds of datasets are available from these two cloud services, so you may practise your analytical skills without having to scrape data from an API. Source: Use Stack Overflow Data for Analytic Purposes 4. Source Code: Anomaly Detection in Cloud Servers 2.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

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. Striim is a cloud-native Data Mesh platform that offers features such as automated data mapping, real-time data integration, streaming analytics, and more.

Architecture 52

Architecture Generalist Government Datasets 52

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. I spoke to Mark Ramsey of Ramsey International (RI) to dive deeper into that last subject.

Data Lake 83

Data Lake Data Pipeline Data Governance Analytics Application 83

Rockset

MAY 17, 2022

The truth is that modern cloud native SQL databases support all of the key features necessary for real-time analytics , including: Mutable data for incredibly fast data ingestion and smooth handling of late-arriving events. There are some myths about SQL databases , but they are based on legacy relational systems from the 1990s.

SQL 52

SQL NoSQL Hadoop MongoDB 52

Knowledge Hut

MAY 31, 2023

Custom analytics applications for IoT data, including machine learning and predictive analytics. DeviceHive supports public, private, or hybrid cloud deployment models and has a container-based architecture managed by Kubernetes. Zetta can be deployed on cloud-based or local hardware, such as Raspberry Pi or Intel Edison.

Programming Language 52

Programming Language Electronics Java Programming 52

Rockset

JULY 6, 2022

And when it comes to the cloud and developers, that means wasted money. Take the Hive analytics database that is part of the Hadoop stack. Rockset is a real-time analytics platform built on top of the RocksDB key-value store. Fixing and rerunning the queries is a time-wasting hassle.

NoSQL 52

NoSQL SQL Systems PostgreSQL 52

Rockset

MARCH 24, 2022

How important is query flexibility to you for iterating and prototyping when building real-time analytical applications , such as real-time reporting and real-time personalization? What databases are you using for real-time analytics? Rockset is the real-time analytics database in the cloud for modern data teams.

Non-relational Database 52

Non-relational Database Relational Database Database Data Pipeline 52

Rockset

MARCH 10, 2022

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. Get faster analytics on fresher data, at lower costs, by exploiting indexing over brute-force scanning.

Data Analytics 52

Data Analytics Data Warehouse Medical MySQL 52

Rockset

AUGUST 4, 2021

Organizations that depend on data for their success and survival need robust, scalable data architecture, typically employing a data warehouse for analytics needs. Snowflake is often their cloud-native data warehouse of choice. The first, bulk loading, loads data from files in cloud storage or a local machine.

Data Ingestion 40

Data Ingestion Cloud Storage Data Warehouse Data Lake 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. You can learn about cloud technologies from AWS data engineer books. Key Benefits and Takeaways: Learn everything there is to know about Apache Spark and its ecosystem.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

ProjectPro

AUGUST 9, 2016

Cognizant’s BIGFrame solution uses Hadoop to simplify migration of data and analytics applications to provide mainframe like performance at an economical cost of ownership over data warehouses.

Hadoop 52

Hadoop Insurance Cloud Computing Big Data 52

Rockset

FEBRUARY 2, 2022

Let’s explore five ways to run MongoDB analytics, along with the pros and cons of each method. 1 – Query MongoDB Directly The first and most direct approach is to run your analytical queries directly against MongoDB. Rockset is the real-time analytics database in the cloud for modern data teams.

MongoDB 52

MongoDB NoSQL Data Warehouse BI 52

Knowledge Hut

JULY 26, 2023

Database Application Providers- (Amazon, Facebook): Amazon and Facebook are two well-known organizations that offer comprehensive database application solutions. Amazon Web Services (AWS) provides a variety of cloud-based database services to meet a variety of needs. Spatial Database (e.g.-

Database 52

Database NoSQL Telecommunication MongoDB 52

ProjectPro

SEPTEMBER 9, 2016

Based on the maturity with big data, HCL helps its clients identify use cases to experiment with big data, create data lakes and deploy hadoop data management platforms to develop analytic applications.

Hadoop 40

Hadoop Data Lake Big Data Cloud Computing 40

Data Engineering Podcast

MARCH 3, 2024

It is an open-source, cloud-native orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability. What are the key considerations for powering AI applications that are substantially different from analytical applications?

Programming 162

Programming Data Lake High Quality Data Data Pipeline 162

Towards Data Science

APRIL 3, 2023

From Enormous Data back to Big Data Say you are tasked with building an analytics application that must process around 1 billion events (1,000,000,000) a day. While this might feel far-fetched at first, due to the sheer size of the data, it often helps to step back and think about the intention of the application (what does it do?)

Process 87

Process Data Lake Systems Bytes 87

ProjectPro

FEBRUARY 16, 2023

If your database is cloud-based, using SQL to clean data is far more effective than scripting languages. For instance, data engineers can easily transfer the data onto a cloud storage system and load the raw data into their data warehouse using the COPY INTO command. They must load the raw data into a data warehouse for this analysis.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

Knowledge Hut

DECEMBER 26, 2023

The Microsoft BI platform features are real-time reporting, predictive analytics, and AI diagnostics. Oracle Analytics Cloud Oracle Analytics Cloud is one of the most powerful AI-driven systems available, which brings us back to genuine analytics. Essential features include Embed, Mashup, and analyze.

Business Intelligence 52

Business Intelligence BI Data Mining Data Analysis 52

Cloudera

MARCH 6, 2018

People are gravitating to the analytics services of the large public cloud providers because the “house-brand” offerings seem to be the easiest choice. This leads to extra cost, effort, and risk to stitch together a sub-optimal platform for multi-disciplinary, cloud-based analytics applications.

Cloud 40

Cloud Metadata Big Data AWS 40

Cloudera

NOVEMBER 7, 2023

Navigating this intricate maze of data can be challenging, and that’s why Apache Ozone has become a popular, cloud-native storage solution that spans any data use case with the performance needed for today’s data architectures. Most traditional analytics applications like Hive, Spark, Impala, YARN etc.

Systems 103

Systems Hadoop Unstructured Data Media 103

ProjectPro

MAY 20, 2015

The company targets to deliver values to its customers through the free SaaS based analytics applications so that it can build credibility with the clients to encourage them to buy more.

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 40

Cloudera

FEBRUARY 8, 2024

Starting from the CDW Public Cloud DWX-1.6.1 release and the matching CDW Private Cloud Data Services release, Hive also supports creating, using, and rebuilding materialized views for Iceberg table format. Cloudera Data Warehouse (CDW) running Hive has previously supported creating materialized views against Hive ACID source tables.

Metadata 89

Metadata Data Warehouse BI AWS 89

Cloudera

NOVEMBER 13, 2017

As the market moves toward cloud-based big data and analytics, three qualities emerge as vital for success. Cloud IaaS facilitates resource self-service provisioning, eliminating the hassles of procurement and deployment on-premises. Make sure any cloud-based analytics service meets these criteria.

Cloud 40

Cloud Big Data Metadata Machine Learning 40

Data Science Blog: Data Engineering

NOVEMBER 15, 2023

The database for Process Mining is also establishing itself as an important hub for Data Science and AI applications, as process traces are very granular and informative about what is really going on in the business processes. DATANOMIQ Data Mesh Cloud Architecture – This image is animated! Click to enlarge!

Architecture 52

Architecture Database-centric Process BI 52

Towards Data Science

APRIL 26, 2023

An open-source implementation of a Data Lake with DuckDB and AWS Lambdas A duck in the cloud. Photo by László Glatz on Unsplash In this post we will show how to build a simple end-to-end application in the cloud on a serverless infrastructure. The cloud is better. The infrastructure often gets in the way though.

Engineering 70

Engineering Data Lake AWS BI 70

Striim

AUGUST 31, 2023

This makes scaling the architecture complex and costly, as businesses will need to invest in additional hardware or cloud computing services in order to handle larger volumes of data processing. Cloud-based architectures are more cost-effective but lack the control of an on-premise setup.

Data Integration 69

Data Integration Architecture Amazon Web Services ETL System 69

Rockset

OCTOBER 26, 2023

Scalable architecture: JetBlue requires a scalable cloud architecture that separates compute from storage as there are a number of applications that need to access the same features and datasets. Rockset took that time down to days due to the ease of converting a SQL query into a REST API.”

Machine Learning 64

Machine Learning Data Science Architecture Data Warehouse 64

Cloudera

AUGUST 13, 2021

A global oil and gas company collects, transforms, and distributes over hundreds terabytes of desktop, server, and application log data to their SIEM per day. As the company evolves into a hybrid and multi-cloud strategy, they need to start collecting applications, servers, and network logs from the cloud.

Data Pipeline 109

Data Pipeline Data Lake ETL Tools Unstructured Data 109

Precisely

MARCH 10, 2023

This capability opens the door to a wide array of data analytics applications. The Rise of Cloud Analytics Data analytics has advanced rapidly over the past decade. That effort led to a dramatic shift toward the cloud. Cloud analytics has grown very rapidly, for many of the reasons cited above.

Datasets 59

Datasets Data Warehouse Big Data Cloud Storage 59