Rockset

FEBRUARY 18, 2021

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. Rockset was 9.4x

Analytics Application 52

Analytics Application SQL Database Structured Data 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. Low Maintenance.

Data Warehouse 69

Data Warehouse Cloud Kafka Cloud Storage 69

Data Engineering Podcast

MARCH 3, 2024

Join us at the top event for the global data community, Data Council Austin. Don't miss out on our only event this year! What are the skills and systems that need to be in place to effectively execute on an AI program? "AI" Visit dataengineeringpodcast.com/data-council and use code dataengpod20 to register today!

Programming 162

Programming Data Lake High Quality Data Data Pipeline 162

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. To accomplish this we can use Kafka streams and KSQL.

Kafka 40

Kafka Database Process SQL 40

ProjectPro

MARCH 10, 2016

LinkedIn processes thousands of events every day. The process of funnelling data into Hadoop systems is not as easy as it appears, because data has to be transferred from one location to a large centralized system. All the batch processing and analytics workload at LinkedIn is primarily handled by Hadoop.

Hadoop 40

Hadoop Big Data Data Analytics Big Data Ecosystem 40

Rockset

OCTOBER 4, 2022

Streaming data feeds many real-time analytics applications, from logistics tracking to real-time personalization. Event streams, such as clickstreams, IoT data and other time series data, are common sources of data into these apps. The broad adoption of Apache Kafka has helped make these event streams more accessible.

MySQL 52

MySQL Kafka Aggregated Data Architecture 52

Knowledge Hut

DECEMBER 26, 2023

Business intelligence (BI) is the collective name for a set of processes, systems, and technologies that turn raw data into knowledge that can be used to operate enterprises profitably. The Microsoft BI platform features are real-time reporting, predictive analytics, and AI diagnostics. What is Business Intelligence (BI)?

Business Intelligence 52

Business Intelligence BI Data Mining Data Analysis 52

Cloudera

AUGUST 13, 2021

The business is so unprepared with information overflow that missing an important event or insight has become the business norm. The application license and infrastructure costs are rising faster than the ability to detect cyber events effectively. What product can help collect events only?

Data Pipeline 108

Data Pipeline Data Lake ETL Tools Unstructured Data 108

Precisely

MARCH 10, 2023

By zeroing in on location, you can better understand relationships between people, structures, and events in the physical world. Variations among street names, spellings, abbreviations, numbering systems, and formatting options make it especially challenging to arrive at a common nomenclature.

Datasets 59

Datasets Data Warehouse Big Data Cloud Storage 59

Cloudera

NOVEMBER 2, 2020

Ingest 100s of TB of network event data per day . The capabilities that more and more customers are asking for are: Analytics on live data AND recent data AND historical data. The capabilities that more and more customers are asking for are: Analytics on live data AND recent data AND historical data. 200,000 queries per day.

Data Warehouse 91

Data Warehouse Kafka Lambda Architecture Telecommunication 91

AltexSoft

OCTOBER 21, 2022

After trying all options existing on the market — from messaging systems to ETL tools — in-house data engineers decided to design a totally new solution for metrics monitoring and user activity tracking which would handle billions of messages a day. process data in real time and run streaming analytics. Practically, nothing.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

Rockset

MAY 3, 2023

Many industries including gaming, internet and financial services are mature in their adoption of event streaming platforms and have already graduated from data streams to torrents. The data generator generates documents, each document is the size of 1.25KB and represents a single event.

Data Ingestion 59

Data Ingestion Kafka Database Architecture 59

AltexSoft

JULY 18, 2023

It has in-memory computing capabilities to deliver speed, a generalized execution model to support various applications, and Java, Scala, Python, and R APIs. Spark Streaming enhances the core engine of Apache Spark by providing near-real-time processing capabilities, which are essential for developing streaming analytics applications.

Big Data 52

Big Data Data Process Process Hadoop 52

Cloudera

APRIL 2, 2019

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. When in memory mode, the data is not saved in the event of a power loss. It supports a wide variety of use cases from powering web & mobile applications to operationalizing IoT data.

NoSQL 47

NoSQL Google Cloud Hadoop Machine Learning 47

AltexSoft

SEPTEMBER 23, 2021

Because it is scattered across disparate systems, hardly available for analytical apps. A data hub serves as a single point of access for all data consumers, whether it be an application, a data scientist, or a business user. The larger the company, the more data it has to generate actionable insights.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

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 can be a challenge, though.

SQL 40

SQL Data Pipeline Kafka Database 40

U-Next

SEPTEMBER 9, 2022

In other words, increasingly, organizations are now using Business Analytics to enable proactive decision-making instead of responding to events as they happen. . . Business Analytics is a flourishing technology as it can be used in every sector where data is accessible and collected.

Retail 40

Retail Big Data Data Analytics Utilities 40

U-Next

AUGUST 26, 2022

Companies may use Data Analytics to evaluate their data (historic, genuine, unorganized, subjective), find connections, and provide insight that can guide and, in some circumstances, automate choices, bridging knowledge and actions. Data Analytics Illustration. Predictive Analytics.

Data Analytics 40

Data Analytics Insurance Transportation Healthcare 40

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. Conclusion.

Data Lake 41

Data Lake Electronics Media Unstructured Data 41

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

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.

Metadata 80

Metadata Algorithm Hadoop Cloud 80

Cloudera

JUNE 16, 2022

Reduce ingest latency and complexity: Multiple point solutions were needed to move data from different data sources to downstream systems. The batch nature of these tools increased the overall latency of the analytics. Faster ingestion was needed to reduce overall analytics latency. .

Kafka 84

Kafka Manufacturing Data Lake SQL 84

ProjectPro

MAY 31, 2021

A big data project is a data analysis project that uses machine learning algorithms and different data analytics techniques on a large dataset for several purposes, including predictive modeling and other advanced analytics applications. Access Solution to Data Warehouse Design for an E-com Site 4.

Big Data 52

Big Data Coding Project Hadoop 52

Rockset

DECEMBER 9, 2021

Long gone are the days when employees would use old school ERP systems to reorder supplies. No, these days all of the coffee beans, cups, and pastries are tracked and reordered constantly through a fully automated system harvesting sales from the cash registers as soon as they are rung up. Out-of-order event streams.

Transportation 52

Transportation BI SQL Data Warehouse 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. It’s probably because their analytics database lacks the features necessary to deliver data-driven decisions accurately in real time. Transmitting out-of-order data is not the issue.

Analytics Application 52

Analytics Application Data Warehouse Raw Data Kafka 52