Data Science Blog: Data Engineering

NOVEMBER 15, 2023

New big data architectures and, above all, data sharing concepts such as Data Mesh are ideal for creating a common database for many data products and applications. 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

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 109

Data Pipeline Data Lake ETL Tools Unstructured Data 109

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. thousand (k) events a second (or around 695k events a minute if the event stream is constant), which is an easier number to rationalize.

Process 84

Process Data Lake Systems Bytes 84

Rockset

MARCH 10, 2022

This is the first post in a series by Rockset's CTO Dhruba Borthakur on Designing the Next Generation of Data Systems for Real-Time Analytics. Earlier at Yahoo, he was one of the founding engineers of the Hadoop Distributed File System. Successful data-driven companies like Uber, Facebook and Amazon rely on real-time analytics.

Data Analytics 52

Data Analytics Data Warehouse Medical MySQL 52

Rockset

FEBRUARY 24, 2023

It’s a continuous and unbounded stream of information that is generated at a high frequency and delivered to a system or application. Typically, the “units” of data being streamed are considered events, which resemble a record in a database, with some key differences. Streaming data has been around for decades.

Kafka 52

Kafka AWS Amazon Web Services Programming Language 52

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 86

Kafka Manufacturing Data Lake SQL 86

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

Snowflake

JULY 13, 2023

Emergency response teams can look at historical data to understand how they can improve their performance for future events. And because the system supports emergency responses, it has to be available 24/7, with the ability to support high concurrency and scalability in cases of public emergencies or natural disasters.

Medical 92

Medical Hospitality Scala Transportation 92

Snowflake

MAY 4, 2023

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. As a result, you should not rely on any forward-looking statements as predictions of future events.

Portfolio 52

Portfolio Cloud Analytics Application Data Security 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

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 94

Data Warehouse Kafka Lambda Architecture Telecommunication 94

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

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. For instance, customer personalization systems need to combine historic data sets with real-time data streams to instantly provide the most relevant product recommendations to customers.

SQL 52

SQL NoSQL Hadoop MongoDB 52

Knowledge Hut

JUNE 26, 2023

Pipeline for Real-Time Data Processing in Music Applications Project Overview: The project will stream events that are created by a fictitious music streaming service that operates similarly to Spotify. You will be able to generate a sample dataset for this project by using Eventism and the Million Songs dataset.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

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

Rockset

FEBRUARY 18, 2021

Using RockBench, we ascertained Rockset’s suitability for many real-time analytics applications due to its ability to keep data latency to under 1 second, while ingesting 1 billion events per day, on a standard 4XLarge Virtual Instance. Rockset was 9.4x

Analytics Application 52

Analytics Application SQL Database Structured Data 52

Knowledge Hut

MAY 31, 2023

These might include hardware like development boards and shields, as well as software tools for creating programs that can run on IoT systems. Top IoT Development Tools of 2023 If you're looking to create some pretty impressive IoT systems, you might be interested in checking out this list of development tools we've put together.

Programming Language 52

Programming Language Electronics Java Programming 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

AUGUST 18, 2020

These are systems of intelligence that Jerry Chen, partner at Greylock describes. What is a system of intelligence and why is it so defensible? What makes a system of intelligence valuable is that it typically crosses multiple data sets, multiple systems of record.

Data Lake 40

Data Lake Data Schemas BI Kafka 40

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 57

Datasets Data Warehouse Big Data Cloud Storage 57

AltexSoft

SEPTEMBER 23, 2021

Because it is scattered across disparate systems, hardly available for analytical apps. The main purpose of a DW is to enable analytics: It is designed to source raw historical data, apply transformations, and store it in a structured format. Source system layer: data extraction. Data lake vs data hub.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 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

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. In the implementation, it uses blocking-IO.

Metadata 82

Metadata Algorithm Hadoop Cloud 82

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 70

Data Warehouse Cloud Kafka Cloud Storage 70

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

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

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

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.

Data Lake 42

Data Lake Electronics Media Unstructured Data 42

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. The datasets must be gathered based on these factors to find patterns.

Big Data 52

Big Data Coding Project Hadoop 52

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

ProjectPro

MAY 23, 2015

For example, an application can be written to subscribe to the Twitter firehose of every tweet written; such an application can analyse the tweets to determine Twitter's most influential users, or identify suddenly prominent events as they occur.

Big Data 52

Big Data Data Analysis Hadoop Retail 52