AltexSoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Traditional data warehouse platform architecture. Data lake. Data lake architecture example.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

ProjectPro

JANUARY 31, 2022

This blog walks you through what does Snowflake do , the various features it offers, the Snowflake architecture, and so much more. Table of Contents Snowflake Overview and Architecture What is Snowflake Data Warehouse? Its analytical skills enable companies to gain significant insights from their data and make better decisions.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Monte Carlo

MAY 14, 2024

As organizations seek greater value from their data, data architectures are evolving to meet the demand — and table formats are no exception. At its core, a table format is a sophisticated metadata layer that defines, organizes, and interprets multiple underlying data files.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Monte Carlo

JUNE 14, 2023

In this post, we will help you quickly level up your overall knowledge of data pipeline architecture by reviewing: Table of Contents What is data pipeline architecture? Why is data pipeline architecture important? What is data pipeline architecture? Why is data pipeline architecture important?

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Snowflake

NOVEMBER 29, 2023

For example, the data storage systems and processing pipelines that capture information from genomic sequencing instruments are very different from those that capture the clinical characteristics of a patient from a site. A conceptual architecture illustrating this is shown in Figure 3.

Metadata 84

Metadata Healthcare Medical Data Storage 84

AltexSoft

SEPTEMBER 23, 2021

The larger the company, the more data it has to generate actionable insights. Because it is scattered across disparate systems, hardly available for analytical apps. Evidently, common storage solutions fail to provide a unified data view and meet the needs of companies for seamless data flow. What is Data Hub?

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Engineering at Meta

MARCH 6, 2024

Our technical solution builds on Meta’s existing client / server architecture We think the best way to deliver interoperability is through a solution which builds on Meta’s existing client / server architecture [Figure 1]. The proof is constructed by the third-party service cryptographically signing an authentication token.

Media 133

Media Architecture Metadata Data Storage 133

Christophe Blefari

JANUARY 20, 2024

What is data engineering As I said it before data engineering is still a young discipline with many different definitions. Still, we can have a common ground when mixing software engineering, DevOps principles, Cloud — or on-prem — systems understanding and data literacy. Is it really modern?

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

LinkedIn Engineering

JULY 19, 2023

Open source data lakehouse deployments are built on the foundations of compute engines (like Apache Spark, Trino, Apache Flink), distributed storage (HDFS, cloud blob stores), and metadata catalogs / table formats (like Apache Iceberg, Delta, Hudi, Apache Hive Metastore). Tables are governed as per agreed upon company standards.

Big Data 78

Big Data Data Management Management Metadata 78

Data Engineering Podcast

SEPTEMBER 12, 2021

Summary The Cassandra database is one of the first open source options for globally scalable storage systems. Since its introduction in 2008 it has been powering systems at every scale. That leaves DataOps reactive to data quality issues and can make your consumers lose confidence in your data.

Database 100

Database Metadata Kafka Data Storage 100

Christophe Blefari

JUNE 16, 2023

Yann's vision goes toward AI systems learning and reasoning like animals and humans. Change Data Capture (CDC) with PostgreSQL and ClickHouse — This is a nice vendor post about CDC with Kafka as movement layer (using Debezium). The post explains well the architecture you need to make it work. This is neat.

Programming Language 130

Programming Language SQL PostgreSQL Data 130

Knowledge Hut

MAY 9, 2024

In this blog post, we will look at some of the world's highest paying data science jobs, what they entail, and what skills and experience you need to land them. What is Data Science? Data science also blends expertise from various application domains, such as natural sciences, information technology, and medicine.

Data Science 52

Data Science Data Mining Data Architect Programming Language 52

Data Engineering Podcast

DECEMBER 16, 2019

The solution to discoverability and tracking of data lineage is to incorporate a metadata repository into your data platform. The metadata repository serves as a data catalog and a means of reporting on the health and status of your datasets when it is properly integrated into the rest of your tools.

Metadata 100

Metadata PostgreSQL Datasets Data Warehouse 100

Towards Data Science

DECEMBER 1, 2023

Technical Overview The project architecture is depicted as follows: Google Calendar -> Fivetran -> Snowflake -> dbt -> Snowflake Dashboard , with GitHub Actions orchestrating the deployment. Storage —  Snowflake Snowflake, a cloud-based data warehouse tailored for analytical needs, will serve as our data storage solution.

Data Engineering 70

Data Engineering Data Engineer Project Engineering 70

Databand.ai

JUNE 28, 2023

“Observability” has become a bit of a buzzword so it’s probably best to define it: Data observability is the blanket term for monitoring and improving the health of data within applications and systems like data pipelines. Data observability vs. monitoring: what is the difference?

Data Pipeline 98

Data Pipeline Data Engineering Data Engineer Engineering 98

Cloudera

MARCH 22, 2023

Over the past handful of years, systems architecture has evolved from monolithic approaches to applications and platforms that leverage containers, schedulers, lambda functions, and more across heterogeneous infrastructures. And, crucial for a hybrid data platform, it does so across hybrid cloud.

Data Governance 87

Data Governance Government Business Analyst Metadata 87

Knowledge Hut

DECEMBER 19, 2023

This type of developer works with the Full stack of a software application, beginning with Front end development and going through back-end development, Database, Server, API, and version controlling systems. Git is an open source version control system that a developer/ development companies use to manage projects.

Java 98

Java Programming Language Architecture Database 98

ProjectPro

FEBRUARY 8, 2023

Let us dive deeper into this data integration solution by AWS and understand how and why big data professionals leverage it in their data engineering projects. When Glue receives a trigger, it collects the data, transforms it using code that Glue generates automatically, and then loads it into Amazon S3 or Amazon Redshift.

AWS 98

AWS Scala Metadata Data Lake 98

ProjectPro

SEPTEMBER 16, 2021

NoSQL databases are the new-age solutions to distributed unstructured data storage and processing. The speed, scalability, and fail-over safety offered by NoSQL databases are needed in the current times in the wake of Big Data Analytics and Data Science technologies. Hence, writes in Hbase are operation intensive.

NoSQL 52

NoSQL Database Hadoop Big Data 52

AltexSoft

JULY 29, 2022

a runtime environment (sandbox) for classic business intelligence (BI), advanced analysis of large volumes of data, predictive maintenance , and data discovery and exploration; a store for raw data; a tool for large-scale data integration ; and. a suitable technology to implement data lake architecture.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Rockset

JUNE 6, 2023

One of the ways Rockset maximizes price-performance for our customers is by separately scaling compute and storage. This improves efficiency and elasticity, but is challenging to implement for a real-time system. This simplifies the system’s architecture and enables high bandwidth, low latency access to the data at query time.

Metadata 52

Metadata Datasets Architecture Algorithm 52

Towards Data Science

FEBRUARY 15, 2023

Concepts, theory, and functionalities of this modern data storage framework Photo by Nick Fewings on Unsplash Introduction I think it’s now perfectly clear to everybody the value data can have. To use a hyped example, models like ChatGPT could only be built on a huge mountain of data, produced and collected over years.

Data Lake 77

Data Lake Data Warehouse Hadoop Data Architecture 77

AltexSoft

JUNE 7, 2021

The system automatically replicates information to prevent data loss in the case of a node failure. Hadoop architecture, or how the framework works. Master Nodes control and coordinate two key functions of Hadoop: data storage and parallel processing of data. A file stored in the system ?an’t

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Knowledge Hut

DECEMBER 21, 2023

Few benefits of Cloud computing are listed below: Scalability: With Cloud computing we get scalable applications which suits for large scale production systems for Businesses which store and process large sets of data. This research could help businesses to reduce the amount of spam that they receive in their cloud-based email systems.

Cloud Computing 52

Cloud Computing Cloud Algorithm Healthcare 52

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. RDBMS is a part of system software used to create and manage databases based on the relational model.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Knowledge Hut

NOVEMBER 28, 2023

As a data engineer description, you must be ready to explore large-scale data processing and use your expertise and soft skills to ensure a scalable and reliable working environment. Data engineers need to work with large amounts of data and maintain the architectures used in various data science projects.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

ProjectPro

NOVEMBER 7, 2016

Understanding the Hadoop architecture now gets easier! This blog will give you an indepth insight into the architecture of hadoop and its major components- HDFS, YARN, and MapReduce. We will also look at how each component in the Hadoop ecosystem plays a significant role in making Hadoop efficient for big data processing.

Hadoop 40

Hadoop Architecture IT Big Data 40

AltexSoft

SEPTEMBER 21, 2023

From those home-made beginnings as Compass, Elasticsearch has matured into one of the leading enterprise search engines, standing among the top 10 most popular database management systems globally according to the Stack Overflow 2023 Developer Survey. Key components of the Elasticsearch architecture.

Engineering 52

Engineering NoSQL Programming Language Java 52

Big Data Tools

SEPTEMBER 6, 2021

There are also several changes in KRaft (namely Revise KRaft Metadata Records and Producer ID generation in KRaft mode ), along with many other changes. Unfortunately, the feature that was most awaited (at least by me) – tiered storage – has been postponed for a subsequent release. Support for Scala 2.12 And more files means more time.

Data Engineering 52

Data Engineering Data Engineer Engineering Big Data Tools 52

LinkedIn Engineering

JULY 27, 2023

Costwiz application and workflow management system For the initial rollout, we built a single-page app for users to perform actions on their recommendations (as seen in Figure 1). Data providers: The core input data for which the workflows should be executed and other supporting data required are fed to the system by data providers.

Metadata 75

Metadata Utilities Cloud Data Lake 75

AltexSoft

JULY 18, 2023

These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Data analysis. Companies employ Spark for customer churn prediction , fraud detection , and recommender systems. Stream processing.

Big Data 52

Big Data Data Process Process Hadoop 52

Cloudera

OCTOBER 15, 2021

Ozone is also fully compatible with S3 API*, establishing it as a future proof solution and enabling CDP Hybrid Cloud to meet the growing demand for a hybrid data cloud. . Apache Ozone has added a new feature called File System Optimization (“FSO”) in HDDS-2939. Apache Ozone – Object Store Architecture. ZooKeeper 3.5.5

Cloud 87

Cloud Hadoop Data Analytics Metadata 87

phData: Data Engineering

AUGUST 4, 2023

Data storage is a vital aspect of any Snowflake Data Cloud database. Within Snowflake, data can either be stored locally or accessed from other cloud storage systems. In Snowflake, there are three different storage layers available, Database, Stage, and Cloud Storage.

Cloud Storage 52

Cloud Storage Google Cloud Amazon Web Services Data Storage 52

Cloudera

AUGUST 31, 2021

While this “data tsunami” may pose a new set of challenges, it also opens up opportunities for a wide variety of high value business intelligence (BI) and other analytics use cases that most companies are eager to deploy. . Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis.

Data Warehouse 82

Data Warehouse Database-centric Metadata Cloud 82

Snowflake

APRIL 5, 2023

Traditionally, the dimensional data modeling approach is used to build complex data warehouses, while Data Vaults are used in data warehouses to offer long-term historical data storage while modeling. Why is data modeling important for a data warehouse?

Data Warehouse 52

Data Warehouse Healthcare Unstructured Data Metadata 52

Pinterest Engineering

NOVEMBER 22, 2023

In the first blog, we will share a short summary on the GokuS and GokuL architecture, data format for Goku Long Term, and how we improved the bootstrap time for our storage and serving components. GokuS (storage architecture found in this link ), which serves the last 1 day of metrics, stores the data in memory.

Database 95

Database Bytes Kafka Architecture 95

AltexSoft

MAY 12, 2023

Generated by various systems or applications, log files usually contain unstructured text data that can provide insights into system performance, security, and user behavior. Sensor data. A fixed schema means the structure and organization of the data are predetermined and consistent.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59