Rockset

AUGUST 2, 2023

The Windward Maritime AI platform Lastly, Windward wanted to move their entire platform from batch-based data infrastructure to streaming. This transition can support new use cases that require a faster way to analyze events that was not needed until now. They used MongoDB as their metadata store to capture vessel and company data.

Database-centric 52

Database-centric PostgreSQL Transportation Insurance 52

Snowflake

NOVEMBER 2, 2023

Over the years, the technology landscape for data management has given rise to various architecture patterns, each thoughtfully designed to cater to specific use cases and requirements. These patterns include both centralized storage patterns like data warehouse , data lake and data lakehouse , and distributed patterns such as data mesh.

Data Lake 89

Data Lake Data Warehouse Cloud Unstructured Data 89

ProjectPro

AUGUST 11, 2021

“Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Data Warehouse Architecture What is a Data lake?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Data Engineering Weekly

MARCH 24, 2023

Data engineering starts to add value to the business by capturing events at each step of the business process. The events are then further enriched and analyzed to bring visibility to business operations. Architectural patterns for Data Creation There are three types of architecture patterns in data creation.

Engineering 67

Engineering Data Transportation Database 67

AltexSoft

JUNE 26, 2023

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data. Note, though, that not any type of web scraping is legal.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Monte Carlo

JUNE 14, 2023

The modern data stack era , roughly 2017 to present data, saw the widespread adoption of cloud computing and modern data repositories that decoupled storage from compute such as data warehouses, data lakes, and data lakehouses. They also recently acquired Apache Flink , another streaming solution.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

ProjectPro

JANUARY 31, 2022

As the demand for big data grows, an increasing number of businesses are turning to cloud data warehouses. The cloud is the only platform to handle today's colossal data volumes because of its flexibility and scalability. Launched in 2014, Snowflake is one of the most popular cloud data solutions on the market.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

AltexSoft

AUGUST 22, 2022

A data fabric is an architecture design presented as an integration and orchestration layer built on top of multiple disjointed data sources like relational databases , data warehouses , data lakes, data marts , IoT , legacy systems, etc., to provide a unified view of all enterprise data.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

AltexSoft

SEPTEMBER 23, 2021

One of the innovative ways to address this problem is to build a data hub — a platform that unites all your information sources under a single umbrella. This article explains the main concepts of a data hub, its architecture, and how it differs from data warehouses and data lakes. What is Data Hub?

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Netflix Tech

DECEMBER 14, 2018

A fundamental requirement for any lasting data system is that it should scale along with the growth of the business applications it wishes to serve. NMDB is built to be a highly scalable, multi-tenant, media metadata system that can serve a high volume of write/read throughput as well as support near real-time queries.

Media 94

Media Database Metadata Data Schemas 94

ProjectPro

AUGUST 24, 2021

Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data. A data engineer interacts with this warehouse almost on an everyday basis. Data Analytics: A data engineer works with different teams who will leverage that data for business solutions.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Snowflake

MARCH 30, 2023

A 2016 data science report from data enrichment platform CrowdFlower found that data scientists spend around 80% of their time in data preparation (collecting, cleaning, and organizing of data) before they can even begin to build machine learning (ML) models to deliver business value. Enter Snowpark !

Engineering 82

Engineering Raw Data Data Science Scala 82

ProjectPro

OCTOBER 28, 2015

Hadoop Sqoop and Hadoop Flume are the two tools in Hadoop which is used to gather data from different sources and load them into HDFS. Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., Sqoop hadoop can also be used for exporting data from HDFS into RDBMS.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

AltexSoft

JULY 19, 2022

In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. There have been relational databases, data warehouses, data lakes, and even a combination of the latter two.

Architecture 52

Architecture Data Lake Medical Datasets 52

AltexSoft

OCTOBER 8, 2021

Data integration defines the process of collecting data from a number of disparate source systems and presenting it in a unified form within a centralized location like a data warehouse. So, why is data integration such a big deal? Connections to both data warehouses and data lakes are possible in any case.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

ProjectPro

NOVEMBER 15, 2021

It serves as a distributed processing engine for both categories of data streams: unbounded and bounded. Support for stream and batch processing, comprehensive state management, event-time processing semantics, and consistency guarantee for the state are just a few of Flink's capabilities.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

OCTOBER 20, 2021

This is used in social media to better gauge sentiments towards an event or a product. Experimentation in production Big Data Data Warehouse for core ETL tasks Direct data pipelines Tiered Data Lake 4. User Behaviour User Behaviour began as Security Information and Event Management (SIEM).

Machine Learning 52

Machine Learning Algorithm Government Data Science 52

ProjectPro

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

Hadoop Big Data Metadata Java 40

ProjectPro

JUNE 23, 2016

Thus, this solution is not practically recommended and this is when Apache Sqoop comes to the rescues of users that allows users to import data on HDFS. Apache Sqoop is a lifesaver for people facing challenges with moving data out of a data warehouse into the Hadoop environment. Data import in sqoop is not event driven.

Hadoop 40

Hadoop MySQL Relational Database Java 40

AltexSoft

MAY 12, 2023

What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Monte Carlo

NOVEMBER 20, 2023

The data is unique and free from duplicates. And the transformed data is free from anomalies. Data quality can be impacted by all sorts of events and errors within a pipeline or ingestion source—from distribution anomalies caused by a keying error to the natural entropy that exists within a complex data system.

Government 69

Government Data Data Governance Datasets 69

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Cloudera

APRIL 1, 2024

We scored the highest in hybrid, intercloud, and multi-cloud capabilities because we are the only vendor in the market with a true hybrid data platform that can run on any cloud including private cloud to deliver a seamless, unified experience for all data, wherever it lies.

Cloud 101

Cloud Unstructured Data Metadata Datasets 101

Monte Carlo

JUNE 28, 2023

The music seems like a missed opportunity to remind us of the 90s theme for the celebration event taking place later tonight with Salt-N-Peppa at the Chase Center, but I’m not an event planner for a reason. Databricks Workflows reached 100m weekly jobs and are processing 2 excabytes of data per day.

Data Warehouse 52

Data Warehouse Scala Unstructured Data Government 52