U-Next

SEPTEMBER 7, 2022

The terms “ Data Warehouse ” and “ Data Lake ” may have confused you, and you have some questions. Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. What is Data Lake? . Athena on AWS. .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

Striim

MARCH 21, 2025

Business transactions captured in relational databases are critical to understanding the state of business operations. Since the value of data quickly drops over time, organizations need a way to analyze data as it is generated.

IT 52

IT Data Lake Data Warehouse Relational Database 52

phData: Data Engineering

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. What is a Data Lake? Consistency of data throughout the data lake.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. What is a data lake?

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

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

François Nguyen

MARCH 22, 2021

With this 3rd platform generation, you have more real time data analytics and a cost reduction because it is easier to manage this infrastructure in the cloud thanks to managed services. The data domain Discovery portal with all the metadata on the data life cycle 4.Federated The number of subjects to automatize is not short.

Technology 130

Technology Architecture Google Cloud Metadata 130

Towards Data Science

JANUARY 16, 2024

But in order to justify why this concept came into existence, I thought it’d be great to look back in time and understand the evolution of the data landscape. Evolution of the data landscape 1980s — Inception Relational databases came into existence. Organizations began to use relational databases for ‘everything’.

Data Warehouse 95

Data Warehouse Data Architecture Relational Database NoSQL 95

U-Next

MARCH 1, 2023

Introduction Data Engineer is responsible for managing the flow of data to be used to make better business decisions. A solid understanding of relational databases and SQL language is a must-have skill, as an ability to manipulate large amounts of data effectively.

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

Data Engineering Podcast

FEBRUARY 27, 2022

If you’re a data engineering podcast listener, you get credits worth $3000 on an annual subscription TimescaleDB, from your friends at Timescale, is the leading open-source relational database with support for time-series data. Time-series data is time stamped so you can measure how a system is changing.

Designing 100

Designing Metadata Data Lake Relational Database 100

Data Engineering Podcast

MARCH 13, 2022

If you’re a data engineering podcast listener, you get credits worth $3000 on an annual subscription RudderStack helps you build a customer data platform on your warehouse or data lake. TimescaleDB, from your friends at Timescale, is the leading open-source relational database with support for time-series data.

Data Lake 100

Data Lake Relational Database Data Engineering Data Engineer 100

Striim

SEPTEMBER 11, 2024

This method is advantageous when dealing with structured data that requires pre-processing before storage. Conversely, in an ELT-based architecture, data is initially loaded into storage systems such as data lakes in its raw form. Would the data be stored on cloud or on-premises?’

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

ProjectPro

FEBRUARY 8, 2023

It offers a simple and efficient solution for data processing in organizations. It offers users a data integration tool that organizes data from many sources, formats it, and stores it in a single repository, such as data lakes, data warehouses, etc., where it can be used to facilitate business decisions.

AWS 98

AWS Scala Metadata Data Lake 98

Towards Data Science

JULY 9, 2024

While Parquet based data lake storage, offered by different cloud providers, gave us the immense flexibilities during the initial days of data lake implementations, the evolution of business and technology requirements in current days are posing challenges around those implementations.

Data Lake 73

Data Lake Datasets Data Storage Database 73

Knowledge Hut

NOVEMBER 2, 2023

Setting Up a Relational Database with Amazon RDS Difficulty Level: Intermediate AWS cloud practitioner applications can create relational databases using the Amazon Relational Database Service (RDS).

AWS 52

AWS Coding Cloud Project 52

DareData

JANUARY 30, 2023

Examples of relational databases include MySQL or Microsoft SQL Server. NoSQL databases: NoSQL databases are often used for applications that require high scalability and performance, such as real-time web applications. Examples of NoSQL databases include MongoDB or Cassandra.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 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

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? Data warehouse vs data lake vs data lakehouse: What’s the difference.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

AltexSoft

AUGUST 4, 2021

Since data marts provide analytical capabilities for a restricted area of a data warehouse, they offer isolated security and isolated performance. Data mart vs data warehouse vs data lake vs OLAP cube. Data lakes, data warehouses, and data marts are all data repositories of different sizes.

Data Lake 64

Data Lake Data Warehouse ETL Tools Database 64

Monte Carlo

JANUARY 5, 2024

Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. A visualization of the flow of data in data lakehouse architecture vs. data warehouse and data lake.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. A visualization of the flow of data in data lakehouse architecture vs. data warehouse and data lake.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Rockset

OCTOBER 11, 2022

Logstash is an event processing pipeline that ingests and transforms data before sending it to Elasticsearch. Logstash offers a JDBC input plugin that polls a relational database, like PostgreSQL or MySQL, for inserts and updates periodically.

Data Ingestion 52

Data Ingestion Kafka Relational Database PostgreSQL 52

Precisely

JANUARY 25, 2024

There are three potential approaches to mainframe modernization: Data Replication creates a duplicate copy of mainframe data in a cloud data warehouse or data lake, enabling high-performance analytics virtually in real time, without negatively impacting mainframe performance.

Metadata 69

Metadata Relational Database Data Governance Government 69

Snowflake

MARCH 29, 2023

Iceberg supports many catalog implementations: Hive, AWS Glue, Hadoop, Nessie, Dell ECS, any relational database via JDBC, REST, and now Snowflake. But even without the catalog, Iceberg Tables are still accessible if the user directly points at appropriate file locations. How does the Snowflake Catalog SDK work?

Metadata 105

Metadata Scala Hadoop Relational Database 105

Grouparoo

OCTOBER 6, 2021

36 Give Data Products a Frontend with Latent Documentation Document more to help everyone 37 How Data Pipelines Evolve Build ELT at mid-range and move to data lakes when you need scale 38 How to Build Your Data Platform like a Product PM your data with business. 89 What Is Big Data?

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

AltexSoft

NOVEMBER 23, 2021

If the transformation step comes after loading (for example, when data is consolidated in a data lake or a data lakehouse ), the process is known as ELT. You can learn more about how such data pipelines are built in our video about data engineering. Popular data virtualization tools.

Process 69

Process Data Lake Metadata Data Warehouse 69

ProjectPro

APRIL 2, 2018

It will also discuss about how enterprises have setup data lakes to bring in information from diverse sources but are facing totally new set of challenges as users are not completely able to make use of the data because of slow query response times and data complexity.

Hadoop 40

Hadoop Data Lake Relational Database Big Data 40

Knowledge Hut

SEPTEMBER 26, 2023

Supports Structured and Unstructured Data: One of Azure Synapse's standout features is its versatility in handling a wide array of data types. Whether your data is structured, like traditional relational databases, or unstructured, such as textual data, images, or log files, Azure Synapse can manage it effectively.

Data Lake 52

Data Lake Database-centric Machine Learning Pipeline-centric 52

Monte Carlo

MAY 28, 2024

Data Transformation : Clean, format, and convert extracted data to ensure consistency and usability for both batch and real-time processing. Data Loading : Load transformed data into the target system, such as a data warehouse or data lake.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

Knowledge Hut

NOVEMBER 17, 2023

To provide end users with a variety of ready-made models, Azure Data engineers collaborate with Azure AI services built on top of Azure Cognitive Services APIs. Understanding SQL You must be able to write and optimize SQL queries because you will be dealing with enormous datasets as an Azure Data Engineer.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Edureka

FEBRUARY 9, 2023

Some of the top skills to include are: Experience with Azure data storage solutions: Azure Data Engineers should have hands-on experience with various Azure data storage solutions such as Azure Cosmos DB, Azure Data Lake Storage, and Azure Blob Storage.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

AltexSoft

AUGUST 22, 2022

What is data fabric? 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., Data fabric vs data mesh.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

Knowledge Hut

MARCH 19, 2024

It also keeps backups, media files, log data, and static website content. S3 is suitable across several scenarios that utilize S3’s durability, availability, and security features, such as data archiving, content distribution, and data lake implementations, among many others.

AWS 52

AWS Cloud Computing Amazon Web Services Relational Database 52

Knowledge Hut

NOVEMBER 19, 2023

Data scientists, data engineers, and business analysts may collaborate more easily thanks to the Databricks platform. Azure Blob Storage, Data Lake Store, SQL Data Warehouse, and HDInsights are just a few of the computing and storage services that Azure offers.

Data Engineering 52

Data Engineering Data Engineer Engineering PostgreSQL 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

ProjectPro

MAY 2, 2017

Despite the hype around NoSQL, SQL is still the go-to query language for relational databases and other emerging novel database technologies. Source : [link] ) Hadoop: the rise of the modern data lake platform.Information-age.com, April 5, 2017. Source : [link] ) Data Works, Hadoop 3.0

Hadoop 52

Hadoop Entertainment Data Lake Big Data 52

Silectis

JANUARY 3, 2021

Data Ingestion The process by which data is moved from one or more sources into a storage destination where it can be put into a data pipeline and transformed for later analysis or modeling. Data Integration Combining data from various, disparate sources into one unified view.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

AltexSoft

MAY 14, 2021

And most of this data has to be handled in real-time or near real-time. Variety is the vector showing the diversity of Big Data. This data isn’t just about structured data that resides within relational databases as rows and columns. Data storage and processing.

Big Data 78

Big Data Data Analytics IT NoSQL 78