Monte Carlo

AUGUST 25, 2023

That’s why it’s essential for teams to choose the right architecture for the storage layer of their data stack. But, the options for data storage are evolving quickly. So let’s get to the bottom of the big question: what kind of data storage layer will provide the strongest foundation for your data platform?

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

phData: Data Engineering

APRIL 4, 2023

Fivetran today announced support for Amazon Simple Storage Service (Amazon S3) with Apache Iceberg data lake format. Amazon S3 is an object storage service from Amazon Web Services (AWS) that offers industry-leading scalability, data availability, security, and performance.

Data Lake 52

Data Lake Amazon Web Services Data Cleanse Data Warehouse 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? What is a Data lake?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Hevo

SEPTEMBER 11, 2024

Nowadays, the term is used for petabytes or even exabytes of data (1024 Petabytes), close to trillions of records from billions of people. In this fast-moving landscape, the key to making a difference is picking up the correct data storage solution for your business. […]

Data Lake 40

Data Lake Data Warehouse Database Data Storage 40

Hevo

JUNE 20, 2024

It provides Cloud services like Amazon Redshift, Amazon S3, and many others for Data Storage. Extract, Transform, Load are 3 important steps performed in the field of Data Warehousing and Databases. So, extracting and loading data from these data storage is one […]

Amazon Web Services 40

Amazon Web Services Data Lake Data Storage AWS 40

Hevo

JUNE 20, 2024

It provides Cloud services like Amazon Redshift, Amazon S3, and many others for Data Storage. Extract, Transform, Load are 3 important steps performed in the field of Data Warehousing and Databases. So, extracting and loading data from these data storage is one […]

Amazon Web Services 40

Amazon Web Services Data Lake Data Storage AWS 40

phData: Data Engineering

NOVEMBER 8, 2024

The world we live in today presents larger datasets, more complex data, and diverse needs, all of which call for efficient, scalable data systems. Though basic and easy to use, traditional table storage formats struggle to keep up. Track data files within the table along with their column statistics.

Architecture 52

Architecture Systems Data Lake Google Cloud 52

Hevo

JULY 23, 2024

With the vast amount of data being collected today for various purposes, there is an increasing need to find the proper data storage, which also heavily depends on your specific analytical objectives. This […]

Data Lake 40

Data Lake Data Warehouse Data Storage Data 40

Striim

SEPTEMBER 11, 2024

Striim, for instance, facilitates the seamless integration of real-time streaming data from various sources, ensuring that it is continuously captured and delivered to big data storage targets. This method is advantageous when dealing with structured data that requires pre-processing before storage.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Snowflake

APRIL 18, 2024

Legacy SIEM cost factors to keep in mind Data ingestion: Traditional SIEMs often impose limits to data ingestion and data retention. Snowflake allows security teams to store all their data in a single platform and maintain it all in a readily accessible state, with virtually unlimited cloud data storage capacity.

Data Lake 82

Data Lake Data Ingestion Bytes Cloud Computing 82

dbt Developer Hub

OCTOBER 3, 2024

Apache Iceberg is a high-performance open table format developed for modern data lakes. When people talk about Iceberg, it often means multiple components including but not limited to: Iceberg Table Format - an open-source table format with large-scale data. Storage systems should just work.” “We

Metadata 86

Metadata Data Lake Data Storage Accessible 86

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Data lakes offer a scalable and cost-effective solution.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Data lakes offer a scalable and cost-effective solution.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Data lakes offer a scalable and cost-effective solution.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

Christophe Blefari

FEBRUARY 24, 2023

In order to improve your data infra you should sometimes try to occasionally kill your data stack , chaos engineering is something that helps discover issues. This goes further than being a data-driven enterprise , you have to put in place a framework the puts data measurement at every product choice, resulting in maturity increase.

Kafka 130

Kafka Data Lake Data Storage Data 130

Christophe Blefari

JANUARY 20, 2024

formats — This is a huge part of data engineering. Picking the right format for your data storage. You'll be seen as the most technical person of a data team and you'll need to help regarding "low-level" stuff you team. You'll be also asked to put in place a data infrastructure.

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

Knowledge Hut

SEPTEMBER 26, 2023

This is particularly valuable in today's data landscape, where information comes in various shapes and sizes. Effective Data Storage: Azure Synapse offers robust data storage solutions that cater to the needs of modern data-driven organizations.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Management Data Lake Data Governance 52

DareData

JANUARY 30, 2023

In this post, we'll discuss some key data engineering concepts that data scientists should be familiar with, in order to be more effective in their roles. These concepts include concepts like data pipelines, data storage and retrieval, data orchestrators or infrastructure-as-code.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

Knowledge Hut

SEPTEMBER 25, 2023

As an Azure Data Engineer, you will be expected to design, implement, and manage data solutions on the Microsoft Azure cloud platform. You will be in charge of creating and maintaining data pipelines, data storage solutions, data processing, and data integration to enable data-driven decision-making inside a company.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Cloudera

MARCH 5, 2024

With built-in features like time travel, schema evolution, and streamlined data discovery, Iceberg empowers data teams to enhance data lake management while upholding data integrity. Zero Downtime Upgrades Beyond improvements to Iceberg and Ozone, the platform now boasts Zero Downtime Upgrades (ZDU).

Data Lake 86

Data Lake Data Storage Government Kafka 86

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 Architecture 77

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

Monte Carlo

MAY 14, 2024

It bridges the gap between traditional databases and the big data world, providing a platform for complex data transformations and batch processing in environments that require deep data analysis. As these new table formats have emerged, it’s changed the way data lakes are structured and managed.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 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. Data engineers should be proficient in scripting to automate routine data tasks and workflows. Automation : Automation is key for managing large datasets efficiently.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Data Engineering Weekly

MARCH 3, 2024

The migration enhanced data quality, lineage visibility, performance improvements, cost reductions, and better reliability and scalability, setting a robust foundation for future expansions and onboarding.

Data Engineering 67

Data Engineering Data Engineer Engineering Pipeline-centric 67

Cloudera

OCTOBER 6, 2022

For example, we have some customers using their data platform originally established for compliance initiatives to drive new use cases. These data lakes house much of the data needed to also support other use cases. We see this consistently in the data platform/data storage space. .

Data Lake 90

Data Lake Machine Learning Data Storage Cloud Computing 90

Edureka

FEBRUARY 9, 2023

Azure Data Engineering is a rapidly growing field that involves designing, building, and maintaining data processing systems using Microsoft Azure technologies. As a certified Azure Data Engineer, you have the skills and expertise to design, implement and manage complex data storage and processing solutions on the Azure cloud platform.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Edureka

FEBRUARY 7, 2023

They should also be proficient in programming languages such as Python , SQL , and Scala , and be familiar with big data technologies such as HDFS , Spark , and Hive. Learn programming languages: Azure Data Engineers should have a strong understanding of programming languages such as Python , SQL , and Scala.

Data Engineering 52

Data Engineering Data Engineer Engineering Programming Language 52

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 50

Data Lake Datasets Data Storage Database 50

Data Engineering Podcast

FEBRUARY 27, 2022

Visit them today at dataengineeringpodcast.com/timescale RudderStack helps you build a customer data platform on your warehouse or data lake. Data integration (extract and load) What are your data sources? Batch or streaming (acceptable latencies) Data storage (lake or warehouse) How is the data going to be used?

Designing 100

Designing Metadata Data Lake Relational Database 100

Monte Carlo

MAY 28, 2024

Data Loading : Load transformed data into the target system, such as a data warehouse or data lake. In batch processing, this occurs at scheduled intervals, whereas real-time processing involves continuous loading, maintaining up-to-date data availability. Used for identifying and cataloging data sources.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

Knowledge Hut

NOVEMBER 19, 2023

As a result, data engineers working with big data today require a basic grasp of cloud computing platforms and tools. Businesses can employ internal, public, or hybrid clouds depending on their data storage needs, including AWS, Azure, GCP, and other well-known cloud computing platforms.

Data Engineering 52

Data Engineering Data Engineer Engineering PostgreSQL 52

Knowledge Hut

MARCH 28, 2024

They use many data storage, computation, and analytics technologies to develop scalable and robust data pipelines. Role Level Intermediate Responsibilities Design and develop data pipelines to ingest, process, and transform data. Education & Skills Required Using technologies such as Hadoop, Kafka, and Spark.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52