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

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

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

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 Engineer 130

Data Engineer Data Engineering Engineering Hadoop 130

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 85

Data Lake Data Ingestion Bytes Cloud Computing 85

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 95

Data Lake Machine Learning Data Storage Cloud Computing 95

Cloudera

JANUARY 21, 2021

With CDW, as an integrated service of CDP, your line of business gets immediate resources needed for faster application launches and expedited data access, all while protecting the company’s multi-year investment in centralized data management, security, and governance. Proprietary file formats mean no one else is invited in!

IT 96

IT Data Lake Data Warehouse Cloud Storage 96

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 92

Data Lake Data Storage Government Kafka 92

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

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 Accessibility 86

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

Data Engineering Podcast

AUGUST 14, 2021

Your host is Tobias Macey and today I’m interviewing Davit Buniatyan about Activeloop, a platform for hosting and delivering datasets optimized for machine learning Interview Introduction How did you get involved in the area of data management? What is the process for sourcing, processing, and storing data to be used by Hub/Activeloop?

Unstructured Data 100

Unstructured Data Machine Learning Data Lake SQL 100

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 74

Data Lake Data Warehouse Hadoop Architecture 74

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

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

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

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

Cloudera

AUGUST 9, 2022

Standby systems can be designed to meet storage requirements during typical periods with burstable compute for failover scenarios using new features such as Data Lake Scaling. Automating the healing, recovery, scaling, and rebalancing of core data services such as our Operational Database.

Data Lake 84

Data Lake Data Warehouse Architecture Data Ingestion 84

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 Engineer 69

Data Engineer Data Engineering Pipeline-centric Engineering 69

Knowledge Hut

JANUARY 18, 2024

IBM is one of the best companies to work for in Data Science. The platform allows not only data storage but also deep data processing by making use of Apache Hadoop. The CDP private cloud is a scalable data storage solution that can handle analytical and machine learning workloads.

Data Science 98

Data Science Amazon Web Services Big Data Finance 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 Metadata Scala Data Lake 98

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 Engineer 52

Data Engineer Data Engineering NoSQL Engineering 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

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

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

Towards Data Science

DECEMBER 15, 2023

Even the best of us sometimes demonize the parts of our organization whose primary goals are in the privacy and security area and conflict with our wishes to splash around in the data lake. In reality, data scientists are not always the heroes and IT and security teams are not the villains. How Much Data Do We Need?

Machine Learning 88

Machine Learning Data Science Data Security Data Storage 88

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

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 Engineer 52

Data Engineer Data Engineering Engineering Data Lake 52

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 Engineer 52

Data Engineer Data Engineering Engineering Amazon Web Services 52