DataKitchen

DECEMBER 9, 2024

They opted for Snowflake, a cloud-native data platform ideal for SQL-based analysis. The team landed the data in a Data Lake implemented with cloud storage buckets and then loaded into Snowflake, enabling fast access and smooth integrations with analytical tools.

Pharmaceutical 64

Pharmaceutical Data Lake Cloud Storage Project 64

Cloudera

FEBRUARY 14, 2019

The Cloudera platform delivers a one-stop shop that allows you to store any kind of data, process and analyze it in many different ways in a single environment, and integrate with the rest of your data infrastructure. But working with cloud storage has often been a compromise. As a Hadoop developer, I loved that!

Data Lake 60

Data Lake Hadoop Cloud Storage Cloud 60

Monte Carlo

APRIL 24, 2023

Data lakes are useful, flexible data storage repositories that enable many types of data to be stored in its rawest state. Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Snowflake

DECEMBER 4, 2023

With this public preview, those external catalog options are either “GLUE”, where Snowflake can retrieve table metadata snapshots from AWS Glue Data Catalog, or “OBJECT_STORE”, where Snowflake retrieves metadata snapshots directly from the specified cloud storage location. With these three options, which one should you use?

Building 122

Building Metadata Cloud Storage AWS 122

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

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

Cloudera

JANUARY 21, 2021

Of high value to existing customers, Cloudera’s Data Warehouse service has a unique, separated architecture. . Separate storage. Cloudera’s Data Warehouse service allows raw data to be stored in the cloud storage of your choice (S3, ADLSg2). Proprietary file formats mean no one else is invited in!

IT 94

IT Data Lake Data Warehouse Cloud Storage 94

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

Data Engineering Podcast

JUNE 12, 2022

Acryl Data provides DataHub as an easy to consume SaaS product which has been adopted by several companies. Signup for the SaaS product at dataengineeringpodcast.com/acryl RudderStack helps you build a customer data platform on your warehouse or data lake. What are the mechanisms that you use for categorizing data assets?

Unstructured Data 130

Unstructured Data MongoDB MySQL Scala 130

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

Cloudera

MARCH 31, 2021

With the addition of Google Cloud, we deliver on our vision of providing a hybrid and multi-cloud architecture to support our customer’s analytics needs regardless of deployment platform. . You could then use an existing pipeline to run analytics on the prepared data in BigQuery. .

Google Cloud 94

Google Cloud Cloud Amazon Web Services Cloud Storage 94

Cloudera

JUNE 25, 2021

This blog post outlines detailed step by step instructions to perform Hive Replication from an on-prem CDH cluster to a CDP Public Cloud Data Lake. CDP Data Lake cluster versions – CM 7.4.0, Configure the required ports to enable connectivity from CDH to CDP Public Cloud (see docs for details).

Cloud 73

Cloud Data Lake Cloud Storage Metadata 73

Towards Data Science

APRIL 26, 2023

An open-source implementation of a Data Lake with DuckDB and AWS Lambdas A duck in the cloud. Photo by László Glatz on Unsplash In this post we will show how to build a simple end-to-end application in the cloud on a serverless infrastructure. The idea is to start from a Data Lake where our data are stored.

Engineering 96

Engineering Data Lake AWS BI 96

Data Engineering Podcast

SEPTEMBER 22, 2019

Summary Object storage is quickly becoming the unifying layer for data intensive applications and analytics. Modern, cloud oriented data warehouses and data lakes both rely on the durability and ease of use that it provides. How do you approach project governance and sustainability?

AWS 100

AWS Google Cloud Cloud Storage Data Lake 100

Cloudera

SEPTEMBER 15, 2022

Mark: The first element in the process is the link between the source data and the entry point into the data platform. At Ramsey International (RI), we refer to that layer in the architecture as the foundation, but others call it a staging area, raw zone, or even a source data lake.

Data Lake 83

Data Lake Analytics Application Cloud Storage Architecture 83

Cloudera

JUNE 5, 2023

RK built some simple flows to pull streaming data into Google Cloud Storage and Snowflake. Many developers use DataFlow to filter/enrich streams and ingest into cloud data lakes and warehouses where the ability to process and route anywhere makes DataFlow very effective.

Google Cloud 77

Google Cloud Cloud Storage Data Lake Data Pipeline 77

Data Engineering Weekly

AUGUST 11, 2024

link] Uber: Enabling Security for Hadoop Data Lake on Google Cloud Storage Uber writes about securing a Hadoop-based data lake on Google Cloud Platform (GCP) by replacing HDFS with Google Cloud Storage (GCS) while maintaining existing security models like Kerberos-based authentication.

Data Engineering 58

Data Engineering Data Engineer Google Cloud Engineering 58

Cloudera

SEPTEMBER 15, 2020

Cloudera Data Platform 7.2.1 introduces fine-grained authorization for access to Azure Data Lake Storage using Apache Ranger policies. Cloudera and Microsoft have been working together closely on this integration, which greatly simplifies the security administration of access to ADLS-Gen2 cloud storage.

Accessible 79

Accessible Accessibility Cloud Cloud Storage 79

Monte Carlo

JULY 19, 2023

In this article, we’ll present you with the Five Layer Data Stack—a model for platform development consisting of five critical tools that will not only allow you to maximize impact but empower you to grow with the needs of your organization. Before you can model the data for your stakeholders, you need a place to collect and store it.

Building 96

Building Business Intelligence Cloud Storage BI 96

Monte Carlo

FEBRUARY 25, 2025

They make data workflows more resilient and easier to manage when things inevitably go sideways. This guide tackles the big decisions every data engineer faces: Should you clean your data before or after loading it? Data lake or warehouse? Data Lakes vs. Data Warehouses: Where Should Your Data Live?

Designing 52

Designing Data Engineering Data Engineer Engineering 52

Towards Data Science

JULY 21, 2023

In this article, we’ll present you with the Five Layer Data Stack — a model for platform development consisting of five critical tools that will not only allow you to maximize impact but empower you to grow with the needs of your organization. Before you can model the data for your stakeholders, you need a place to collect and store it.

Building 98

Building Business Intelligence BI Cloud Storage 98

WeCloudData

OCTOBER 19, 2021

Conclusion WeCloudData helped a client build a flexible data pipeline to address the needs from multiple business units requiring different sets, views and timelines of job market data.

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 52

WeCloudData

OCTOBER 19, 2021

Conclusion WeCloudData helped a client build a flexible data pipeline to address the needs from multiple business units requiring different sets, views and timelines of job market data.

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 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. You’re using the data, of course!

Machine Learning 98

Machine Learning Data Science Data Security Data Storage 98

Cloudyard

AUGUST 22, 2023

With this feature, you can efficiently manage, govern, and analyze your data irrespective of its storage location, ensuring optimal data management. This feature significantly contributes to enhancing your data management capabilities within the Snowflake ecosystem. Zero egress fees mean zero vendor lock-in.”

Bytes 52

Bytes Data Lake Cloud Storage Cloud 52

Ascend.io

AUGUST 31, 2023

Secondly , the rise of data lakes that catalyzed the transition from ELT to ELT and paved the way for niche paradigms such as Reverse ETL and Zero-ETL. Still, these methods have been overshadowed by EtLT — the predominant approach reshaping today’s data landscape.

Data Lake 52

Data Lake Data Warehouse ETL Tools Data Pipeline 52

AltexSoft

MAY 12, 2023

Unstructured data , on the other hand, is unpredictable and has no fixed schema, making it more challenging to analyze. Without a fixed schema, the data can vary in structure and organization. There are several widely used unstructured data storage solutions such as data lakes (e.g., Hadoop, Apache Spark).

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Edureka

JULY 3, 2024

ADF leverages compute services like Azure HDInsight, Spark, Azure Data Lake Analytics, or Machine Learning to process and analyze the data according to defined requirements. Publish: Transformed data is then published either back to on-premises sources like SQL Server or kept in cloud storage.

Pipeline-centric 52

Pipeline-centric Data Lake Database-centric Data Pipeline 52

DareData

JANUARY 30, 2023

Data lakes: These are large-scale data storage systems that are designed to store and process large amounts of raw, unstructured data. Examples of technologies able to aggregate data in data lake format include Amazon S3 or Azure Data Lake. Stanford's Relational Databases and SQL.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

Cloudera

DECEMBER 14, 2017

Improved support for cloud storage systems like S3 (with S3Guard ), Microsoft Azure Data Lake, and Aliyun OSS. YARN Timeline Service v2, which improves the scalability, reliability, and usability of the existing Timeline Service. See the Apache Hadoop 3.0.0 documentation for a full rundown of the changes.

Hadoop 43

Hadoop Cloud Storage Data Lake Software Engineering 43

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake Machine Learning BI 64

Cloudera

FEBRUARY 16, 2022

Each workspace is associated with a collection of cloud resources. In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage.

Machine Learning 85

Machine Learning Algorithm Government Metadata 85

Knowledge Hut

SEPTEMBER 26, 2023

Key connectivity features include: Data Ingestion: Databricks supports data ingestion from a variety of sources, including data lakes, databases, streaming platforms, and cloud storage. This flexibility allows organizations to ingest data from virtually anywhere.

Data Lake 52

Data Lake Database-centric Machine Learning Pipeline-centric 52

Snowflake

FEBRUARY 23, 2023

Snowflake’s solution to ingesting very large healthcare pricing transparency data files. In the above solution approach, the pricing transparency JSON file is hosted in a cloud storage bucket and is referenced through an external stage on Snowflake.

Healthcare 52

Healthcare Hospitality Insurance Cloud Storage 52

Cloudera

OCTOBER 26, 2017

Organizations find they have much more agility with analytics in the cloud and can operate at a lower cost point than has been possible with legacy on-premises solutions. Generally, instances for transient clusters need only minimal local disk space, since data processing runs directly on the data in the cloud storage.

Cloud 43

Cloud BI Cloud Storage Business Intelligence 43

Cloudera

AUGUST 21, 2020

Data-in-motion is predominantly about streaming data so enterprises typically have two different ways or binary ways of looking at data.

Banking 62

Banking Kafka Cloud Storage Government 62

ProjectPro

OCTOBER 6, 2021

Also, Cloud Endpoints are used, which help speed up the development, making smoother API calls for mobile app development. Data Lake using Google Cloud Platform What is a Data Lake? Data Lake is a centralized area or repository for data storage.

Google Cloud 52

Google Cloud Project Data Lake Healthcare 52