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

Cloudera

JANUARY 21, 2021

By separating the compute, the metadata, and data storage, CDW dynamically adapts to changing workloads and resource requirements, speeding up deployment while effectively managing costs – while preserving a shared access and governance model. Architecture overview. Separate storage. Separate compute.

IT 94

IT Data Lake Data Warehouse Cloud Storage 94

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

phData: Data Engineering

APRIL 4, 2023

Today we want to introduce Fivetran’s support for Amazon S3 with Apache Iceberg, investigate some of the implications of this feature, and learn how it fits into the modern data architecture as a whole. Fivetran today announced support for Amazon Simple Storage Service (Amazon S3) with Apache Iceberg data lake format.

Data Lake 52

Data Lake Amazon Web Services Data Cleanse Data Warehouse 52

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

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

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

Monte Carlo

AUGUST 25, 2023

Data teams need to balance the need for robust, powerful data platforms with increasing scrutiny on costs. 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.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Cloudera

SEPTEMBER 15, 2022

Modern data platforms deliver an elastic, flexible, and cost-effective environment for analytic applications by leveraging a hybrid, multi-cloud architecture to support data fabric, data mesh, data lakehouse and, most recently, data observability. Luke: What is a modern data platform?

Data Lake 83

Data Lake Analytics Application Cloud Storage Architecture 83

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, Architecture. Pre-Check: Data Lake Cluster. Understanding Ranger Policies in Data Lake Cluster.

Cloud 73

Cloud Data Lake Cloud Storage Metadata 73

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

ProjectPro

DECEMBER 7, 2021

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. As data is expanding exponentially, organizations struggle to harness digital information's power for different business use cases. What is a Big Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

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

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

WeCloudData

OCTOBER 19, 2021

The team was able to achieve this by leveraging cloud as well as open source tools in a modular set up, taking advantage of relatively cheap cloud storage, a versatile programming language in Python and Spark’s powerful processing engine.

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 52

WeCloudData

OCTOBER 19, 2021

The team was able to achieve this by leveraging cloud as well as open source tools in a modular set up, taking advantage of relatively cheap cloud storage, a versatile programming language in Python and Spark’s powerful processing engine.

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 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

AltexSoft

FEBRUARY 11, 2023

To get a better understanding of a data architect’s role, let’s clear up what data architecture is. Data architecture is the organization and design of how data is collected, transformed, integrated, stored, and used by a company. Sample of a high-level data architecture blueprint for Azure BI programs.

Data Architect 87

Data Architect Certification Generalist Big Data 87

AltexSoft

MARCH 30, 2023

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. The relatively new storage architecture powering Databricks is called a data lakehouse. Databricks lakehouse platform architecture.

Scala 64

Scala Data Lake Machine Learning BI 64

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

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., Build data architecture.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Ascend.io

AUGUST 31, 2023

In the dynamic world of data, many professionals are still fixated on traditional patterns of data warehousing and ETL, even while their organizations are migrating to the cloud and adopting cloud-native data services. Central to this transformation are two shifts. Let’s take a closer look.

Data Lake 52

Data Lake Data Warehouse ETL Tools Data Pipeline 52

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

Cloudera

OCTOBER 26, 2017

Become more agile with business intelligence and data analytics. Clouds (source: Pexels ). 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. Architecture patterns for the cloud.

Cloud 43

Cloud BI Cloud Storage Business Intelligence 43

ProjectPro

OCTOBER 6, 2021

Online Book Store System using Google Cloud Platform 15 Sample GCP Real Time Projects for Practice in 2023 With the need to learn Cloud Platform as part of any analytical job role, it is essential to understand the basics and then gain some hands-on experience leveraging the cloud platforms.

Google Cloud 52

Google Cloud Project Data Lake Healthcare 52

Rockset

AUGUST 25, 2021

With this release , Rockset users have the capability to continuously aggregate and transform data at the time of ingest, using SQL, from any data source (data streams, databases and data lakes). This is a first in the industry and frees users from managing slow, expensive ETL pipelines for their streaming data.

Aggregated Data 52

Aggregated Data Hadoop SQL Data Lake 52

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. This can extend to streaming analytics capabilities into any cloud environment.

Banking 62

Banking Kafka Cloud Storage Government 62

Knowledge Hut

JUNE 26, 2023

A complete end-to-end stream processing pipeline is shown here using an architectural diagram. The pipeline in this reference design collects data from two different sources, then conducts a join operation on related records from each stream, then enriches the output, and finally produces an average.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Rockset

AUGUST 4, 2021

Organizations that depend on data for their success and survival need robust, scalable data architecture, typically employing a data warehouse for analytics needs. Snowflake is often their cloud-native data warehouse of choice. Snowflake provides a couple of ways to load data.

Data Ingestion 40

Data Ingestion Cloud Storage Data Warehouse Architecture 40

ProjectPro

JANUARY 24, 2023

Tired of relentlessly searching for the most effective and powerful data warehousing solutions on the internet? This blog is your comprehensive guide to Google BigQuery, its architecture, and a beginner-friendly tutorial on how to use Google BigQuery for your data warehousing activities. Search no more! Did you know ?

Bytes 52

Bytes Google Cloud Data Warehouse Cloud Storage 52

Ascend.io

MAY 18, 2023

The growing complexity drove a proliferation of software and data innovations, which in turn demanded highly trained data engineers to build code-based data pipelines that ensured data quality, consistency, and stability. Because data pipelines were coded from scratch, they started breaking down under the complexity.

Data Warehouse 52

Data Warehouse Data Pipeline Data Lake Data Engineering 52

Rockset

MAY 24, 2021

Serverless computing (often just called "serverless") is a model where a cloud provider, like AWS, abstracts away the concept of servers from the user. Serverless architecture entails the dynamic allocation of resources to carry out various execution tasks. What Is Serverless? Serverless is not limited to functions.

Database 40

Database Google Cloud AWS Cloud Storage 40

Monte Carlo

JANUARY 27, 2024

Those tools include: Table of Contents Cloud storage and compute Data transformation Business Intelligence (BI) Data observability Data orchestration The most important part? Cloud storage and compute Whether you’re stacking data tools or pancakes, you always build from the bottom up.

Building 52

Building Business Intelligence Cloud Storage BI 52

Confluent

OCTOBER 16, 2019

Along with using Postgres (or KSQL as shown above) for analytics, the data can be streamed using Kafka Connect into S3, from where it can serve multiple roles. In S3, it can be seen as the “cold storage”, or the data lake, against which as-yet-unknown applications and processes may be run.

Kafka 19

Kafka Building Data Coding 19

Knowledge Hut

JULY 6, 2023

It is a built-in Massively parallel processing (MPP) data lake house to handle all your infrastructure observability and security needs. It is a free standalone application that makes working with Azure Storage data on Windows, macOS, and Linux effortlessly.

Amazon Web Services 52

Amazon Web Services Data Lake Java SQL 52

ProjectPro

AUGUST 24, 2021

If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of best data engineering project examples below. With the trending advance of IoT in every facet of life, technology has enabled us to handle a large amount of data ingested with high velocity.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Striim

AUGUST 22, 2024

“Sometimes there’s so much data that old batch processing (late at night once a day or once a week) just doesn’t have time to move all data and hence the only way to do it is trickle feed data via CDC,” says Dmitriy Rudakov, Director of Solution Architecture at Striim.

Data Warehouse 52

Data Warehouse Retail Machine Learning Database 52