Precisely

MARCH 9, 2023

Data warehouse vs. data lake, each has their own unique advantages and disadvantages; it’s helpful to understand their similarities and differences. In this article, we’ll focus on a data lake vs. data warehouse. Read Many of the preferred platforms for analytics fall into one of these two categories.

Data Lake 57

Data Lake Data Warehouse Hadoop Raw Data 57

Snowflake

NOVEMBER 2, 2023

Over the years, the technology landscape for data management has given rise to various architecture patterns, each thoughtfully designed to cater to specific use cases and requirements. These patterns include both centralized storage patterns like data warehouse , data lake and data lakehouse , and distributed patterns such as data mesh.

Data Lake 91

Data Lake Data Warehouse Cloud Unstructured Data 91

Start Data Engineering

APRIL 10, 2020

Many data engineers coming from traditional batch processing frameworks have questions about real time data processing systems, like “What kind of data model did you implement, for real-time processing?”

Data Warehouse 130

Data Warehouse Building Data Data Engineering 130

Towards Data Science

JUNE 6, 2023

The fact it’s insanely fast and does (mostly) all processing in memory make it a good choice for building my personal data warehouse. Fitbit activity data The first collection of files I looked at was activity data. Extra points for its seamless integration with Python and R.

Data Warehouse 90

Data Warehouse Data SQL Data Analysis 90

Towards Data Science

MAY 8, 2023

Data Warehouse Dimensional Modeling Design 101 Continue reading on Towards Data Science »

Data Warehouse 68

Data Warehouse Data Engineering Data Engineer Building 68

Monte Carlo

FEBRUARY 6, 2023

So, you’re planning a cloud data warehouse migration. But be warned, a warehouse migration isn’t for the faint of heart. As you probably already know if you’re reading this, a data warehouse migration is the process of moving data from one warehouse to another. A worthy quest to be sure.

Data Warehouse 52

Data Warehouse AWS Data Validation Data 52

Data Engineering Podcast

JANUARY 1, 2022

In this episode Emily Riederer shares her work to create a controlled vocabulary for managing the semantic elements of the data managed by her team and encoding it in the schema definitions in her data warehouse. star/snowflake schema, data vault, etc.)

Data Warehouse 100

Data Warehouse BI Data Workflow Data 100

Monte Carlo

JANUARY 25, 2023

In an evolving data landscape, the explosion of new tooling solutions—from cloud-based transforms to data observability —has made the question of “build versus buy” increasingly important for data leaders. Data storage and compute are very much the foundation of your data platform. Let’s jump in!

Data Warehouse 40

Data Warehouse Building Data Lake Data Storage 40

Data Engineering Podcast

DECEMBER 8, 2019

Summary Data warehouses have gone through many transformations, from standard relational databases on powerful hardware, to column oriented storage engines, to the current generation of cloud-native analytical engines. If you are evaluating your options for building or migrating a data platform, then this is definitely worth a listen.

Data Warehouse 100

Data Warehouse Cloud AWS Relational Database 100

Monte Carlo

OCTOBER 17, 2022

Platform and data warehouse migrations aren’t something you do everyday or even every few years, but they’re becoming much more frequent as organizations seek to modernize their data infrastructure with the new capabilities being offered by Snowflake, Databricks, Google, AWS, and others. Editor’s note: We agree.

Data Warehouse 59

Data Warehouse AWS MySQL Data 59

Data Engineering Podcast

NOVEMBER 26, 2019

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.

Data Warehouse 100

Data Warehouse Building PostgreSQL Kafka 100

Data Engineering Podcast

OCTOBER 14, 2019

Summary Managing a data warehouse can be challenging, especially when trying to maintain a common set of patterns. They provide an AWS-native, serverless, data infrastructure that installs in your VPC. Datacoral helps data engineers build and manage the flow of data pipelines without having to manage any infrastructure.

Data Warehouse 100

Data Warehouse PostgreSQL AWS Programming Language 100

Monte Carlo

JANUARY 25, 2023

In this article, Chad Sanderson , Head of Product, Data Platform , at Convoy and creator of Data Quality Camp , introduces a new application of data contracts: in your data warehouse. In the last couple of posts , I’ve focused on implementing data contracts in production services.

Data Warehouse 52

Data Warehouse Data High Quality Data Metadata 52

Data Engineering Podcast

JANUARY 15, 2023

Trusted by the data teams at Fox, JetBlue, and PagerDuty, Monte Carlo solves the costly problem of broken data pipelines. Monte Carlo also gives you a holistic picture of data health with automatic, end-to-end lineage from ingestion to the BI layer directly out of the box.

Coding 130

Coding Building PostgreSQL Data Lake 130

Cloudera

MARCH 2, 2022

We used 3 benchmarks: Microbenchmark: We ran the build and probe methods 60 times on a smaller number of rows to evaluate the performance and memory consumed. Billion-Row benchmark: On a single daemon, we ran the build and probe benchmark for a billion rows to measure the performance and memory consumed. Build Benchmark.

Data Warehouse 88

Data Warehouse Bytes Data Business Intelligence 88

Data Engineering Podcast

JANUARY 18, 2021

Summary The data warehouse has become the central component of the modern data stack. Building on this pattern, the team at Hightouch have created a platform that synchronizes information about your customers out to third party systems for use by marketing and sales teams. Can you describe how Hightouch is architected?

Data Warehouse 100

Data Warehouse BI Data Data Pipeline 100

Cloudera

MAY 23, 2024

In modern enterprises, the exponential growth of data means organizational knowledge is distributed across multiple formats, ranging from structured data stores such as data warehouses to multi-format data stores like data lakes.

Systems 78

Systems Building Management Data Lake 78

Monte Carlo

APRIL 16, 2022

The data warehouse is the foundation of the modern data stack, so it caught our attention when we saw Convoy head of data Chad Sanderson declare, “ the data warehouse is broken ” on LinkedIn. Treating data like an API. Immutable data warehouses have challenges too.

Data Warehouse 52

Data Warehouse Architecture Data Government 52

Data Engineering Podcast

MAY 1, 2022

He describes how the platform is architected, the challenges related to selling cloud technologies into enterprise organizations, and how you can adopt Matillion for your own workflows to reduce the maintenance burden of data integration workflows. What have been the most challenging integrations to build and support?

Data Warehouse 100

Data Warehouse Data Integration Cloud Google Cloud 100

Monte Carlo

AUGUST 25, 2023

Different vendors offering data warehouses, data lakes, and now data lakehouses all offer their own distinct advantages and disadvantages for data teams to consider. 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

Data Engineering Podcast

MAY 27, 2021

Summary The data warehouse has become the focal point of the modern data platform. With increased usage of data across businesses, and a diversity of locations and environments where data needs to be managed, the warehouse engine needs to be fast and easy to manage.

Data Warehouse 100

Data Warehouse Cloud PostgreSQL Kafka 100

Data Engineering Podcast

APRIL 16, 2023

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management RudderStack helps you build a customer data platform on your warehouse or data lake. How have the recent breakthroughs in large language models (LLMs) improved your ability to build features in Zenlytic?

Business Intelligence 147

Business Intelligence Building Data Lake BI 147

Cloudera

JANUARY 15, 2021

Cloud data warehouses allow users to run analytic workloads with greater agility, better isolation and scale, and lower administrative overhead than ever before. The results demonstrate superior price performance of Cloudera Data Warehouse on the full set of 99 queries from the TPC-DS benchmark. Introduction.

Data Warehouse 94

Data Warehouse Cloud Consulting SQL 94

Towards Data Science

FEBRUARY 9, 2024

How to build a modern, scalable data platform to power your analytics and data science projects (updated) Table of Contents: What’s changed? The Platform Integration Data Store Transformation Orchestration Presentation Transportation Observability Closing What’s changed?

Building 80

Building Transportation Data Lake Metadata 80

U-Next

SEPTEMBER 7, 2022

The terms “ Data Warehouse ” and “ Data Lake ” may have confused you, and you have some questions. There are times when the data is structured , but it is often messy since it is ingested directly from the data source. What is Data Warehouse? . Data Warehouse in DBMS: .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

Data Engineering Podcast

JUNE 11, 2023

Summary Data engineering is all about building workflows, pipelines, systems, and interfaces to provide stable and reliable data. Your data can be stable and wrong, but then it isn't reliable. Confidence in your data is achieved through constant validation and testing.

Project 130

Project Building Data Lake Machine Learning 130

Netflix Tech

OCTOBER 27, 2020

Usually Data scientists and engineers write Extract-Transform-Load (ETL) jobs and pipelines using big data compute technologies, like Spark or Presto , to process this data and periodically compute key information for a member or a video. The processed data is typically stored as data warehouse tables in AWS S3.

Data Warehouse 97

Data Warehouse Datasets Data Big Data 97

RudderStack

MAY 11, 2021

RudderStack builds a Customer Data Platform on the Data Warehouse. Where one can join all the customer data into a program & get a personalized UI encounter.

Data Warehouse 40

Data Warehouse Building Data Programming 40

Seattle Data Guy

MAY 26, 2024

Many data engineers and analysts don’t realize how valuable the knowledge they have is. They’ve spent hours upon hours learning SQL, Python, how to properly analyze data, build data warehouses, and understand the differences between eight different ETL solutions.

Consulting 130

Consulting Engineering Data Warehouse SQL 130

Data Engineering Podcast

JULY 8, 2019

Summary The market for data warehouse platforms is large and varied, with options for every use case. It was interesting to learn about some of the custom data types and performance optimizations that are included. What are some of the advanced capabilities, such as SQL extensions, supported data types, etc.

Data Warehouse 100

Data Warehouse MySQL Data Lake Hadoop 100

Data Engineering Podcast

JANUARY 29, 2023

Data analysts create reports that are used by the business to understand and direct the business, but the process is very labor and time intensive. The team at Omni have taken a new approach by automatically building models based on the queries that are executed. Can you describe what Omni Analytics is and the story behind it?

Business Intelligence 130

Business Intelligence PostgreSQL Building BI 130

Simon Späti

MARCH 9, 2021

This post focuses on practical data pipelines with examples from web-scraping real-estates, uploading them to S3 with MinIO, Spark and Delta Lake, adding some Data Science magic with Jupyter Notebooks, ingesting into Data Warehouse Apache Druid, visualising dashboards with Superset and managing everything with Dagster.

Data Engineering 189

Data Engineering Data Engineer Engineering Project 189

dbt Developer Hub

APRIL 19, 2023

The goal of dimensional modeling is to take raw data and transform it into Fact and Dimension tables that represent the business. Part 7: Consume dimensional model ​ Finally, we can consume our dimensional model by connecting to our data warehouse to our Business Intelligence (BI) tools such as Tableau, Power BI, and Looker.

Building 145

Building PostgreSQL BI Database 145

Cloudera

JANUARY 11, 2021

How self-service data warehousing frees IT resources. Cloudera Data Warehouse (CDW) is a cloud service and an integral part of the newly released Cloudera Data Platform (CDP). Key features are: Highly scalable and performant open-source engines for BI and data warehousing workloads. Simplified provisioning.

Data Warehouse 62

Data Warehouse Pharmaceutical Data Lake BI 62

Data Engineering Podcast

DECEMBER 12, 2021

Summary Spark is a powerful and battle tested framework for building highly scalable data pipelines. Because of its proven ability to handle large volumes of data Capital One has invested in it for their business needs. Go to dataengineeringpodcast.com/datafold today to start a 30-day trial of Datafold.

Building 130

Building Data Pipeline BI Data Warehouse 130

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

Data Engineering Podcast

FEBRUARY 18, 2024

Summary A data lakehouse is intended to combine the benefits of data lakes (cost effective, scalable storage and compute) and data warehouses (user friendly SQL interface). Data lakes are notoriously complex. Visit: dataengineeringpodcast.com/data-council today. Your first 30 days are free!

Data Lake 262

Data Lake High Quality Data Data Warehouse Google Cloud 262