Seattle Data Guy

AUGUST 2, 2023

A few months ago, I uploaded a video where I discussed data warehouses, data lakes, and transactional databases. However, the world of data management is evolving rapidly, especially with the resurgence of AI and machine learning.

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Uber Engineering

OCTOBER 27, 2024

Learn how Uber is streamlining the Cloud migration of its massive Data Lake by incorporating key Data Mesh principles.

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Start Data Engineering

APRIL 12, 2022

Introduction Data lakes and data warehouses Data lake Data warehouse Criteria to choose lake and warehouse tools Conclusion Further reading References Introduction With the data ecosystem growing fast, new terms are coming up every week.

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KDnuggets

OCTOBER 30, 2023

A comparative overview of data warehouses, data lakes, and data marts to help you make informed decisions on data storage solutions for your data architecture.

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Hevo

JULY 15, 2024

From mobile devices and IoT sensors to our online content, unprecedented amounts of data are generated. Traditional databases and warehouse technologies cannot handle this data volume and variety burst. This led to the rise of data lakes […]

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Hevo

JULY 15, 2024

From mobile devices and IoT sensors to our online content, unprecedented amounts of data are generated. Traditional databases and warehouse technologies cannot handle this data volume and variety burst. This led to the rise of data lakes […]

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Seattle Data Guy

DECEMBER 19, 2022

Whether its helping increase revenue by finding new customers or reducing costs, all of it starts with data.

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Hevo

JULY 25, 2024

A data lake is a central storage place for an organization’s data in its original format. Unlike data warehouses, data lakes can handle all kinds of data, including unstructured and semi-structured data like images, video, audio, and documents.

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KDnuggets

FEBRUARY 5, 2024

How and why the data lake architecture often fails to meet its promises. And how better governance helps mitigate such challenges.

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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. It is often used as a foundation for enterprise data lakes.

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Hevo

JULY 12, 2024

Building a data lake for reporting, analytics, and machine learning needs has become general practice. Data lakes allow us to ingest data from multiple sources in their raw formats in real time. This will enable us to scale any data size and save time in defining its schema and transformations.

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Data Engineering Podcast

AUGUST 3, 2021

Summary Data lake architectures have largely been biased toward batch processing workflows due to the volume of data that they are designed for. With more real-time requirements and the increasing use of streaming data there has been a struggle to merge fast, incremental updates with large, historical analysis.

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Hevo

JULY 23, 2024

The term “Data Lake” was first introduced by James Dixon in 2010 as a form of storage to cope with evolving data needs due to advancements in IT and IoT. The close of the 19th century and beginning of the 20th century saw an influx of new digital tools like the mobile phone and smart […]

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Hevo

SEPTEMBER 4, 2024

Currently, data management is a continually developing field that requires careful consideration when deciding which solution should be implemented to store, process, and analyze data effectively. There are two forms that are frequently selected: data warehouse vs data lake.

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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.

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Hevo

APRIL 20, 2024

In the early 2000s, organizations started dealing with more semi-structured and unstructured data, which consisted of images, videos, log files, text, and sensor data. They needed a storage solution that was more flexible than a data warehouse.

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Towards Data Science

SEPTEMBER 27, 2023

Data Access API over Data Lake Tables Without the Complexity Build a robust GraphQL API service on top of your S3 data lake files with DuckDB and Go Photo by Joshua Sortino on Unsplash 1. This data might be primarily used for internal reporting, but might also be valuable for other services in our organization.

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KDnuggets

JANUARY 16, 2023

In this article, we will discuss the benefits of using SQL with a data lake and how it can help organizations unlock the full potential of their data.

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Cloudyard

DECEMBER 13, 2022

Read Time: 4 Minute, 23 Second During this post we will discuss how AWS S3 service and Snowflake integration can be used as Data Lake in current organizations. How customer has migrated On Premises EDW to Snowflake to leverage snowflake Data Lake capabilities.

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Data Engineering Podcast

NOVEMBER 20, 2021

Summary One of the perennial challenges posed by data lakes is how to keep them up to date as new data is collected. In this episode Ori Rafael shares his experiences from Upsolver and building scalable stream processing for integrating and analyzing data, and what the tradeoffs are when coming from a batch oriented mindset.

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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.

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phData: Data Engineering

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. What is a Data Lake? Consistency of data throughout the data lake.

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Hevo

JULY 12, 2024

Are you looking for a data lake tool that is scalable, cost-efficient, and accessible, can store your business’s historical data, and can help you perform intelligent analytics? To lift the weight off your shoulders, I have compiled a list of data lake tools. No worries.

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DareData

JULY 5, 2023

Learn how we build data lake infrastructures and help organizations all around the world achieving their data goals. In today's data-driven world, organizations are faced with the challenge of managing and processing large volumes of data efficiently.

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Data Engineering Podcast

JUNE 1, 2020

Summary Data lakes offer a great deal of flexibility and the potential for reduced cost for your analytics, but they also introduce a great deal of complexity. In order to bring the DBA into the new era of data management the team at Upsolver added a SQL interface to their data lake platform.

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Data Engineering Podcast

MAY 15, 2022

Summary Designing a data platform is a complex and iterative undertaking which requires accounting for many conflicting needs. Designing a platform that relies on a data lake as its central architectural tenet adds additional layers of difficulty. When is a data lake architecture the wrong choice?

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Data Engineering Podcast

JULY 22, 2019

Summary The current trend in data management is to centralize the responsibilities of storing and curating the organization’s information to a data engineering team. This organizational pattern is reinforced by the architectural pattern of data lakes as a solution for managing storage and access.

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Data Engineering Podcast

NOVEMBER 2, 2020

Summary Data lakes are gaining popularity due to their flexibility and reduced cost of storage. Along with the benefits there are some additional complexities to consider, including how to safely integrate new data sources or test out changes to existing pipelines.

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Data Engineering Podcast

JUNE 16, 2019

Summary Building and maintaining a data lake is a choose your own adventure of tools, services, and evolving best practices. The flexibility and freedom that data lakes provide allows for generating significant value, but it can also lead to anti-patterns and inconsistent quality in your analytics.

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Grouparoo

JANUARY 11, 2022

This article looks at the options available for storing and processing big data, which is too large for conventional databases to handle. There are two main options available, a data lake and a data warehouse. What is a Data Warehouse? What is a Data Lake?

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AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. What is a data lake?

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Data Engineering Podcast

SEPTEMBER 1, 2021

Summary The Presto project has become the de facto option for building scalable open source analytics in SQL for the data lake. Another area that has been seeing a lot of activity is data lakes and projects to make them more manageable and feature complete (e.g. Hudi, Delta Lake, Iceberg, Nessie, LakeFS, etc.).

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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. .

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

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KDnuggets

JANUARY 16, 2020

Whereas a data warehouse will need rigid data modeling and definitions, a data lake can store different types and shapes of data. In a data lake, the schema of the data can be inferred when it’s read, providing the aforementioned flexibility.

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Snowflake

AUGUST 8, 2023

In 2022, the company realized that in order to monitor, analyze, counter, and prevent security threats, it needed both a modern data lake as well as a security information and event management (SIEM) solution. Then, they conducted insight mining by querying the data on different topics.

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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.

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