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Data Lake Data Storage Data Warehouse 
Analytics Vidhya
FEBRUARY 2, 2023
Introduction In this constantly growing era, the volume of data is increasing rapidly, and tons of data points are produced every second. Now, businesses are looking for different types of data storage to store and manage their data effectively.
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Snowflake
APRIL 2, 2025
Data storage has been evolving, from databases to data warehouses and expansive data lakes, with each architecture responding to different business and data needs. Now you dont have to choose. This is why Snowflake is fully embracing this open table format.
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Agent Tooling: Connecting AI to Your Tools, Systems & Data
How to Modernize Manufacturing Without Losing Control
Mastering Apache Airflow® 3.0: What’s New (and What’s Next) for Data Orchestration
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.
139 
Seattle Data Guy
DECEMBER 19, 2022
Whether its helping increase revenue by finding new customers or reducing costs, all of it starts with data.
130 
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?
52 
Sync Computing
NOVEMBER 7, 2024
A brief history of data storage The value of data has been apparent for as long as people have been writing things down. Despite these limitations, data warehouses, introduced in the late 1980s based on ideas developed even earlier, remain in widespread use today for certain business intelligence and data analysis applications.
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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.
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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?
52 
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?
52 
Data Engineering Weekly
FEBRUARY 2, 2025
[link] Get Your Guide: From Snowflake to Databricks: Our cost-effective journey to a unified data warehouse. GetYourGuide discusses migrating its Business Intelligence (BI) data source from Snowflake to Databricks, achieving a 20% cost reduction.
Monte Carlo
OCTOBER 31, 2024
There are dozens of data engineering tools available on the market, so familiarity with a wide variety of these can increase your attractiveness as an AI data engineering candidate. Data Storage Solutions As we all know, data can be stored in a variety of ways.
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.
52 
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.
52 
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.
Christophe Blefari
JANUARY 20, 2024
Data engineering inherits from years of data practices in US big companies. Hadoop initially led the way with Big Data and distributed computing on-premise to finally land on Modern Data Stack — in the cloud — with a data warehouse at the center. Picking the right format for your data storage.
130 
Monte Carlo
SEPTEMBER 25, 2024
A data lake is essentially a vast digital dumping ground where companies toss all their raw data, structured or not. A modern data stack can be built on top of this data storage and processing layer, or a data lakehouse or data warehouse, to store data and process it before it is later transformed and sent off for analysis.
52 
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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Cloudera
JANUARY 21, 2021
While cloud-native, point-solution data warehouse services may serve your immediate business needs, there are dangers to the corporation as a whole when you do your own IT this way. Cloudera Data Warehouse (CDW) is here to save the day! CDW is an integrated data warehouse service within Cloudera Data Platform (CDP).
94 
Monte Carlo
NOVEMBER 21, 2024
This approach is fantastic when you’re not quite sure how you’ll need to use the data later, or when different teams might need to transform it in different ways. It’s more flexible than ETL and works great with the low cost of modern data storage.
Cloudera
MAY 30, 2024
Cloudera customers run some of the biggest data lakes on earth. These lakes power mission-critical, large-scale data analytics and AI use cases—including enterprise data warehouses.
74 
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.
98 
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.
52 
Monte Carlo
APRIL 4, 2023
Data mesh vs data warehouse is an interesting framing because it is not necessarily a binary choice depending on what exactly you mean by data warehouse (more on that later). Despite their differences, however, both approaches require high-quality, reliable data in order to function. What is a Data Mesh?
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. […]
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 […]
40 
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. .
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Data Engineering Podcast
AUGUST 14, 2021
Are you bored with writing scripts to move data into SaaS tools like Salesforce, Marketo, or Facebook Ads? Hightouch is the easiest way to sync data into the platforms that your business teams rely on. The data you’re looking for is already in your data warehouse and BI tools. No more scripts, just SQL.
Monte Carlo
JANUARY 25, 2023
When it comes to the question of building or buying your data stack, there’s never a one-size-fits-all solution for every data team—or every component of your data stack. Data storage and compute are very much the foundation of your data platform. Let’s jump in!
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.
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.
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.
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?
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AltexSoft
AUGUST 4, 2021
Now let’s think of sweets as the data required for your company’s daily operations. Instead of combing through the vast amounts of all organizational data stored in a data warehouse, you can use a data mart — a repository that makes specific pieces of data available quickly to any given business unit.
64 
Cloudera
AUGUST 9, 2022
Data platforms are no longer skunkworks projects or science experiments. As customers import their mainframe and legacy data warehouse workloads, there is an expectation on the platform that it can meet, if not exceed, the resilience of the prior system and its associated dependencies.
78 
Cloudera
DECEMBER 12, 2018
After having rebuilt their data warehouse, I decided to take a little bit more of a pointed role, and I joined Oracle as a database performance engineer. I spent eight years in the real-world performance group where I specialized in high visibility and high impact data warehousing competes and benchmarks.
AltexSoft
OCTOBER 30, 2021
Data engineer’s integral task is building and maintaining data infrastructure — the system managing the flow of data from its source to destination. This typically includes setting up two processes: an ETL pipeline , which moves data, and a data storage (typically, a data warehouse ), where it’s kept.
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.
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.
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.
ProjectPro
FEBRUARY 8, 2023
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., Glue uses ETL jobs for extracting data from various AWS cloud services and integrating it into data warehouses and lakes.
98 
Sync Computing
JANUARY 27, 2025
EC2 storage options Amazon EC2 provides several key storage options tailored to different workload needs: Elastic Block Store (EBS) : Persistent, high-performance block storage ideal for boot volumes, databases, and data warehouses.
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Towards Data Science
DECEMBER 15, 2023
Taking a hard look at data privacy puts our habits and choices in a different context, however. Data scientists’ instincts and desires often work in tension with the needs of data privacy and security. Anyone who’s fought to get access to a database or data warehouse in order to build a model can relate.
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.
AltexSoft
NOVEMBER 10, 2021
The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Data warehouse vs data lake vs data lakehouse: What’s the difference.
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