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Data lakes vs. data warehouses: Decoding the data storage debate

Data Science Dojo

When it comes to data, there are two main types: data lakes and data warehouses. What is a data lake? An enormous amount of raw data is stored in its original format in a data lake until it is required for analytics applications. Which one is right for your business? Let’s take a closer look.

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Differentiating Between Data Lakes and Data Warehouses

Smart Data Collective

The market for data warehouses is booming. While there is a lot of discussion about the merits of data warehouses, not enough discussion centers around data lakes. We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes. Data Warehouse.

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Data Lakes Vs. Data Warehouse: Its significance and relevance in the data world

Pickl AI

Discover the nuanced dissimilarities between Data Lakes and Data Warehouses. Data management in the digital age has become a crucial aspect of businesses, and two prominent concepts in this realm are Data Lakes and Data Warehouses. It acts as a repository for storing all the data.

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How OCX Cognition reduced ML model development time from weeks to days and model update time from days to real time using AWS Step Functions and Amazon SageMaker

AWS Machine Learning Blog

This post was co-authored by Brian Curry (Founder and Head of Products at OCX Cognition) and Sandhya MN (Data Science Lead at InfoGain) OCX Cognition is a San Francisco Bay Area-based startup, offering a commercial B2B software as a service (SaaS) product called Spectrum AI. Finally, the code is run using Step Functions.

AWS 91
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Beyond data: Cloud analytics mastery for business brilliance

Dataconomy

Machine learning and AI analytics: Machine learning and AI analytics leverage advanced algorithms to automate the analysis of data, discover hidden patterns, and make predictions. IoT analytics: IoT (Internet of Things) analytics deals with data generated by IoT devices, such as sensors, connected appliances, and industrial equipment.

Analytics 203
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Celebrating 40 years of Db2: Running the world’s mission critical workloads

IBM Journey to AI blog

Db2 Warehouse SaaS, on the other hand, is a fully managed elastic cloud data warehouse with our columnar technology. watsonx.data integration At Think, IBM announced watsonx.data as a new open, hybrid and governed data store optimized for all data, analytics, and AI workloads.

Database 101
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What Are the Best Data Modeling Methodologies & Processes for My Data Lake?

phData

A rigid data model such as Kimball or Data Vault would ruin this flexibility and essentially transform your data lake into a data warehouse. However, some flexible data modeling techniques can be used to allow for some organization while maintaining the ease of new data additions.