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Discover And De-Clutter Your Unstructured Data With Aparavi

Data Engineering Podcast

Summary Unstructured data takes many forms in an organization. From a data engineering perspective that often means things like JSON files, audio or video recordings, images, etc. This episode is brought to you by Acryl Data, the company behind DataHub, the leading developer-friendly data catalog for the modern data stack.

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The Rise of Unstructured Data

Cloudera

The word “data” is ubiquitous in narratives of the modern world. And data, the thing itself, is vital to the functioning of that world. This blog discusses quantifications, types, and implications of data. Quantifications of data. Quantifications of data. So data is big and growing. And data moves around.

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Prepare Your Unstructured Data For Machine Learning And Computer Vision Without The Toil Using Activeloop

Data Engineering Podcast

Summary The vast majority of data tools and platforms that you hear about are designed for working with structured, text-based data. What do you do when you need to manage unstructured information, or build a computer vision model? Hightouch is the easiest way to sync data into the platforms that your business teams rely on.

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Top 5 Data + AI Predictions for Financial Services in 2024

Snowflake

And it’s no wonder — this new technology has the potential to revolutionize the industry by augmenting the value of employee work, driving organizational efficiencies, providing personalized customer experiences, and uncovering new insights from vast amounts of data. One potential source is data sharing.

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Data Warehouse vs Big Data

Knowledge Hut

In the modern data-driven landscape, organizations continuously explore avenues to derive meaningful insights from the immense volume of information available. Two popular approaches that have emerged in recent years are data warehouse and big data. Data warehousing offers several advantages.

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GPT and LLMs from a Data Engineering Perspective

Jesse Anderson

There has been quite a bit of writing covering GPT and LLMs from data science and business perspectives. I haven’t seen much from the data engineering side. Let me share my perspective, having been in data and AI for a while and using LLMs before they became popular. How can we use LLMs in data engineering?

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Data Engineering Weekly #166

Data Engineering Weekly

Poor data quality and unlcear data ownership remains the top challenges for the data teams. Data Mesh continuously gaining popularity among the enterprises. It is a stark difference from the Gartner report about data mesh. I guess only the time will tell who wins in the data mesh vs data fabric war.