Fri.Dec 08, 2023

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Improve your RAG application response quality with real-time structured data

databricks

Retrieval Augmented Generation (RAG) is an efficient mechanism to provide relevant data as context in Gen AI applications. Most RAG applications typically use.

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5 Super Cheat Sheets to Master Data Science

KDnuggets

The collection of super cheat sheets covers basic concepts of data science, probability & statistics, SQL, machine learning, and deep learning.

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Create Many-To-One relationships Between Columns in a Synthetic Table with PySpark UDFs

Towards Data Science

Leverage some simple equations to generate related columns in test tables. Image generated with DALL-E 3 I’ve recently been playing around with Databricks Labs Data Generator to create completely synthetic datasets from scratch. As part of this, I’ve looked at building sales data around different stores, employees, and customers. As such, I wanted to create relationships between the columns I was artificially populating — such as mapping employees and customers to a certain store.

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Personalized AI Made Simple: Your No-Code Guide to Adapting GPTs

KDnuggets

OpenAI revolutionizes personal AI customization with its no-code approach to creating custom ChatGPTs.

Coding 136
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15 Modern Use Cases for Enterprise Business Intelligence

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

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Unified Data Governance: The Key to Greater Visibility

Precisely

The past few years have been transformative, with global events reshaping our personal and professional lives. From a rapidly shifting regulatory environment to volatile economic conditions, today’s business leaders are faced with challenges unlike any in recent memory. In the midst of this turbulence, there has been a pronounced shift toward data-centric strategies.

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ChatGPT’s New Rival: Google’s Gemini

KDnuggets

Google has introduced a revamped AI model that is said to outperform ChatGPT. Let’s learn more.

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Add One Line of SQL to Optimise Your BigQuery Tables

Towards Data Science

Clustering: A simple way to group similar rows and prevent unnecessary data processing Continue reading on Towards Data Science »

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Accelerate Business Value from Data Sharing with Databricks Unity Catalog and Tredence UnityGO!

databricks

Enterprise leaders are turning to the Databricks Data Intelligence Platform to create a centralized source of high-quality data that business teams can leverage.

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Enhancing Business Efficiency with Striim’s ‘Read Once, Write Everywhere’ CDC Pattern

Striim

In today’s data-driven business landscape, the ability to effectively capture and utilize real-time data is paramount. Change Data Capture (CDC) is not just a technical process; it’s a gateway to unparalleled business efficiency and intelligence. Let’s explore how Striim’s ‘Read Once, Write Everywhere’ CDC pattern is revolutionizing how businesses handle data.

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The Role of Data Products in Maximizing ROI from AI Initiatives

The Modern Data Company

The post The Role of Data Products in Maximizing ROI from AI Initiatives appeared first on TheModernDataCompany.

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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

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Data Provenance vs. Data Lineage: What’s the Difference?

Monte Carlo

What’s something you never want your data to be? Mysterious. The best starting place to make sure you really know your data is, well, your data’s starting place – wherever that may be. For data teams, it’s essential to know your data from the source throughout its entire lifecycle. But, as data moves and is transformed through the pipeline, it can become increasingly complex to trace its journey.

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Data Provenance vs. Data Lineage: What’s the Difference?

Monte Carlo

What’s something you never want your data to be? Mysterious. The best starting place to make sure you really know your data is, well, your data’s starting place – wherever that may be. For data teams, it’s essential to know your data from the source throughout its entire lifecycle. But, as data moves and is transformed through the pipeline, it can become increasingly complex to trace its journey.