Fri.Dec 08, 2023

article thumbnail

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.

article thumbnail

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.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

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 135
article thumbnail

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 »

SQL 82
article thumbnail

Navigating the Future: Generative AI, Application Analytics, and Data

Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

article thumbnail

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.

104
104
article thumbnail

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.

More Trending

article thumbnail

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.

article thumbnail

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.

Coding 89
article thumbnail

Change Data Capture Best Practices with a ‘Read Once, Stream Anywhere’ Pattern in Striim

Striim

Note: To follow best practices guide, you must have the Persisted Streams add-on in Striim Cloud or Striim Platform. Introduction Change Data Capture (CDC) is a critical methodology, particularly in scenarios demanding real-time data integration and analytics. CDC is a technique designed to efficiently capture and track changes made in a source database, thereby enabling real-time data synchronization and streamlining the process of updating data warehouses, data lakes, or other systems.

Kafka 64
article thumbnail

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.

article thumbnail

Get Better Network Graphs & Save Analysts Time

Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

article thumbnail

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.

article thumbnail

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.