Thu.Aug 22, 2024

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DAIS 2024: Unit tests - configuration and declaration

Waitingforcode

Code organization and assertions flow are both important but even them, they can't guarantee your colleagues' adherence to the unit tests. There are other user-facing attributes to consider as well.

Coding 130
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Pip Install YOU: A Beginner’s Guide to Creating Your Python Library

KDnuggets

Have you ever wanted to create your library in Python? Well, it’s achievable and surprisingly quite easy!

Python 137
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What's new in Workflows?

databricks

Databricks Workflows is the cornerstone of the Databricks Data Intelligence Platform, serving as the orchestration engine that powers critical data and AI workloads.

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Top 5 Free Machine Learning Courses to Level Up Your Skills

KDnuggets

The article highlights five top free machine learning courses to enhance your skills.

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Driving Responsible Innovation: How to Navigate AI Governance & Data Privacy

Speaker: Aindra Misra, Senior Manager, Product Management (Data, ML, and Cloud Infrastructure) at BILL

Join us for an insightful webinar that explores the critical intersection of data privacy and AI governance. In today’s rapidly evolving tech landscape, building robust governance frameworks is essential to fostering innovation while staying compliant with regulations. Our expert speaker, Aindra Misra, will guide you through best practices for ensuring data protection while leveraging AI capabilities.

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Raise Your Tests: Testing Functional Kotlin with Arrow and Raise

Rock the JVM

By Riccardo Cardin At Rock the JVM, we deeply understand the power of the Kotlin Arrow library and the Raise DSL, and we’ve previously shared our insights in our article on Functional Error Handling in Kotlin, Part 3: The Raise DSL. Now, we’re ready to introduce the crucial topic of testing applications that use the Raise DSL. To fully grasp the concepts we’ll be discussing, it’s essential to have a solid understanding of Kotlin, Arrow library, and the Raise DSL.

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Inside the hardware and co-design of MTIA

Engineering at Meta

In this talk from AI Infra @ Scale 2024 , Joel Colburn, a software engineer at Meta, technical lead Junqiang Lan, and software engineer Jack Montgomery discuss the second generation of MTIA , Meta’s in-house training and inference accelerator. They cover the co-design process behind building the second generation of Meta’s first-ever custom silicon for AI workloads, including the PyTorch software ecosystem, and the model architectures for Meta’s key applications.

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Unraveling the Threads: Data Fabric vs Data Mesh for Modern Enterprises

Precisely

Key Takeaways Data fabric and data mesh are modern data management architectures that allow organizations to more easily understand, create, and manage data for more timely, accurate, consistent, and contextual data analytics and operations. Both architectures tackle significant data management challenges such as integrating disparate data sources, improving data accessibility, automating management processes, and ensuring data governance and security.

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4 Ways Gen AI Can Help Brand Advertisers and Ad Agencies

Snowflake

Uncertainty is the new norm for today’s brand advertisers and advertising agencies. Google has once again changed its stance on third-party cookies, keeping them for at least the time being. With the future of cookies still uncertain, many advertisers have already been preparing to use alternative targeting strategies, such as first-party data and contextual targeting.

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Looking Ahead: The Future of Data Preparation for Generative AI

Data Science Blog: Data Engineering

Sponsored Post Generative AI is a significant part of the technology landscape. The effectiveness of generative AI is linked to the data it uses. Similar to how a chef needs fresh ingredients to prepare a meal, generative AI needs well-prepared, clean data to produce outputs. Businesses need to understand the trends in data preparation to adapt and succeed.

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AWS Glue vs Informatica: A Comprehensive Comparison

Hevo

Businesses today rely heavily on efficient data integration and ETL (Extract, Transform, Load) tools to manage and analyze their data. Choosing the right tool can significantly impact an organization’s ability to process and utilize data effectively. AWS Glue and Informatica are prominent players offering unique features and benefits.

AWS 52
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Launching LLM-Based Products: From Concept to Cash in 90 Days

Speaker: Christophe Louvion, Chief Product & Technology Officer of NRC Health and Tony Karrer, CTO at Aggregage

Christophe Louvion, Chief Product & Technology Officer of NRC Health, is here to take us through how he guided his company's recent experience of getting from concept to launch and sales of products within 90 days. In this exclusive webinar, Christophe will cover key aspects of his journey, including: LLM Development & Quick Wins 🤖 Understand how LLMs differ from traditional software, identifying opportunities for rapid development and deployment.

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An In-Depth Guide to Real-Time Analytics

Striim

It’s increasingly necessary for businesses to make immediate decisions. More importantly, it’s crucial these decisions are backed up with data. That’s where real- time analytics can help. Whether you’re a SaaS company looking to release a new feature quickly, or own a retail shop trying to better manage inventory, these insights can empower businesses to assess and act on data quickly to make better decisions.

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Airbyte vs Airflow: Which Tool Should You Choose in 2024?

Hevo

In the world of data engineering, the choice of tools can significantly impact the efficiency and scalability of your data workflows. Two popular options are Airbyte and Apache Airflow. Both tools serve distinct purposes but often get compared due to their roles in managing data pipelines.

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Data Quality Circles: The Key to Elevating Data and Analytics Team Performance

DataKitchen

Data Quality Circles: The Key to Elevating Data and Analytics Team Performance Introduction: The Pursuit of Quality in Data and Analytic Teams. According to a study by HFS Research, 75 percent of business executives do not have a high level of trust in their data. High-quality data underpins the reliability of insights, models’ accuracy, and decision-making processes’ efficacy.

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Prompt Engineering Salary: A Comprehensive Guide

Edureka

Prompt engineering has become one of the most important areas in artificial intelligence, with companies seeking experienced professionals. This article will provide extensive information on prompt engineering salary, which has been rapidly changing in the recent past; the elements affecting salaries; the average wage and compensation; various career advancements; the influence of certifications on salaries; and the likely trends of salary in the near future.

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How To Speak The Language Of Financial Success In Product Management

Speaker: Jamie Bernard

Success in product management goes beyond delivering great features - it’s about achieving measurable financial outcomes that resonate across the organization. By connecting your product’s journey with the company’s financial success, you’ll ensure that every feature, release, and innovation contributes to the bottom line, driving both customer satisfaction and business growth.

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Databricks Data Warehouse Brickbuilder Migration Solutions Help Businesses Democratize Data and Analytics

databricks

Today, we're excited to announce the launch of Data Warehouse Brickbuilder Migration Solutions. This is an expansion to the Brickbuilder Program , which.

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Top Trends Shaping the Future of Business Intelligence

RandomTrees

Future Trends in Business Intelligence Business intelligence (BI) continues to evolve rapidly, driven by technological advancements and changing business needs. Here are some of the key trends currently transforming the BI landscape: 1. Artificial Intelligence and Machine Learning Integration AI and machine learning are becoming increasingly central to BI solutions.