Sat.Sep 14, 2024 - Fri.Sep 20, 2024

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How to build a data project with step-by-step instructions

Start Data Engineering

1. Introduction 2. Setup 3. Parts of data engineering 3.1. Requirements 3.1.1. Understand input datasets available 3.1.2. Define what the output dataset will look like 3.1.3. Define SLAs so stakeholders know what to expect 3.1.4. Define checks to ensure the output dataset is usable 3.2. Identify what tool to use to process data 3.3. Data flow architecture 3.

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Paying down tech debt: further learnings

The Pragmatic Engineer

This is a follow-up to the article Paying down tech debt , written by industry veteran Lou Franco. Lou has been in the software business for over 30 years as an engineer, EM, and executive. He’s also worked at four startups and the companies that later acquired them; most recently Atlassian as a Principal Engineer on the Trello iOS app. Later this year, he’s publishing a book on tech debt.

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How To Modernize Your Data Strategy And Infrastructure For 2025

Seattle Data Guy

We are still in the early days of data and the value it can add to companies. You’ll read plenty of statistics about how much value data can drive and how far behind companies that aren’t using data are. And as a data consultant, I have helped companies find that value in their data. It… Read more The post How To Modernize Your Data Strategy And Infrastructure For 2025 appeared first on Seattle Data Guy.

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Data Modeling in the Brave New Lakehouse World

Confessions of a Data Guy

It is a Brave New World out there these days. The new tools and features come out faster than your mom on Sunday morning getting you ready for church. The same goes for the context and advice being produced on a myriad of platforms, the ole’ Like and Subscribe, and all that bit. It does […] The post Data Modeling in the Brave New Lakehouse World appeared first on Confessions of a Data Guy.

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Improving the Accuracy of Generative AI Systems: A Structured Approach

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

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Fine-tuning Llama 3.1 with Long Sequences

databricks

Mosaic AI Model Training now supports fine-tuning up to 131K context length for Llama 3.1 models. More efficient training at long sequence lengths is made possible by several optimizations highlighted in this post.

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Partial Functions in Python: A Guide for Developers

KDnuggets

In Python, functions often require multiple arguments, and you may find yourself repeatedly passing the same values for certain parameters. This is where partial functions can help. Python’s built-in functools module allows you to create partial functions.

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More Trending

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Introducing Confluent’s OEM Program: Deliver Data Streaming Faster and Unlock Revenue Growth

Confluent

Bring data streaming to your product or service quickly and confidently with unified Apache Kafka® and Apache Flink®, backed by the original creators of Kafka.

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Unleash Your Innovation: Announcing the Databricks Generative AI Startup Challenge with Over $1 Million in Credits, Prizes, and Potential Venture Funding

databricks

The Databricks Generative AI Startup Challenge offers $1M+ in prizes for innovative startups building Generative AI use cases on Databricks. Apply by November 1, 2024!

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How to Import Data into BigQuery

KDnuggets

Data come from everywhere, and the number of origins, sources, and formats under which valuable data may appear underscores the need for database management tools capable of loading data from multiple sources. This tutorial illustrates how to load datasets from different formats and sources into Google BigQuery. All the prerequisites we need are having registered.

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Cloudera Evaluates Integrated Data and AI Exchange Business Line to Optimize Data-Driven Generative AI Use Cases

Cloudera

According to recent survey data from Cloudera, 88% of companies are already utilizing AI for the tasks of enhancing efficiency in IT processes, improving customer support with chatbots, and leveraging analytics for better decision-making. More and more enterprises are leveraging pre-trained models for various applications, from natural language processing to computer vision.

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The Ultimate Guide To Data-Driven Construction: Optimize Projects, Reduce Risks, & Boost Innovation

Speaker: Donna Laquidara-Carr, PhD, LEED AP, Industry Insights Research Director at Dodge Construction Network

In today’s construction market, owners, construction managers, and contractors must navigate increasing challenges, from cost management to project delays. Fortunately, digital tools now offer valuable insights to help mitigate these risks. However, the sheer volume of tools and the complexity of leveraging their data effectively can be daunting. That’s where data-driven construction comes in.

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Snowflake Acquires Night Shift Development, Inc. to Accelerate Growth in US Public Sector

Snowflake

Data is increasingly becoming critical for the public sector — from guiding decisions in higher education to enhancing citizen services and streamlining government operations. Government agencies are overwhelmed with data, whether it be structured, like incident logs, or unstructured, like satellite images. Harnessing the vast amount of data can become a burden for any organization, yet the insights have the potential to significantly improve quality of life and strengthen national security.

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Establish your Generative AI expertise with the latest Databricks certification

databricks

The value of Generative AI, the deepened investment Databricks has made in the space, and how customers have benefited from the certification.

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How to Visualize Data with ggplot2 in R

KDnuggets

ggplot2 is a tool in R for making charts. You can create charts with dots, bars, or lines. You can also add layers to show more details. This article will help you learn how to use ggplot2 to create visualizations. Getting started with ggplot2 Before using ggplot2, you need to install it and.

Data 104
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Ensuring Even Ad Spend on the Zalando Homepage: How Our New Bidding Algorithm Maximizes Value for Advertisers and Shoppers

Zalando Engineering

Introduction Zalando Marketing Services (ZMS) is Zalando's advertising platform. It helps brands create and manage campaigns on Zalando, increasing their visibility and improving performance at every stage of the marketing funnel, from awareness to purchase, within the Zalando marketplace. At ZMS, we're constantly innovating to optimize the advertising experience on Zalando homepage.

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Building Your BI Strategy: How to Choose a Solution That Scales and Delivers

Speaker: Evelyn Chou

Choosing the right business intelligence (BI) platform can feel like navigating a maze of features, promises, and technical jargon. With so many options available, how can you ensure you’re making the right decision for your organization’s unique needs? 🤔 This webinar brings together expert insights to break down the complexities of BI solution vetting.

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9 Ways AI Can Uplevel Your Business Right Now

Snowflake

As the frenzied hype around generative AI cools off and as we get into the year of ideation, earlier adopters of AI are starting to see the results of initial experimentation. And these conversations are increasingly shifting to a more problem-oriented mentality. A lot of people were understandably swept up in the excitement of all that AI can do, only to find that some use cases were too risky or that those problems could be solved with traditional methods that were less costly.

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Inference-Friendly Models with MixAttention

databricks

Transformer models, the backbone of modern language AI, rely on the attention mechanism to process context when generating output. During inference, the attention.

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How to Perform Data Aggregation Over Time Series Data with Pandas

KDnuggets

Image by Editor | Ideogram Let’s learn how to perform time series data aggregation in Pandas. Preparation We would need the Pandas and Numpy packages installed, so we can install them using the following code: pip install pandas numpy With the packages installed, let’s jump into the article. Time Series.

Data 106
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AI Success – Powered by Data Governance and Quality

Precisely

Key Takeaways: Data integrity is essential for AI success and reliability – helping you prevent harmful biases and inaccuracies in AI models. Robust data governance for AI ensures data privacy, compliance, and ethical AI use. Proactive data quality measures are critical, especially in AI applications. Using AI systems to analyze and improve data quality both benefits and contributes to the generation of high-quality data.

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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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Run pandas on 1TB+ Enterprise Data Directly in Snowflake

Snowflake

As one of the most widely used libraries in the Python ecosystem, pandas helps developers analyze, load and transform data across data science, data engineering and machine learning. The flexibility and ease of use of the pandas API have driven rapid growth in popularity, with pandas being used by one in every five developers , according to the StackOverflow 2024 Developer Survey.

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Unifying Parameters Across Databricks

databricks

Today, we are excited to announce the support for named parameter markers in the SQL editor. This feature allows you to write parameterized.

SQL 103
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VoiceChat with Your LLMs using AlwaysReddy

KDnuggets

Rapid development is happening around us, and one of the most interesting aspects of this evolution is artificial intelligence's ability to communicate through natural language with humans. Suppose you want to communicate with some LLM running on your computer without switching between applications or windows, just by using a voice hotkey. This is exactly what.

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Content Creation Copilot - AI-assisted product onboarding

Zalando Engineering

Introduction At Zalando, we strive to discover valuable use cases that benefit our customers and stakeholders by using AI-based approaches. Our team's primary mission is to enable content creation teams to produce and integrate best-in-class content for our customers in the most efficient way. We are building tools that streamline the content creation journey - from photo shooting, copyrighting to submission articles in Zalando shop in compliant way.

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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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Data Quality Power Moves: Scorecards & Data Checks for Organizational Impact

DataKitchen

A DataOps Approach to Data Quality The Growing Complexity of Data Quality Data quality issues are widespread, affecting organizations across industries, from manufacturing to healthcare and financial services. According to DataKitchen’s 2024 market research, conducted with over three dozen data quality leaders, the complexity of data quality problems stems from the diverse nature of data sources, the increasing scale of data, and the fragmented nature of data systems.

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Security best practices for the Databricks Data Intelligence Platform

databricks

At Databricks, we know that data is one of your most valuable assets. Our product and security teams work together to deliver an enterprise-grade Data Intelligence Platform that enables you to defend against security risks and meet your compliance obligations. In this blog, we'll explain how you can leverage our platform's security features to establish a robust defense-in-depth posture that protects your data and AI assets from risks.

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5 YouTube Channels to Master LLMs

KDnuggets

Image by Author If you’re in the tech industry (or are attempting to transition into the field), LLMs are a must-learn. Companies have started integrating language models into their workflows to improve efficiencies and cut costs. Due to this, there have been a number of new AI job openings. New roles have begun to.

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Key Data Integrity Trends and Insights for Your 2025 Strategy

Precisely

Businesses around the world are facing major challenges due to higher manufacturing costs, disruptive new technologies like artificial intelligence (AI), and tougher global competition. This means it’s more important than ever to make data-driven decisions, cut costs, and improve efficiency. But this is all easier said than done, as evidenced by key findings from this year’s 2025 Outlook: Data Integrity Trends and Insights report, published in partnership between Precisely and the Center for App

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What Is Entity Resolution? How It Works & Why It Matters

Entity Resolution Sometimes referred to as data matching or fuzzy matching, entity resolution, is critical for data quality, analytics, graph visualization and AI. Learn what entity resolution is, why it matters, how it works and its benefits. Advanced entity resolution using AI is crucial because it efficiently and easily solves many of today’s data quality and analytics problems.

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Streamlining Financial Market Intelligence with Time-Series Innovations

Snowflake

Why now is the time for data leaders in financial services to address the challenges of tick data analysis — and how Snowflake can help The financial services industry has been facing plenty of challenges lately. The rising cost of capital means leaders need to be smart about finding places to reduce total cost of ownership and scale technology. The number of market and technology regulations around data, infrastructure and reporting, like DORA and GDPR , can be overwhelming; complying to them m

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Announcing GA of AI Model Sharing

databricks

Special thanks to Daniel Benito (CTO, Bitext), Antonio Valderrabanos(CEO, Bitext), Chen Wang (Lead Solution Architect, AI21 Labs), Robbin Jang (Alliance Manager, AI21 Labs).

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Deep Learning Approaches in Medical Image Segmentation

KDnuggets

Medical imaging has been revolutionized by the adoption of deep learning techniques. The use of this branch of machine learning has ushered in a new era of precision and efficiency in medical image segmentation, a central analytical process in modern healthcare diagnostics and treatment planning. By harnessing neural networks, deep learning algorithms are able.

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Build, Manage, and Monitor Data Streaming Applications, All Within Your Favorite IDE

Confluent

Confluent for VS Code streamlines workflows, accelerates development cycles, and enhances real-time data processing, all within a unified environment.

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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.