Sat.Aug 31, 2024 - Fri.Sep 06, 2024

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What are the Key Parts of Data Engineering?

Start Data Engineering

1. Introduction 2. Key parts of data systems: 2.1. Requirements 2.2. Data flow design 2.3. Orchestrator and scheduler 2.4. Data processing design 2.5. Code organization 2.6. Data storage design 2.7. Monitoring & Alerting 2.9. Infrastructure 3. Conclusion 1. Introduction If you are trying to break into (or land a new) data engineering job, you will inevitably encounter a slew of data engineering tools.

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Real-time Analytics Vs Stream Processing – What Is The Difference?

Seattle Data Guy

One of the holy grails that many data teams seem to chase is real-time data analytics. After all, if you can have real-time analytics, you can make better decisions faster. However, there often is a conflation between real-time data analytics and stream processing. These are two different concepts that are crucial to understanding how to… Read more The post Real-time Analytics Vs Stream Processing – What Is The Difference?

Process 130
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Streaming Postgres data to Databricks Delta Lake in Unity Catalog

Confessions of a Data Guy

Over the many years I’ve been pounding my keyboard … Perl, PHP, Python, C#, Rust … whatever … I, like most programmers, built up a certain disdain for what is called Low Code / No Code solutions. In my rush to worship at the feet of the code we create, I failed, in the beginning, […] The post Streaming Postgres data to Databricks Delta Lake in Unity Catalog appeared first on Confessions of a Data Guy.

Python 100
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10 Built-In Python Modules Every Data Engineer Should Know

KDnuggets

Interested in data engineering? Check out this round-up of built-in Python modules that'll come in handy for data engineering tasks.

Python 137
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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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Databricks announces significant improvements to the built-in LLM judges in Agent Evaluation

databricks

An improved answer-correctness judge in Agent Evaluation Agent Evaluation enables Databricks customers to define, measure, and understand how to improve the quality of.

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Read Meta’s 2024 Sustainability Report

Engineering at Meta

We are working in partnership with others to scale inclusive solutions that support the transition to a zero-carbon economy and help create a healthier planet for all.

More Trending

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Python Files within Snowflake Python Procedures

Cloudyard

Read Time: 1 Minute, 36 Second Snowflake’s support for Python stored procedures allows data engineers and scientists to leverage Python’s vast ecosystem directly within Snowflake. This capability enables advanced analytics, custom data processing, and seamless integration of Python libraries. One particularly powerful feature is the ability to import and use Python files (.py) directly within a Snowflake stored procedure, which promotes code modularity, reusability, and better organi

Python 96
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Revolutionizing Insight into Heavy Equipment Maintenance with GenAI

databricks

Maintaining heavy equipment assets, such as oil rigs, agricultural combines, or fleets of vehicles, poses an extremely complex challenge for global companies. These.

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Using FastAPI for Building ML-Powered Web Apps

KDnuggets

A beginner tutorial on building a simple web application for machine learning model inference using FastAPI and Jinja2 templates.

Building 106
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How Producers Work: Kafka Producer and Consumer Internals, Part 1

Confluent

Dive into Kafka internals with a four-part series examining client requests and brokers. Part 1 covers what a producer does to prepare raw event data for the broker.

Kafka 92
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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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Comprehensive Guide to Modern Data Warehouse in 2024

Hevo

A data warehouse is a centralized system that stores, integrates, and analyzes large volumes of structured data from various sources. It is predicted that more than 200 zettabytes of data will be stored in the global cloud by 2025.

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Enhanced Workflows UI reduces debugging time and boosts productivity

databricks

Data teams spend way too much time troubleshooting issues, applying patches, and restarting failed workloads. It's not uncommon for engineers to spend their.

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How to Compute the Cross-Correlation Between Two NumPy Arrays

KDnuggets

Let's see how to perform cross-correlation in NumPy, a method for measuring the similarity or relationship between two sequences of data as one is shifted in relation to the other.

Data 83
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Data Engineering Weekly #187

Data Engineering Weekly

Try Fully Managed Apache Airflow for FREE Run Airflow without the hassle and management complexity. Take Astro (the fully managed Airflow solution) for a test drive today and unlock a suite of features designed to simplify, optimize, and scale your data pipelines. For a limited time, new sign-ups will receive a complimentary Airflow Fundamentals Certification exam (normally $150).

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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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Best Practices for Effective Data Retention: A How to Guide

Precisely

How compliant is your organization with the GDPR (General Data Protection Regulation) requirements that keep personal data only as long as needed for the purpose it was collected? How easily could you prove your compliance if audited? GDPR states that personal data must not be kept longer than the purpose for which it was collected and processed.

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Cost savings on serverless compute for Notebooks, Jobs, and Pipelines

databricks

We recently announced the General Availability of our serverless compute offerings for Notebooks, Jobs, and Pipelines. Serverless compute provides rapid workload startup, automatic.

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I Took Udacity’s Free A/B Testing Course by Google: Here’s What I Learned

KDnuggets

A beginner's guide to A/B testing by FAANG data scientists.

Data 110
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Let Flink Cook: Mastering Real-Time Retrieval-Augmented Generation (RAG) with Flink

Confluent

How to use Flink AI model inference with familiar SQL syntax to work directly with LLMs and vector databases for your generative AI use cases.

SQL 69
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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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Precisely Customers Bring SAP Success Stories to Automate User Group

Precisely

HP Hood, Johnson & Johnson Vision, Loparex, Pactiv Evergreen, South Florida Water Management District, and Refresco share efficiencies and insights gained with Precisely Precisely hosted events during SAP Sapphire week in Orlando, FL – including an Automate User Group meeting, or “Inspiration Day.” These quarterly events bring Precisely Automate customers together to share knowledge, insights, and real-world results.

Finance 62
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The short guide to understanding data intelligence

databricks

Terms like “data governance,” “Generative AI” and “large language models” are becoming commonplace in the workplace. But for business leaders, it takes more.

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Using FLUX.1 Locally

KDnuggets

Learn how to install Stable Diffusion WebUI Forge easily and set up the FLUX.1 [dev] model for local use on a laptop.

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Use response caching as a shortcut for servers

ArcGIS

Learn more about how to use response caching for hosted feature services in ArcGIS Enterprise.

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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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Precisely Women in Technology: Meet Mahima

Precisely

According to the Women in Tech Network , women make up about 35 percent of the tech workforce. While this number has grown over the years, it still indicates that technology is a male-dominated industry. Precisely is committed to creating a supportive environment for women to build their careers so that this number can continue growing. As a result, the Precisely Women in Technology (PWIT) network was developed.

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Driving into the future of electric transportation

databricks

Rivian chose to modernize its data infrastructure on the Databricks Data Intelligence Platform, giving it the ability to unify all of its data into a common view for downstream analytics and machine learning.

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An Introduction to Explainable AI (XAI)

KDnuggets

Explainable AI (XAI) makes it easier to understand how AI decisions are made. This introduction explains what XAI is and why it matters.

IT 76
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Batch And Streaming Demystified For Unification

Towards Data Science

Understand how batch can be considered a subset of streaming and why data engineering should simplify its usage significantly Continue reading on Towards Data Science »

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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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Podcast 17 – Amerley Ampofo, MTN, Ghana; The key to good leadership is through emotional intelligence.

ArcGIS

Amerley Ampofo with MTN Ghana provides incredible insight into her geospatial story, the telco world, and her thoughts about leadership.

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Community Tips for the Databricks Data Intelligence Platform

databricks

Within the Databricks Community, there is a technical blog where community members share best practices, tutorials and insights on data analytics, data engineering.

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Scalability Challenges & Strategies in Data Science

KDnuggets

Scaling data science projects can be difficult. This article explores challenges and strategies for managing large-scale data.

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Deploying AI to Enhance Data Quality and Reliability

Ascend.io

AI-driven data quality workflows deploy machine learning to automate data cleansing, detect anomalies, and validate data. Integrating AI into data workflows ensures reliable data and enables smarter business decisions. Data quality is the backbone of successful data engineering projects. Poor data quality can lead to costly errors, misinformed decisions, and ultimately, a significant economic impact.

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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.