Sat.Aug 20, 2022 - Fri.Aug 26, 2022

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7 Techniques to Handle Imbalanced Data

KDnuggets

This blog post introduces seven techniques that are commonly applied in domains like intrusion detection or real-time bidding, because the datasets are often extremely imbalanced.

Datasets 160
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Data Lake / Lakehouse Guide: Powered by Data Lake Table Formats (Delta Lake, Iceberg, Hudi)

Simon Späti

Image by Rachel Claire on Pexels Ever wanted or been asked to build an open-source Data Lake offloading data for analytics? Asked yourself what components and features would that include. Didn’t know the difference between a Data Lakehouse and a Data Warehouse? Or you just wanted to govern your hundreds to thousands of files and have more database-like features but don’t know how?

Data Lake 130
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An Exploration Of The Expectations, Ecosystem, and Realities Of Real-Time Data Applications

Data Engineering Podcast

Summary Data has permeated every aspect of our lives and the products that we interact with. As a result, end users and customers have come to expect interactions and updates with services and analytics to be fast and up to date. In this episode Shruti Bhat gives her view on the state of the ecosystem for real-time data and the work that she and her team at Rockset is doing to make it easier for engineers to build those experiences.

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Building Custom Runtimes with Editors in Cloudera Machine Learning

Cloudera

Cloudera Machine Learning (CML) is a cloud-native and hybrid-friendly machine learning platform. It unifies self-service data science and data engineering in a single, portable service as part of an enterprise data cloud for multi-function analytics on data anywhere. CML empowers organizations to build and deploy machine learning and AI capabilities for business at scale, efficiently and securely, anywhere they want.

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Apache Airflow® Best Practices for ETL and ELT Pipelines

Whether you’re creating complex dashboards or fine-tuning large language models, your data must be extracted, transformed, and loaded. ETL and ELT pipelines form the foundation of any data product, and Airflow is the open-source data orchestrator specifically designed for moving and transforming data in ETL and ELT pipelines. This eBook covers: An overview of ETL vs.

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How to Package and Distribute Machine Learning Models with MLFlow

KDnuggets

MLFlow is a tool to manage the end-to-end lifecycle of a Machine Learning model. Likewise, the installation and configuration of an MLFlow service is addressed and examples are added on how to generate and share projects with MLFlow in Layer.

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Reinforcement Learning for Budget Constrained Recommendations

Netflix Tech

by Ehtsham Elahi with James McInerney , Nathan Kallus , Dario Garcia Garcia and Justin Basilico Introduction This writeup is about using reinforcement learning to construct an optimal list of recommendations when the user has a finite time budget to make a decision from the list of recommendations. Working within the time budget introduces an extra resource constraint for the recommender system.

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G2 names Confluent the Event Stream Processing Industry Leader

Confluent

G2 named Confluent the the event stream processing industry leader for top-rated performance, reliability, ease of use, integration APIs, data modeling features, and more.

Process 64
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Customize Your Data Frame Column Names in Python

KDnuggets

This tutorial will explore four scenarios in which you can apply different transformations to all DataFrame columns.

Python 148
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Case Study: iYOTAH Brings Real-Time IoT Analytics to Dairy Farming with Its AgTech SaaS Platform

Rockset

The American dairy industry is a mighty one. America’s 32,000 dairy farmers not only produce the most milk in the world , they are also the most efficient, producing 23 thousand pounds of milk per cow per year — almost 20 times the weight of an average (1,200 pound) dairy cow. For their genetically strong herds, healthy cows, high yields, even increasingly green operations , farmers can credit both agricultural science as well as data science.

IT 52
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5 Steps to Operationalizing Data Observability with Monte Carlo?

Monte Carlo

“How do we scale data observability with Monte Carlo?” I’ve heard this from hundreds of new customers. They’re excited about all that data observability can do for them, but like with any new software, they want prescriptive guidance. “In the ‘Crawl → Walk → Run’ of software adoption, what’s the quickest way for my team to start crawling?” If you’re a data team of 5-15 engineers or analysts, I recommend building healthy data observability muscles using our end-to-end, out-of-the-box monitors , a

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Apache Airflow®: The Ultimate Guide to DAG Writing

Speaker: Tamara Fingerlin, Developer Advocate

In this new webinar, Tamara Fingerlin, Developer Advocate, will walk you through many Airflow best practices and advanced features that can help you make your pipelines more manageable, adaptive, and robust. She'll focus on how to write best-in-class Airflow DAGs using the latest Airflow features like dynamic task mapping and data-driven scheduling!

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Confluent in India: Cultivating an Innovative Organization Where People Thrive

Confluent

The VP of Engineering at Confluent India shares how the team builds innovative, modern data solutions while instilling a humble, open work culture where employees thrive.

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Simplify Data Processing with Pandas Pipeline

KDnuggets

Write a single line of code to clean and process the data for analytics and machine learning tasks.

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A Day in the Life of a Palantir Incident Management Engineer

Palantir

The Palantir Incident Response team addresses the highest-priority issues across our platforms — Foundry, Gotham, and Apollo — ensuring they continue to support mission-critical work around the world. Essentially, the team’s core mandate is to respond when things go wrong. More broadly, Incident Response focuses on business continuity while adapting to an ever-expanding feature set as development teams across Palantir continuously add new capabilities and enhancements.

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Is it Finally Time for Change in the Insurance Industry?

Teradata

Is insurance immune from the surge in data-driven applications in other industries? Of course not, but why has there been such a slow uptake in data resources?

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Optimizing The Modern Developer Experience with Coder

Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

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Getting Started with Confluent Cloud Networking

Confluent

Full introduction to Confluent Cloud networking: security, setup and configuration, cost considerations, and which networking option to choose for your architecture.

Cloud 59
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Free Python Project Coding Course

KDnuggets

Learn Python by doing Python. Check out this free project-based course to quickly learn how to program in the high-demand language.

Python 144
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What are Data Types in R?

U-Next

Introduction. R Programming Language: What Is It? R is available as an open language of programming for statistical computing and data analytics, and R often has a command-line API. R is accessible on popular operating systems, including Pc, Linux, and macintosh. The newest cutting-edge technology is the R programming language. The R Research Core Group is presently carrying out its research.

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Wolt loves open-source software

Wolt

Here at Wolt we truly love open-source software. We’re a fast-growing company, building the rocket ship while riding it to allow our business to scale. This wouldn’t be possible without standing on the shoulders of giant open-source projects. Almost our whole tech stack is based on open-source software, most notably on the data engineering side.

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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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Daniel Kahneman and Nate Silver to Headline IMPACT: The Data Observability Summit

Monte Carlo

What do Daniel Kahneman, the Nobel Prize-winning psychologist, economist, and author of Thinking, Fast and Slow , and Nate Silver, founder and editor-in-chief of opinion poll analysis website FiveThirtyEight , have in common? Not only are they two of the most interesting voices in data, but they’re speaking at IMPACT: The Data Observability Summit , from October 25-26, 2022.

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Tuning Random Forest Hyperparameters

KDnuggets

Hyperparameter tuning is important for algorithms. It improves their overall performance of a machine learning model and is set before the learning process and happens outside of the model.

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An introduction to unit testing your dbt Packages

dbt Developer Hub

Editors note - this post assumes working knowledge of dbt Package development. For an introduction to dbt Packages check out So You Want to Build a dbt Package. It’s important to be able to test any dbt Project, but it’s even more important to make sure you have robust testing if you are developing a dbt Package. I love dbt Packages, because it makes it easy to extend dbt’s functionality and create reusable analytics resources.

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Tableau Tutorial

U-Next

Introduction. If the results of the assessment of the information are displayed in the form of information representation, all the outstanding purpose-oriented corporate judgments become simple to pursue. Additionally, having all statistics, infographics, graphs, etc., on one dashboard makes it easier to foresee insights. Tableau serves as a visual framework for business intelligence and analytics, assisting users in watching, observing, comprehending, and making choices with various data types.

BI 52
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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, Terrence Sheflin, and Mahyar Ghasemali

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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What is Data Fabric: Architecture, Principles, Advantages, and Ways to Implement

AltexSoft

The landscape of enterprise data is fragmented. According to Flexera’s 2022 State of the Cloud Report , 89 percent of respondents have a multi-cloud strategy with 80 percent having a hybrid cloud approach in place. Organizations have data stored in public and private clouds, as well as in various on-premises data repositories. How organizations embrace multi-cloud.

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Top Posts August 15-21: How to Perform Motion Detection Using Python

KDnuggets

How to Perform Motion Detection Using Python • The Complete Collection of Data Science Projects – Part 2 • Free AI for Beginners Course • Decision Tree Algorithm, Explained • What Does ETL Have to Do with Machine Learning?

Python 131
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Surrogate keys in dbt: Integers or hashes?

dbt Developer Hub

Those who have been building data warehouses for a long time have undoubtedly encountered the challenge of building surrogate keys on their data models. Having a column that uniquely represents each entity helps ensure your data model is complete, does not contain duplicates, and able to join across different data models in your warehouse. Sometimes, we are lucky enough to have data sources with these keys built right in — Shopify data synced via their API, for example, has easy-to-use keys on a

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Searching In Data Structure

U-Next

Introduction. The communications system is growing quickly in the modern world. To increase organizational productivity, organizations are turning digital. Datasets are growing increasingly complicated due to an increase in the volume of data produced on the web. Searching in Data Structure enables the efficient retrieval of individual elements from a collection, such as a specific record from a database.

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How to Drive Cost Savings, Efficiency Gains, and Sustainability Wins with MES

Speaker: Nikhil Joshi, Founder & President of Snic Solutions

Is your manufacturing operation reaching its efficiency potential? A Manufacturing Execution System (MES) could be the game-changer, helping you reduce waste, cut costs, and lower your carbon footprint. Join Nikhil Joshi, Founder & President of Snic Solutions, in this value-packed webinar as he breaks down how MES can drive operational excellence and sustainability.

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What Type of Data Warehouse Is Snowflake Data Platform? | Propel Data Analytics Blog

Propel Data

With Snowflake, it’s possible to build an enterprise data warehouse (EDW), an operational data store (ODS), or a team-specific data mart.

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How to Better Leverage Data Science for Business Growth

KDnuggets

Is data science for you? And if it is, how can you use it to grow your business?

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How to Build Data Products Your Company Will Actually Use

Monte Carlo

Across both public and private sectors, more organizations are adopting a “data-driven” mindset—or, at least, data-driven messaging. But in reality, most aren’t prepared for the reality of what it takes to truly make decisions based on data. Teams have to be aligned about what data is used and how decisions are made. Data has to be accessible and available to the right decision-makers at the right time.

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All About Machine Learning Cheat Sheet

U-Next

Introduction. Artificial Intelligence is indeed the science of Machine Learning. Making people aware of current Machine Learning models and developments and enabling them to comprehend original data is the main goal of Machine Learning cheat sheets. They will employ the information in Machine Learning models that individuals and organizations may use after they have a deeper knowledge of the raw and different data formats.

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The Cloud Development Environment Adoption Report

Cloud Development Environments (CDEs) are changing how software teams work by moving development to the cloud. Our Cloud Development Environment Adoption Report gathers insights from 223 developers and business leaders, uncovering key trends in CDE adoption. With 66% of large organizations already using CDEs, these platforms are quickly becoming essential to modern development practices.