August, 2023

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Top 5 questions Data Engineers should ask before joining a startup

Towards Data Science

Advice from a startup founder in the data space on how to find a startup that works for you Photo by Leeloo Thefirst from Pexels.com So you want to join a startup huh? I’m not talking about a fancy Series E startup that’s about to go IPO funded by a16z. I’m talking about a real startup, from seed to series B — where every day can feel like you’re either about to soar or crash and burn — and there’s little in between.

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Why Is Data Modeling So Challenging – How To Data Model For Analytics

Seattle Data Guy

Learning about how to data models from basic star schemas on the internet is like learning data science using the IRIS data set. It works great as a toy example. But it doesn’t match real life at all. Data modeling in real life requires you fully understand the data sources and your business use cases.… Read more The post Why Is Data Modeling So Challenging – How To Data Model For Analytics appeared first on Seattle Data Guy.

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MSSQL vs MySQL: Comparing Powerhouses of Databases

Analytics Vidhya

Introduction In the bustling arena of database management systems, two heavyweight contenders emerge, each carrying its arsenal of features and capabilities. In one corner, we have the suave and sophisticated Microsoft SQL Server (MSSQL), donned in the elegance of enterprise-level prowess. And in the other corner the scrappy and open-source MySQL, armed with its community-driven […] The post MSSQL vs MySQL: Comparing Powerhouses of Databases appeared first on Analytics Vidhya.

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How Games Typically Get Built

The Pragmatic Engineer

👋 Hi, this is Gergely with a bonus, free issue of the Pragmatic Engineer Newsletter. In every issue, I cover topics related to Big Tech and startups through the lens of engineering managers and senior engineers. In this article, we cover one out of for topics from the past newsletter issue Game Development Basics. To get the full issues, twice a week, subscribe here.

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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?

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Table file formats - commits: Delta Lake

Waitingforcode

One of the great features of modern table file formats is the ability to handle write conflicts. It wouldn't be possible without commits that are the topic of this new blog post.

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Building An Internal Database As A Service Platform At Cloudflare

Data Engineering Podcast

Summary Data persistence is one of the most challenging aspects of computer systems. In the era of the cloud most developers rely on hosted services to manage their databases, but what if you are a cloud service? In this episode Vignesh Ravichandran explains how his team at Cloudflare provides PostgreSQL as a service to their developers for low latency and high uptime services at global scale.

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The Burtch Works 2023 Data Science & AI Professionals Salary Report is Here!

KDnuggets

The Burtch Works 2023 Data Science & AI Professionals salary report is here, and includes insightful data such as hiring and marketplace trends, compensation changes over time, and salary data. Get your copy here.

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ELT vs ETL: Unveiling the Differences and Similarities

Analytics Vidhya

Introduction In today’s data-driven world, seamless data integration plays a crucial role in driving business decisions and innovation. Two prominent methodologies have emerged to facilitate this process: Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT). In this article, we will discuss ELT vs ETL, comparing their characteristics, benefits, and suitability for various use cases. […] The post ELT vs ETL: Unveiling the Differences and Similarities appeared first on Ana

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A senior engineer/EM job search story

The Pragmatic Engineer

👋 Hi, this is Gergely with a bonus, free issue of the Pragmatic Engineer Newsletter. In every issue, I cover topics related to Big Tech and startups through the lens of engineering managers and senior engineers. In this article, we cover one out of five topics from today’s subscriber-only The Pulse issue. To get full issues twice a week, subscribe here.

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Table file formats - isolation levels: Delta Lake

Waitingforcode

If Delta Lake implemented the commits only, I could stop exploring this transactional part after the previous article. But as for RDBMS, Delta Lake implements other ACID-related concepts. One of these are isolation levels.

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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.

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Activating Data from the Lakehouse: Databricks Ventures Invests in Hightouch

databricks

It’s no secret that modern organizations are doubling down on their investments in data - investments that uncover deep customer insights that provide a.

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Missing Data Demystified: The Absolute Primer for Data Scientists

Towards Data Science

Data Quality Chronicles Missing data, missing mechanisms, and missing data profiling Missing Data prevents data scientists to see the entire story the data has to tell. Sometimes, even the smallest pieces of information can provide a completely unique view of the world. Photo by Ronan Furuta on Unsplash. Earlier this year, I started a piece on several data quality issues (or characteristics) that heavily compromise our machine learning models.

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KDnuggets News, August 30: 7 Projects Built with Generative AI • Beyond Numpy and Pandas: Lesser-Known Python Libraries

KDnuggets

7 Projects Built with Generative AI • Beyond Numpy and Pandas: Unlocking the Potential of Lesser-Known Python Libraries • 5 Ways You Can Use ChatGPT’s Code Interpreter For Data Science • GPT-4: 8 Models in One; The Secret is Out

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Snowflake and Instacart: The Facts

Snowflake

In the past few days, the scope and trajectory of Instacart’s use of Snowflake has been misrepresented by some on social media. Snowflake has partnered closely with Instacart to scale up to meet the company’s massive demand growth, and then to optimize for efficiency. Optimizations are undertaken on a workload-by-workload basis, and have been extremely successful.

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Understanding User Needs and Satisfying Them

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

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Are reports of StackOverflow’s fall greatly exaggerated?

The Pragmatic Engineer

👋 Hi, this is Gergely with a bonus, free issue of the Pragmatic Engineer Newsletter. In every issue, I cover topics related to Big Tech and startups through the lens of engineering managers and senior engineers. In this article, we cover one out of five topics from today’s subscriber-only The Pulse issue. To get full issues twice a week, subscribe here.

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16+ fascinating Big data examples

InData Labs

The world is generating an unprecedented amount of data every second. From online transactions and social media interactions to sensor readings and scientific research, the sheer volume, velocity, and variety of data have given rise to the concept of “Big data.” This vast ocean of information holds immense potential, capable of revolutionizing industries, driving innovation, Запись 16+ fascinating Big data examples впервые появилась InData Labs.

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Organizing Generative AI Teams: 5 Lessons Learned From Data Science

Monte Carlo

You did it! After executive leadership vaguely promised stakeholders that new Gen AI features would be incorporated across the organization, your tiger team sprinted to produce a MVP that checks the box. Integrating that OpenAI API into your application wasn’t that difficult and it may even turn out to be useful. But now what happens? Tiger teams can’t sprint forever.

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Precisely Women in Technology: Meet Monica Di Martino

Precisely

With an increasing number of women joining IT, it’s becoming a more inclusive environment. Precisely is committed to building a more inclusive work environment, which is why there are ample opportunities for women in the organization. One of the company’s initiatives is the Precisely Women in Technology (PWIT) program, that was established to be a place for women to come together, support each other, offer guidance, and more.

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Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

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5 Skills All Marketing Analytics and Data Science Pros Need Today

KDnuggets

Join us at the MADS conference in Washington, D.C., from Sept. 26 to 28, 2023. Learn more here and register with code KDN100 for $100 of your conference pass.

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A step-by-step guide to build an Effective Data Quality Strategy from scratch

Towards Data Science

A Step-by-Step Guide to Building an Effective Data Quality Strategy from Scratch How to build an interpretable data quality framework based on user expectations Photo by Rémi Müller on Unsplash As data engineers, we are (or should be) responsible for the quality of the data we provide. This is nothing new, but every time I join a data project I ask myself the same questions: When should I start working on data quality?

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Google Shutting down Firebase Dynamic Links

The Pragmatic Engineer

👋 Hi, this is Gergely with a free issue of the Pragmatic Engineer Newsletter. We cover one out of five topics in today’s subscriber-only The Pulse issue. If you’re not yet a full subscriber, you missed this week’s deepdive: The 2023 tech market, as seen by hiring managers. To get full newsletters twice a week, subscribe here.

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Using MLflow AI Gateway and Llama 2 to Build Generative AI Apps

databricks

To build customer support bots, internal knowledge graphs, or Q&A systems, customers often use Retrieval Augmented Generation (RAG) applications which leverage pre-trained models.

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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

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Robinhood Wallet Adds Support for Bitcoin and Dogecoin, and Enables Ethereum Swaps

Robinhood

Bitcoin and Dogecoin support is now available to all Robinhood Wallet users, and in-app Ethereum Swaps started rolling out today Since launching to the general public nearly six months ago, Robinhood Wallet has seen significant adoption globally, with hundreds of thousands of users in more than 140 countries worldwide. We are always gathering feedback, and have heard loud and clear that people want access to more coins on more chains.

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Forging a Data Strategy for Success in Uncertain Times

Precisely

The results are in! The 2023 Data Integrity Trends and Insights Report , published in partnership between Precisely and Drexel University’s LeBow College of Business, delivers groundbreaking insights into the importance of trusted data. For the report, more than 450 data and analytics professionals worldwide were surveyed about the state of their data programs.

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Who Will Make Money from the Generative AI Gold Rush?

KDnuggets

Buckle up for the Generative AI gold rush! Will BigTech rule with its picks and shovels? Which startups will strike it rich? Will “copilot for X” be the business strategy to hit pay dirt? How can startups dig moats to keep out other prospectors? And will the US once again have the richest gold seams?

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How to Create an Amazon Price Tracker Service Using Python?

Workfall

Reading Time: 12 minutes Hey there, shopping savvy! Ever wished you could magically know when your favorite Amazon items go on sale? Guess what – we’ve cracked the code! Learn how to build your very own Amazon Price Tracker using Python. Imagine getting alerts right in your inbox when prices drop. Let’s dive in and make those savings dreams come true!

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How Embedded Analytics Gets You to Market Faster with a SAAS Offering

Start-ups & SMBs launching products quickly must bundle dashboards, reports, & self-service analytics into apps. Customers expect rapid value from your product (time-to-value), data security, and access to advanced capabilities. Traditional Business Intelligence (BI) tools can provide valuable data analysis capabilities, but they have a barrier to entry that can stop small and midsize businesses from capitalizing on them.

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Supercharging your Rust static executables with mimalloc

Tweag

Why link statically against musl? Have you ever faced compatibility issues when dealing with Linux binary executables? The culprit is often the libc implementation, glibc. Acting as the backbone of nearly all Linux distros, glibc is the library responsible for providing standard C functions. Yet, its version compatibility often poses a challenge. Binaries compiled with a newer version of glibc may not function on systems running an older one, creating a compatibility headache.

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15 Best AXELOS Certifications That Pay Well in 2023

Knowledge Hut

Staying current with rapidly advancing technology holds significant importance. Obtaining the latest certifications can enhance your professional standing by providing you with sought-after skills, thereby increasing your attractiveness to potential employers. It's noteworthy that AXELOS is a renowned authority in awarding certifications across a diverse spectrum of IT domains.

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Announcing Databricks Belgrade Development Center

databricks

We are thrilled to announce the opening of Databricks’ latest development center in Belgrade, Serbia. This addition joins our existing R&D centers in A.

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2023 Esri User Conference: ArcGIS Survey123 Team’s Top Picks

ArcGIS

Dive into the ArcGIS Survey123 team's curated picks from the 2023 Esri User Conference. Learn new tools and tips to help elevate your work.

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Embedding BI: Architectural Considerations and Technical Requirements

While data platforms, artificial intelligence (AI), machine learning (ML), and programming platforms have evolved to leverage big data and streaming data, the front-end user experience has not kept up. Holding onto old BI technology while everything else moves forward is holding back organizations. Traditional Business Intelligence (BI) aren’t built for modern data platforms and don’t work on modern architectures.