Tue.Mar 28, 2023

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Polars vs Spark. Real Talk.

Confessions of a Data Guy

Real talk. Polars is all the rage. People love Spark. People use Spark for small data, but data is too big for Pandas. Spark runs on a local machine. Polars runs on a local machine. What do I choose, Spark or Polars? Does it matter? I’ve written about Polars at different points, here, and here […] The post Polars vs Spark. Real Talk. appeared first on Confessions of a Data Guy.

IT 130
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Reading Minds with AI: Researchers Translate Brain Waves to Images

KDnuggets

Two researchers from Osaka University were able to reconstruct highly accurate images from human brain activity obtained by fMRI. Read this article if you are curious to find out what all the hype is about.

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Uniting the Machine Learning and Data Streaming Ecosystems - Part 1

Confluent

The future of data is real time and enriched by machine learning. How can we overcome socio-technical blockers and unite the ML and data streaming markets?

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Top Posts March 20-26: GPT-4: Everything You Need To Know

KDnuggets

GPT-4: Everything You Need To Know • OpenChatKit: Open-Source ChatGPT Alternative • Top Posts March 13-19: GPT-4: Everything You Need To Know • 5 Free Tools For Detecting ChatGPT, GPT3, and GPT2 • 4 Ways to Generate Passive Income Using ChatGPT

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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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What is GPT-4? How it is better than ChatGPT

Edureka

We were already surprised by the wonders ChatGPT has been doing, and now GPT-4 has arrived with features nobody could have ever imagined. These days, one really can’t say what else we are going to explore in the future of language models, as every day is like a new challenge for the developers of ChatGPT. OpenAI has announced the release of its latest large language model, GPT-4.

IT 98
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5 Machine Learning Skills Every Machine Learning Engineer Should Know in 2023

KDnuggets

Most essential skills are programming, data preparation, statistical analysis, deep learning, and natural language processing.

More Trending

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Are You Doing Your Data Sourcing Right? You Better!

Snowflake

We all know we’re living in challenging times—the economy, global politics, the environment. Not to make light of anything happening today, but this isn’t the first time businesses have faced difficult times. The financial crisis of the early aughts is still relatively recent history. These crises caused a retraction in the economy and a slowdown of many technology investments.

Finance 86
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Automate the Boring Stuff with ChatGPT and Python

KDnuggets

Speed up your daily workflows by getting AI to write Python code in seconds.

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The Executive’s Guide to Data, Analytics and AI Transformation, Part 1: A blueprint for modernization

databricks

Now more than ever, organizations need to adapt quickly to market opportunities and emerging risks so that they are better positioned to adapt.

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Create a No-code GraphQL Server Using Hasura and PostgreSQL

Workfall

Reading Time: 7 minutes To handle CRUD, authorization, and business logic, backend developers frequently need to write several lines of code. All of this code must be tested, debugged, and maintained for the duration of the project. This consumes a significant amount of time that developers could be used to create new features. This blog will demonstrate to you how Hasura and PostgreSQL can help you accelerate app development and easily launch backends.

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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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No Average Patient – Leveraging Data for Precision Healthcare

Cloudera

The evolution of healthcare has come a long way since local physicians made house calls and homespun remedies were formulated using items from the kitchen spice rack. Today’s healthcare is driven as much by the promise of emerging technologies centered on data processing and advanced analytics as by developing new and specialized drugs. This has ushered in a new era of precision healthcare focused on the uniqueness of each patient and the multitude of variables that factor into more precise and

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Data Quality Analyst: The Role In 2023 and Beyond

Monte Carlo

What is a data quality analyst? Ever since the advent of the database there have been data quality issues, and thus data quality specialists. Today, these specialists most frequently hold job titles such as data reliability engineer , data quality engineer, and data quality analyst. The role of a data quality analyst is to ensure reliable data by setting standards, identifying anomalies, and helping to resolve issues.

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4 Reasons Why You Should Automate Data Ingestion

Hevo

As businesses continue to generate and collect large amounts of data, the need for automated data ingestion becomes increasingly critical. The process of ingesting and processing vast amounts of information can be overwhelming.

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5 Proven Best Practices for Measuring Data Team ROI

Monte Carlo

Data leaders are, by nature, comfortable with pulling metrics and crunching numbers. So why is measuring data team ROI such a universally challenging task? That was the first question we posed to our recent powerhouse panel of data leaders: Meenal Iyer , VP of Data at Momentive (maker of SurveyMonkey); Shivani Khanna Stumpf , Group VP of Analytics, Data Science, and New Solutions at education tech provider PowerSchool; and Barr Moses , CEO and co-founder of Monte Carlo.

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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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What is Project Planning? Steps, Process, Importance, Tools

Knowledge Hut

There is a golden adage that says - "you don't plan to fail but you fail to plan"; well, it holds pretty much the same importance in project management as it does in all aspects of life. Project planning is quintessential to the project and projects that are not planned well result in unwanted overheads or at times sunk costs which result in pressures on the execution of the project and often escalate situations out of control for the project manager.

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Stale Data Explained: Why It Kills Data-Driven Organizations

Monte Carlo

What is stale data? Stale data is data that hasn’t been updated at the frequency interval required for its productive use. Depending on the use case, this could be weeks or minutes. It’s completely contextual. For example, the marketing team may require their ad spend dashboard updated weekly for their regular meeting where they make optimization decisions, but a machine learning algorithm that detects financial fraud may require data latency measured in seconds (or less).

IT 52
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4 Reasons Why You Should Automate Data Ingestion

Hevo

As businesses continue to generate and collect large amounts of data, the need for automated data ingestion becomes increasingly critical. The process of ingesting and processing vast amounts of information can be overwhelming.

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Toward a Comprehensive Developer Story Around Imagery

ArcGIS

This series aims to provide a comprehensive picture of imagery to broaden dialogue around developer-centric workflows.

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From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

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Azure Synapse Analytics: A Comprehensive Guide For Data Professionals

Hevo

Ronaldo vs. Messi- who is the better footballer? Oh, that’s tough! Synapse vs. other big 4 data warehouses is just like that. Azure Synapse is one of the best data warehouses which helps data engineers to have an entire end-to-end data pipeline in one place.

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Toward a Comprehensive Developer Story Around Imagery

ArcGIS

This series aims to provide a comprehensive picture of imagery to broaden dialogue around developer-centric workflows.

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Is My Data Lake Actually a Data Swamp?

Elder Research

The post Is My Data Lake Actually a Data Swamp? appeared first on Elder Research.

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The missing guide to debug() in dbt

dbt Developer Hub

Editor's note—this post assumes intermediate knowledge of Jinja and macros development in dbt. For an introduction to Jinja in dbt check out the documentation and the free self-serve course on Jinja, Macros, Pacakages. Jinja brings a lot of power to dbt, allowing us to use ref() , source() , conditional code, and macros. But, while Jinja brings flexibility, it also brings complexity, and like many times with code, things can run in expected ways.

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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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Using Change Data Capture for Warehouse Analytics

Picnic Engineering

Introduction We continue our story on the Analytics Platform setup in Picnic. Last time , we looked at the internal services data pipeline. Now we are going to look at the setup for the FCA (automated fulfillment center) pipeline. FCA is Picnic’s own automated fulfillment center. Thousands of customer orders are prepared here every day in a highly automated manner.

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Ready or Not. The Post Modern Data Stack Is Coming.

Monte Carlo

If you don’t like change, data engineering is not for you. Little in this space has escaped reinvention. The most prominent, recent examples are Snowflake and Databricks disrupting the concept of the database and ushering in the modern data stack era. As part of this movement, Fivetran and dbt fundamentally altered the data pipeline from ETL to ELT.

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Building the Modern Day IRA Metropolis

Robinhood

Robinhood was founded on a simple idea: that our financial markets should be accessible to all. With customers at the heart of our decisions, Robinhood is lowering barriers and providing greater access to financial information and investing. Together, we are building products and services that help create a financial system everyone can participate in.

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How Manufacturers Drive Profits with Connected Products

Snowflake

It’s been a decade since “connected” objects—commonly referred to as “the internet of things” (IoT)— reached broad audiences. Connected toothbrushes, sensors embedded in sneakers, and smart watches have started to change consumer behavior through a data-driven, gamified approach. Technology has rapidly evolved to handle large data volumes at high velocities and big data analytics.

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The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Communication

Speaker: David Bard, Principal at VP Product Coaching

In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.

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Building the Modern Day IRA Metropolis

Robinhood

Robinhood was founded on a simple idea: that our financial markets should be accessible to all. With customers at the heart of our decisions, Robinhood is lowering barriers and providing greater access to financial information and investing. Together, we are building products and services that help create a financial system everyone can participate in.