Sat.Apr 22, 2023 - Fri.Apr 28, 2023

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The Composable Customer Data Platform: Everything You Need To Know

Monte Carlo

Introduction Thanks to the continued push towards a privacy-first internet, first-party customer data has never been more important to digital organizations. With the imminent death of third-party cookies and the rising expectations of modern consumers, companies are quickly moving to invest in implementing scalable customer data infrastructures that can deliver on their many needs.

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Importance of Data Transformation in Business Process

Hevo

In today’s data-driven world, businesses collect and store vast amounts of data from various sources. However, raw data is often unstructured, inconsistent, and may not be immediately usable for analysis or decision-making. That’s where data transformation comes into play.

Process 52
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What is Data Analytics? How to Use it in Your Career?

Analytics Vidhya

In this digital world, Data is the backbone of all businesses. With such large-scale data production, it is essential to have a field that focuses on deriving insights from it. What is data analytics? What tools help in data analytics? How can data analytics be applied to various industries? We will be answering all these […] The post What is Data Analytics?

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Table file formats - Schema evolution: Delta Lake

Waitingforcode

Data lakes have made the data-on-read schema popular. Things seem to change with the new open table file formats, like Delta Lake or Apache Iceberg. Why? Let's try to understand that by analyzing their schema evolution parts.

Data Lake 130
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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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Data News — Week 23.17

Christophe Blefari

Berlin ( credits ) Hey you, new edition of the newsletter. This week summer time arrived in Berlin and it was awesome. I managed to move forward with my client projects this week and it also feels relieving. So I'm pretty happy, sun and great projects 🙂 Regarding the content, if you are in Paris on May 9th, we are organising the Paris Airflow Meetup in Algolia offices, it will be in English so you don't have any excuses not to come.

SQL 100
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Dealing With Noisy Labels in Text Data

KDnuggets

The article shows effective coding procedures for fixing noisy labels in text data that improve the performance of any NLP model. The impact is proved by the comparison of the ML algorithm on starting and cleaning the dataset.

Datasets 114

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Improved Alerting with Atlas Streaming Eval

Netflix Tech

Ruchir Jha , Brian Harrington , Yingwu Zhao TL;DR Streaming alert evaluation scales much better than the traditional approach of polling time-series databases. It allows us to overcome high dimensionality/cardinality limitations of the time-series database. It opens doors to support more exciting use-cases. Engineers want their alerting system to be realtime, reliable, and actionable.

Database 115
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Type-safe data processing pipelines

Tweag

Computing is all about transforming data. A wide variety of domains, such as multimedia, securities trading or compilers, allow decomposing the corresponding transformations into a sequence of well-defined steps. Moreover, these steps can be combined in different ways, perhaps omitting some or changing the order of others, producing different data processing pipelines tailored to a particular task at hand.

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Data Visualization Best Practices & Resources for Effective Communication

KDnuggets

This article is meant to help you understand the art of data visualization and how to apply it to your work.

Data 139
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A Detailed Guide of Interview Questions on Apache Kafka

Analytics Vidhya

Introduction Apache Kafka is an open-source publish-subscribe messaging application initially developed by LinkedIn in early 2011. It is a famous Scala-coded data processing tool that offers low latency, extensive throughput, and a unified platform to handle the data in real-time. It is a message broker application and a logging service that is distributed, segmented, and […] The post A Detailed Guide of Interview Questions on Apache Kafka appeared first on Analytics Vidhya.

Kafka 201
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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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DoorDash identifies Five big areas for using Generative AI

DoorDash Engineering

In the wake of ChatGPT and Generative AI DoorDash is identifying ways this new technology can enhance the customer’s ordering experience on the platform. The company is exploring the use of Generative AI, a subset of Artificial Intelligence that generates novel content based on existing data, and how it can be implemented effectively with consideration for the privacy and security of personal information.

Food 98
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How Does Scrum Master Facilitate Events?

Knowledge Hut

Scrum Masters are important to the success of Scrum teams because they lead many of the activities that make sure the team works well together, improve consistency, and gives the client something of value. In this article, we will look at how a scrum master facilitates events such as daily scrum meetings, sprint planning, sprint review, and sprint retrospective meetings.

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Top Posts April 17-23: AutoGPT: Everything You Need To Know

KDnuggets

AutoGPT: Everything You Need To Know • Baby AGI: The Birth of a Fully Autonomous AI • Mastering Generative AI and Prompt Engineering: A Free eBook • Data Analytics: The Four Approaches to Analyzing Data and How To Use Them Effectively • A Step-by-Step Guide to Web Scraping with Python and Beautiful Soup

Python 107
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A data architecture pattern to maximize the value of the Lakehouse

databricks

One of Lakehouse's outstanding achievements is the ability to combine workloads for modern use cases, such as traditional BI, machine learning & AI.

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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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Gaining Control of Your CDP Environment

Cloudera

Unwelcome… … are platform instability, downtime, hardware failure, poor performance, cluster resource contention, repeated process failures, runaway live queries, critical services alarms, invisibility into alarm cacophony… the list goes on. If those are ailments you would like to remedy … Welcome! To this six-part series, where we’ll look at how to get control of the health of your Cloudera Data platform (CDP) environment.

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Building a large scale unsupervised model anomaly detection system?—?Part 2

Lyft Engineering

Building a large scale unsupervised model anomaly detection system — Part 2 Building ML Models with Observability at Scale By Rajeev Prabhakar , Han Wang , Anindya Saha Photo by Octavian Rosca on Unsplash In our previous blog we discussed the different challenges we faced for model monitoring and our strategy for addressing some of these problems. We briefly mentioned using z-scores to identify anomalies.

Systems 75
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Automate Your Codebase with Promptr and GPT

KDnuggets

Are you looking to streamline your code operations with GPT but are tired of the copy-pasting process? Well, here is the solution in the form of Promptr. An open-source tool to automate your codebase.

Coding 107
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Announcing the General Availability of Predictive I/O for Reads

databricks

Today, we are excited to announce the general availability of Predictive I/O for Databricks SQL (DB SQL): a machine learning powered feature to.

SQL 85
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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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??Kafka Summit London 2023: Level Up Your Kafka Experience!

Confluent

Kafka Summit 2023 brings 60+ sessions, keynotes, and lightning talks, and more from industry leaders. Check out the agenda, highlights, networking events, and more event info.

Kafka 73
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Building an ELT Pipeline in Python and Snowflake

Towards Data Science

Extracting, Loading and Transforming Data Continue reading on Towards Data Science »

Python 98
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MiniGPT-4: A Lightweight Alternative to GPT-4 for Enhanced Vision-language Understanding

KDnuggets

MiniGPT-4 possesses many capabilities of GPT-4 like generating image descriptions, creating a website with a hand-written draft, and writing a poem based on an image.

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Applying software development & DevOps best practices to Delta Live Table pipelines

databricks

Databricks Delta Live Tables (DLT) radically simplifies the development of the robust data processing pipelines by decreasing the amount of code that data.

Coding 80
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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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The (Hidden) Cost of Kafka Operations

Confluent

Quantifying the cost of running Kafka is challenging. In part 2, learn how to calculate Kafka costs stemming from the development and operations personnel needed to self-manage clusters.

Kafka 62
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Running Jaffle Shop dbt Project in Docker

Towards Data Science

A containerised version of the popular Jaffle Shop dbt project Continue reading on Towards Data Science »

Project 87
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Using ChatGPT to Learn SQL

KDnuggets

And how to use this amazing tool to enhance our SQL skills.

SQL 159
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Enhancing Product Search with Large Language Models (LLMs)

databricks

The text generation capabilities of ChatGPT, Dolly and the like are truly impressive and are rightfully recognized as major steps forward in the.

Retail 83
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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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Performance for Free on Android with our MVI Library

Yelp Engineering

In 2018, Yelp switched from using the MVP architecture to the MVI architecture for Android development. Since then, adoption of our new MVI architecture library has risen and we’ve seen some great performance and scalability wins. In this blog post, we’ll cover why we switched to MVI in the first place, how we managed to get performant screens by default, and our take on unit testing MVI.

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LLM Economics: ChatGPT vs Open-Source

Towards Data Science

How much does it cost to deploy LLMs like ChatGPT? Are open-source LLMs cheaper to deploy? What are the tradeoffs?

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Working with Confidence Intervals

KDnuggets

Learn the basics of how confidence intervals are used in data science and statistics.

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Announcing Public Preview of Databricks Marketplace

databricks

We are excited to announce the public preview of Databricks Marketplace, an open marketplace for all your data, analytics, and AI, powered by.

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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.