Sat.Apr 09, 2022 - Fri.Apr 15, 2022

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What is the difference between a data lake and a data warehouse?

Start Data Engineering

Introduction Data lakes and data warehouses Data lake Data warehouse Criteria to choose lake and warehouse tools Conclusion Further reading References Introduction With the data ecosystem growing fast, new terms are coming up every week. Some of the most popular ones include “data lakes” and “data warehouses” If you are Trying to understand the differences between a data lake and a data warehouse Frustrated by vendor marketing content aimed at selling their lake/warehouse

Data Lake 130
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5 Different Ways to Load Data in Python

KDnuggets

Data is the bread and butter of a Data Scientist, so knowing many approaches to loading data for analysis is crucial. Here, five Python techniques to bring in your data are reviewed with code examples for you to follow.

Python 160
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The Reasons for Data Mesh on Pulsar

Jesse Anderson

Data mesh is quickly becoming a way for companies to roll out their data strategy. If you haven’t already learned about data mesh , I suggest doing so. It comes with organizational and technical changes. I think a crucial part of your data mesh revolves around the choice of publish/subscribe technologies. At the crux of data mesh is a desire for flexibility.

Kafka 124
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How Apache Kafka Works: An Introduction to Kafka’s Internals

Confluent

It’s not difficult to get started with Apache Kafka®. Learning resources can be found all over the internet, especially on the Confluent Developer site. If you are new to Kafka, […].

Kafka 124
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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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Synthetic Data As A Service For Simplifying Privacy Engineering With Gretel

Data Engineering Podcast

Summary Any time that you are storing data about people there are a number of privacy and security considerations that come with it. Privacy engineering is a growing field in data management that focuses on how to protect attributes of personal data so that the containing datasets can be shared safely. In this episode Gretel co-founder and CTO John Myers explains how they are building tools for data engineers and analysts to incorporate privacy engineering techniques into their workflows and val

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Data Science Interview Guide – Part 2: Interview Resources

KDnuggets

Check out these resources to help you prepare for your data science Interview, or for those who are brushing up on their technical skills or who want to start learning data science.

More Trending

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Responsible AI: Ways to Avoid the Dark Side of AI Use

AltexSoft

“AI systems (will) take decisions that have ethical grounds and consequences.”. Prof. Dr. Virginia Dignum from Umeå University. On March 23, 2016, Microsoft released its AI-based chatbot Tay via Twitter. The bot was trained to generate its responses based on interactions with users. But there was a catch. Various users started posting offensive tweets toward the bot, resulting in Tay making replies in the same language.

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Stop Trying to be a Digital Bank

Teradata

Digitization is necessary, but not sufficient to meet evolving customer demands & create the bank of the future. Use data analytics to help customers achieve their goals not deliver better apps.

Banking 98
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Answering Questions with HuggingFace Pipelines and Streamlit

KDnuggets

See how easy it can be to build a simple web app for question answering from text using Streamlit and HuggingFace pipelines.

Building 153
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#Clouderalife Volunteer Spotlight: Dániel Omaisz-Takács

Cloudera

April 11 is “Inter” National Pet Day, a day dedicated to celebrating the pets and animals in our lives and communities. . While Pet Day is the perfect moment to show some extra love to the pets in our lives – Cloudera wants to take this opportunity to also recognize a Cloudera volunteer who goes above and beyond to care for the welfare and health of animals outside of his family – Dániel Omaisz-Takács.

Medical 78
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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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Harness Trusted, Quality Data Streams with Confluent Platform 7.1

Confluent

Streaming data has become critical to the success of modern businesses. Leveraging real-time data enables companies to deliver the rich, digital experiences and data-driven backend operations that delight customers. For […].

Data 57
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It’s the ROI that Matters when Migrating to the Cloud

Teradata

Agility & innovation are the primary benefits enabled by a move to the cloud, but the initial focus is often on reducing the total cost of ownership. But this is only the first stage!

Cloud 75
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Python Libraries Data Scientists Should Know in 2022

KDnuggets

Let's have a look at the Python libraries that every data scientist should know in 2022, to maintain and improve their coding journey.

Python 133
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5 Ways to Improve Data Quality with the New Monte Carlo Data Quality Trends Dashboard

Monte Carlo

Monte Carlo recently launched an updated Dashboard view as part of our efforts to equip our customers with the best tools to tackle their data downtime issues effectively seamlessly. The Dashboard incorporates data and visualization to provide actionable insights to users across data teams. Our customers use these features to gain visibility into how their incident levels are trending, the status of incident resolution, the health of custom monitors, team specific data, and other data health ins

Bytes 52
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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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Pipeline Academy Setting Trends at the EdTech Awards

Pipeline Data Engineering

Finalists and winners for The EdTech Awards 2022 have been announced to a worldwide audience of educators, technologists, students, parents, and policymakers interested in building a better future for learners and leaders in the education and workforce sectors. The EdTech Awards were established in 2010 to recognise, acknowledge, and celebrate the most exceptional innovators, leaders, and trendsetters in education technology.

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Hotjar.com™ feedback widget in Ionic v3 mobile apps

nodeSWAT

_Note: This solution is making use of undocumented features and inner workings of Hotjar feedback widget and is not guaranteed to work or might break if Hotjar decides to change something inside their code. I am in no way affiliated with Hotjar.com ™ and can not offer any support regarding these matters._ I had a request the other day to integrate Hotjar.com™ feedback widget into our iOS and Android mobile applications which run on Ionic v3.

Coding 52
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The Complete Collection Of Data Repositories – Part 2

KDnuggets

Check out the collection of the best data repositories on healthcare, natural language, neuroscience, physics, social network, sports, time series, transportation, miscellaneous, and super data repositories.

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Navigating the Maze of Azure Data Certifications

A Cloud Guru: Data Engineering

It’s no secret that the Azure certification exam ecosystem can be tricky to navigate. There are lots of certs that are frequently updated or retired, and new ones get added all the time. Today, we’ll dive in a specific corner of the maze that is the world of Azure Data certifications. Find out what certifications […] The post Navigating the Maze of Azure Data Certifications appeared first on A Cloud Guru.

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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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Rockset Goes on the Road!

Rockset

In-person data and analytics events are back in full swing, and Rockset will be at three events in the span of one week this April. Rockset exhibiting at AWS re:Invent 2021 in Las Vegas AWS Summit San Francisco You can catch us first at AWS Summit SF , April 20th and 21st, at Moscone Center South in San Francisco. Visit us at booth #609 to enter to win our live PlayStation 5 raffle at the end of day one of the conference.

Food 52
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Vanquish Toil: 9 Data Engineering Processes Ripe For Automation

Monte Carlo

Data teams love the idea of automating data engineering processes in principle. After all, who doesn’t want to move faster and eliminate the time consuming, boring aspects of their job? But even time-strapped, technically savvy engineers will sometimes squirm when the suggestion is made to automate a specific task. We’ve felt it ourselves. There are often understandable reasons for this hesitation: An upfront investment of time and/or resources The change management needed to modify related proc

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How to Write Engaging Technical Blogs

KDnuggets

Learn the rules for writing technical blogs, and increase unique views tenfold. Focusing on title, images, vocabulary, code blocks, writing style, and social media promotion can help you build a solid brand.

Media 108
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Functional tests with Testcontainers

Zalando Engineering

In this article, I will show how teams at Zalando Marketing Services are using functional tests. We will follow the idea of functional tests: the main concept and the attributes of a good functional test. Then, we will discuss an example based on the TestContainers library used in the Spring environment. You can find an introduction to the TestContainers library in my previous article Integration tests with Testcontainers , because that is out of the scope of this one.

Java 52
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Entity Resolution Checklist: What to Consider When Evaluating Options

Are you trying to decide which entity resolution capabilities you need? It can be confusing to determine which features are most important for your project. And sometimes key features are overlooked. Get the Entity Resolution Evaluation Checklist to make sure you’ve thought of everything to make your project a success! The list was created by Senzing’s team of leading entity resolution experts, based on their real-world experience.

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??Kafka Summit London 2022: Welcoming the ??Apache Kafka Community Back to In-Person Events!

Confluent

In just a few weeks’ time, the Apache Kafka® community will be convening for Kafka Summit London 2022—its first in-person event in over two years. The conference is being held […].

Kafka 52
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How Netflix Content Engineering makes a federated graph searchable

Netflix Tech

By Alex Hutter , Falguni Jhaveri and Senthil Sayeebaba Over the past few years Content Engineering at Netflix has been transitioning many of its services to use a federated GraphQL platform. GraphQL federation enables domain teams to independently build and operate their own Domain Graph Services (DGS) and, at the same time, connect their domain with other domains in a unified GraphQL schema exposed by a federated gateway.

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Top 5 Reasons Why You Should Avoid a Data Science Career

KDnuggets

The intent of this article is to give you a reality check of what are the personality traits of a typical data scientist before you dip your feet in the ocean of the big shiny world of data science.

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DataOps As A Service For Your Data Integration Workflows With Rivery

Data Engineering Podcast

Summary Data engineering is a practice that is multi-faceted and requires integration with a large number of systems. This often means working across multiple tools to get the job done which can introduce significant cost to productivity due to the number of context switches. Rivery is a platform designed to reduce this incidental complexity and provide a single system for working across the different stages of the data lifecycle.

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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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Data In Motion: NASA and Aurica

Cloudera

Some 300 million years ago, Earth had one continent called Pangea. Over millions of years, that vast single land mass broke up and drifted in different directions, creating the seven continents that exist today. . Since the planet changed so dramatically over millennia, it raises an obvious question: How will it change in the future? The same forces, plate tectonics and continental drift, that broke up Pangea hundreds of millions of years ago still exert themselves.

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Handling Out-of-Order Data in Real-Time Analytics Applications

Rockset

This is the second post in a series by Rockset's CTO Dhruba Borthakur on Designing the Next Generation of Data Systems for Real-Time Analytics. We'll be publishing more posts in the series in the near future, so subscribe to our blog so you don't miss them! Posts published so far in the series: Why Mutability Is Essential for Real-Time Data Analytics Handling Out-of-Order Data in Real-Time Analytics Applications Handling Bursty Traffic in Real-Time Analytics Applications SQL and Complex Queries

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How to Ace Data Science Assessment Test by Using Automatic EDA Tools

KDnuggets

By using a few lines of code, you can understand key aspects of a given dataset. These tools have helped me answer business-related questions during the data assessment test by Alooba.

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Top Posts April 4-10: The Complete Collection Of Data Repositories – Part 1

KDnuggets

Also: Decision Tree Algorithm, Explained; 8 Free MIT Courses to Learn Data Science Online; Why Are So Many Data Scientists Quitting Their Jobs?; Top Programming Languages and Their Uses.

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How to Build an Experimentation Culture for Data-Driven Product Development

Speaker: Margaret-Ann Seger, Head of Product, Statsig

Experimentation is often seen as an aspirational practice, especially at smaller, fast-moving companies who are strapped for time and resources. So, how can you get your team making decisions in a more data-driven way while continuing to remain lean and maintaining ship velocity? In this webinar, Margaret-Ann Seger, Head of Product at Statsig, will teach you how to build an experimentation culture from the ground-up, graduating from just getting started with data-driven development to operating