Sat.Feb 04, 2023 - Fri.Feb 10, 2023

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Most Essential 2023 Interview Questions on Data Engineering

Analytics Vidhya

Introduction Data engineering is the field of study that deals with the design, construction, deployment, and maintenance of data processing systems. The goal of this domain is to collect, store, and process data efficiently and efficiently so that it can be used to support business decisions and power data-driven applications. This includes designing and implementing […] The post Most Essential 2023 Interview Questions on Data Engineering appeared first on Analytics Vidhya.

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Data Types in Delta Lake + Spark. Join and Storage Performance.

Confessions of a Data Guy

Hmm … data types. We all know they are important, but we don’t take them very seriously. I mean we know the difference between boolean, string, and integers, those are easy to get right. But we all get sloppy, sometimes we got the string and varchar route because we don’t spend enough time on the […] The post Data Types in Delta Lake + Spark.

Data 238
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Reflecting On The Past 6 Years Of Data Engineering

Data Engineering Podcast

Summary This podcast started almost exactly six years ago, and the technology landscape was much different than it is now. In that time there have been a number of generational shifts in how data engineering is done. In this episode I reflect on some of the major themes and take a brief look forward at some of the upcoming changes. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Your host is Tobias Macey and today I'm reflecting on the m

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Table file formats - compaction: Apache Iceberg

Waitingforcode

Compaction is also a feature present in Apache Iceberg. However, it works a little bit differently than for Delta Lake presented last time. Why? Let's see in this new blog post!

IT 130
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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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What are Data Access Object and Data Transfer Object in Python?

Analytics Vidhya

Introduction A design pattern is simply a repeatable solution for problems that keep on reoccurring. The pattern is not an actual code but a template that can be used to solve problems in different situations. Especially while working with databases, it is often considered a good practice to follow a design pattern. This ensures easy […] The post What are Data Access Object and Data Transfer Object in Python?

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Ownership and Borrowing in Rust – Data Engineering Gold Mine.

Confessions of a Data Guy

As I started to use Rust on and off, more out of curiosity than anything, I discovered some specs of gold buried down in the depths. Some of the things I’m going to talk about, well … all of it, is probably fairly obvious to most Rust folk, but it’s enjoyable to learn what new […] The post Ownership and Borrowing in Rust – Data Engineering Gold Mine. appeared first on Confessions of a Data Guy.

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The evolution of Facebook’s iOS app architecture

Engineering at Meta

Facebook for iOS (FBiOS) is the oldest mobile codebase at Meta. Since the app was rewritten in 2012 , it has been worked on by thousands of engineers and shipped to billions of users, and it can support hundreds of engineers iterating on it at a time. After years of iteration , the Facebook codebase does not resemble a typical iOS codebase: It’s full of C++, Objective-C(++), and Swift.

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Top 6 Amazon Redshift Interview Questions

Analytics Vidhya

Introduction Amazon Redshift is a fully managed, petabyte-scale data warehousing Amazon Web Services (AWS). It allows users to easily set up, operate, and scale a data warehouse in the cloud. Redshift uses columnar storage techniques to store data efficiently and supports data warehousing workloads intelligence, reporting, and analytics. It allows users to perform complex queries […] The post Top 6 Amazon Redshift Interview Questions appeared first on Analytics Vidhya.

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ChatGPT for Coding: Unleash the Power of ChatGPT

Edureka

We are introduced to new discoveries and technologies every day, and one of the best and most popular inventions today is artificial intelligence (AI) and its tools. One of them is Chat GPT, a conversational model of AI that is a powerful chatbot that answers follow-up questions and writes code for the users. The day it was launched, everybody was going gaga over the new technology and the remarkable uses of this AI-powered chatbot.

Coding 130
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Apache Kafka Beyond the Basics: Windowing

Confluent

Learn what windowing is, the difference between the four types of windows (hopping and tumbling, or session and sliding), and how to create them.

Kafka 140
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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

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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Improving Meta’s global maps

Engineering at Meta

A lot has changed since the initial launch of our basemap in late 2020. We’re Meta now, but our mission remains the same: Giving people the power to build community and bring the world closer together. Across Meta, our family of applications (Facebook, Instagram, WhatsApp, among others) are using our basemap to connect people through functions like status updates, location sharing, and location-based searching.

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Isolated Python Environments using Docker

Analytics Vidhya

Introduction While working with multiple projects, there are chances of issues with versions of packages in python; for example, a project needs a new version of a package, and another requires a different version. Sometimes the python version itself changes from project to project. Managing these different python versions and different versions of packages is […] The post Isolated Python Environments using Docker appeared first on Analytics Vidhya.

Python 218
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How We Scaled New Verticals Fulfillment Backend with CockroachDB

DoorDash Engineering

It would be almost impossible to build a scalable backend without a scalable datastore. DoorDash’s expansion from food delivery into new verticals like convenience and grocery introduced a number of new business challenges that would need to be supported by our technical stack. This business expansion not only increased the number of integrated merchants dramatically but also exponentially increased the number of menu items, as stores have much larger and more complicated inventories than typica

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Regulation: Hurdle or Driver for Data Analytics in Financial Services

Teradata

In the aftermath of the 2008 financial crash, service providers have been subject to increasing rules & requirements. To what extent has this climate held back advances in data analytics?

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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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Learning How to Use ChatGPT to Learn Python (or anything else)

KDnuggets

Let's learn how ChatGPT can help us learn about Python. or really anything at all.

Python 160
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How to Implement a Data Pipeline Using Amazon Web Services?

Analytics Vidhya

Introduction The demand for data to feed machine learning models, data science research, and time-sensitive insights is higher than ever thus, processing the data becomes complex. To make these processes efficient, data pipelines are necessary. Data engineers specialize in building and maintaining these data pipelines that underpin the analytics ecosystem.

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Deploying Data Pipelines using the Saga pattern

Picnic Engineering

Delivering the right events at low latency and with a high volume is critical to Picnic’s system architecture. In our previous blog, Dima Kalashnikov explained how we configure our Internal services pipeline in the Analytics Platform. In this post, we will explain how our team automates the creation of new data pipeline deployments. The step towards automation was an important improvement for us, as the previous setup was manual, slow, and error-prone.

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ThoughtSpot and Databricks make governed, self-service analytics a reality with new Unity Catalog integration

ThoughtSpot

Two years ago, we announced our Databricks partnership —including the launch of ThoughtSpot for Databricks, which gives joint customers the ability to run ThoughtSpot search queries directly on the Databricks Lakehouse without the need to move any data. Since then, we’ve empowered teams at companies like Johnson & Johnson, NASDAQ, and Flyr to safely self-serve business-critical insights on governed and reliable data.

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Improving the Accuracy of Generative AI Systems: A Structured Approach

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

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Linear Programming 101 for Data Scientists

KDnuggets

This post provides an overview of topics in linear programming, history, and recent advances, software packages, common problem specifications, and a case study using Toronto shelters data and the PuLP software package.

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Data Warehouse Interview Questions

Analytics Vidhya

source: svitla.com Introduction Before jumping to the data warehouse interview questions, let’s first understand the overview of a data warehouse. A data warehouse is a system used for collecting and managing large amounts of data from various sources, such as transactional systems, log files, and external data sources. The data is then organized and structured […] The post Data Warehouse Interview Questions appeared first on Analytics Vidhya.

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Running a NixOS VM on macOS

Tweag

In this post I want to explore the current issues with developing parts of NixOS on macOS and how we can make this task easier. Why would I want to run a NixOS virtual machine on macOS? My colleague at Tweag, Dominic Steinitz, asked me this question after I shared my first minor achievement in this area, and it struck me that I have never described why exactly I run virtual machines (VMs) on my laptop and why I want to make it easier for myself (and others).

Systems 103
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Kubernetes Cheat Sheet: Essential Commands And Examples

Knowledge Hut

In this article, we'll discuss the importance of having a Kubernetes cheat sheet available so you can quickly get up-to-speed with this powerful tool before diving into more advanced topics like deployments and automation. What is Kubernetes? Kubernetes is an open-source system for automating containerized applications' deployment, scaling, and management.

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The Ultimate Guide To Data-Driven Construction: Optimize Projects, Reduce Risks, & Boost Innovation

Speaker: Donna Laquidara-Carr, PhD, LEED AP, Industry Insights Research Director at Dodge Construction Network

In today’s construction market, owners, construction managers, and contractors must navigate increasing challenges, from cost management to project delays. Fortunately, digital tools now offer valuable insights to help mitigate these risks. However, the sheer volume of tools and the complexity of leveraging their data effectively can be daunting. That’s where data-driven construction comes in.

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5 Reasons Why You Need Synthetic Data

KDnuggets

Collecting and labeling data in the real world can be time-consuming and expensive. This data can also come with quality, diversity, and quantity issues. Fortunately, problems like these can be helped with synthetic data.

Data 108
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A Beginner’s Guide to the Basics of Big Data and Hadoop

Analytics Vidhya

Introduction In this technical era, Big Data is proven as revolutionary as it is growing unexpectedly. According to the survey reports, around 90% of the present data was generated only in the past two years. Big data is nothing but the vast volume of datasets measured in terabytes or petabytes or even more. Big data […] The post A Beginner’s Guide to the Basics of Big Data and Hadoop appeared first on Analytics Vidhya.

Big Data 205
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AWS Glue-Unleashing the Power of Serverless ETL Effortlessly

ProjectPro

Do ETL and data integration activities seem complex to you? AWS Glue is here to put an end to all your worries! Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Did you know the global big data market will likely reach $268.4 billion by 2026? Businesses are leveraging big data now more than ever.

AWS 98
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Getting started with NLP using Hugging Face transformers pipelines

databricks

Advances in Natural Language Processing (NLP) have unlocked unprecedented opportunities for businesses to get value out of their text data. Natural Language Processing.

Process 101
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Business Intelligence 101: How To Make The Best Solution Decision For Your Organization

Speaker: Evelyn Chou

Choosing the right business intelligence (BI) platform can feel like navigating a maze of features, promises, and technical jargon. With so many options available, how can you ensure you’re making the right decision for your organization’s unique needs? 🤔 This webinar brings together expert insights to break down the complexities of BI solution vetting.

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Learn Data Engineering From These GitHub Repositories

KDnuggets

Kickstart your Data Engineering career with these curated GitHub repositories.

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February DataHour: Enhance Your Skills with Expert Sessions

Analytics Vidhya

Introduction The February installment of the webinar series is now open! It’s a farewell time to your quest for finding the ideal data science learning platform, as Analytics Vidhya has arrived. Explore your ultimate data science destination where the emphasis is on supporting the community and fostering professional development. Attend expert-led DataHour sessions to boost […] The post February DataHour: Enhance Your Skills with Expert Sessions appeared first on Analytics Vidhya.

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6 Steps to Making Data Reliability a Habit

Towards Data Science

Some organizations approach data quality like a crash diet. Instead, try these 6 steps for sustainable data quality at scale. Photo by Bruno Nascimento on Unsplash I like to think of operationalizing data reliability within the context of physical fitness. You can get in shape with hard work, but staying in shape requires good habits. And above all else it’s a mindset and a lifestyle.

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What’s New in Apache Kafka 3.4

Confluent

Migrate Kafka clusters from ZooKeeper to KRaft with no downtime (early access), get improvements for Kafka Streams and Kafka Connect, and more.

Kafka 105
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Driving Responsible Innovation: How to Navigate AI Governance & Data Privacy

Speaker: Aindra Misra, Senior Manager, Product Management (Data, ML, and Cloud Infrastructure) at BILL

Join us for an insightful webinar that explores the critical intersection of data privacy and AI governance. In today’s rapidly evolving tech landscape, building robust governance frameworks is essential to fostering innovation while staying compliant with regulations. Our expert speaker, Aindra Misra, will guide you through best practices for ensuring data protection while leveraging AI capabilities.