2020

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Change Data Capture Using Debezium Kafka and Pg

Start Data Engineering

Change data capture is a software design pattern used to capture changes to data and take corresponding action based on that change. The change to data is usually one of read, update or delete. The corresponding action usually is supposed to occur in another system in response to the change that was made in the source system.

Kafka 246
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Coronavirus Data and Poll Analysis – yes, there is hope, if we act now

KDnuggets

We examine the growth of coronavirus daily cases in most affected countries, and show evidence that social distancing works in reducing the rate of spread. We also analyze KDnuggets Poll results - the scale of change to online and how Data Science work is likely to increase or drop in different regions. Stay Healthy and practice social distancing!

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12 Days of Apache Kafka

Confluent

Before you say it: Yes, we are right now three days past Christmas, but technically the 12 days of Christmas refer to the days between Christmas and Epiphany, which is—I […].

Kafka 145
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Introducing Domain-Oriented Microservice Architecture

Uber Engineering

Introduction. Recently there has been substantial discussion around the downsides of service oriented architectures and microservice architectures in particular. While only a few years ago, many people readily adopted microservice architectures due to the numerous benefits they provide such as … The post Introducing Domain-Oriented Microservice Architecture appeared first on Uber Engineering Blog.

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Apache Airflow® 101 Essential Tips for Beginners

Apache Airflow® is the open-source standard to manage workflows as code. It is a versatile tool used in companies across the world from agile startups to tech giants to flagship enterprises across all industries. Due to its widespread adoption, Airflow knowledge is paramount to success in the field of data engineering.

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Keeping Small Queries Fast – Short query optimizations in Apache Impala

Cloudera

This is part of our series of blog posts on recent enhancements to Impala. The entire collection is available here. Apache Impala is synonymous with high-performance processing of extremely large datasets, but what if our data isn’t huge? What if our queries are very selective? The reality is that data warehousing contains a large variety of queries both small and large; there are many circumstances where Impala queries small amounts of data; when end users are iterating on a use case, filterin

Metadata 143

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Doing Good with Data: Teradata's COVID-19 Resiliency Dashboard

Teradata

To help our customers navigate the world's new normal, our teams have created a business-centric, execution-focused tool – we call it the Resiliency Dashboard.

Data 142
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Off The Shelf Data Governance With Satori

Data Engineering Podcast

Summary One of the core responsibilities of data engineers is to manage the security of the information that they process. The team at Satori has a background in cybersecurity and they are using the lessons that they learned in that field to address the challenge of access control and auditing for data governance. In this episode co-founder and CTO Yoav Cohen explains how the Satori platform provides a proxy layer for your data, the challenges of managing security across disparate storage system

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Is Data Engineering a must for Data Scientists?

Team Data Science

Organizations in several industries such as banking, healthcare, and automobiles are now acknowledging the value of data science in their mode of operation. Thus, an ideal and efficacious data science team are therefore expected to manage numerous volume of tasks. Even then, developing a team to successfully manage AI tasks is essential to tackle any challenges faced by organizations as regard data.

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Business Intelligence meets Data Engineering with Emerging Technologies

Simon Späti

Today we have more requirements with ever-growing tools and framework, complex cloud architectures, and with data stack that is changing rapidly. I hear claims: “Business Intelligence (BI) takes too long to integrate new data”, or “understanding how the numbers match up is very hard and needs lots of analysis”. The goal of this article is to make business intelligence easier, faster and more accessible with techniques from the sphere of data engineering.

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Apache Airflow® Best Practices: DAG Writing

Speaker: Tamara Fingerlin, Developer Advocate

In this new webinar, Tamara Fingerlin, Developer Advocate, will walk you through many Airflow best practices and advanced features that can help you make your pipelines more manageable, adaptive, and robust. She'll focus on how to write best-in-class Airflow DAGs using the latest Airflow features like dynamic task mapping and data-driven scheduling!

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20+ Machine Learning Datasets & Project Ideas

KDnuggets

Upgrading your machine learning, AI, and Data Science skills requires practice. To practice, you need to develop models with a large amount of data. Finding good datasets to work with can be challenging, so this article discusses more than 20 great datasets along with machine learning project ideas for you to tackle today.

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Time Series Classification Synthetic vs Real Financial Time Series

KDnuggets

This article discusses distinguishing between real financial time series and synthetic time series using XGBoost.

Finance 160
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The 4 Best Jupyter Notebook Environments for Deep Learning

KDnuggets

Many cloud providers, and other third-party services, see the value of a Jupyter notebook environment which is why many companies now offer cloud hosted notebooks that are hosted on the cloud. Let's have a look at 3 such environments.

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Covid-19, your community, and you — a data science perspective

KDnuggets

Let's talk about covid-19; the reality, the numbers, and the data science.

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Optimizing The Modern Developer Experience with Coder

Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

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50 Must-Read Free Books For Every Data Scientist in 2020

KDnuggets

In this article, we are listing down some excellent data science books which cover the wide variety of topics under Data Science.

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What is the most effective policy response to the new coronavirus pandemic?

KDnuggets

Where Test/Trace/Quarantine are working, the number of cases/day have declined empirically. Furthermore, this appears to be a radically superior strategy where it can be deployed. I’ll review the evidence, discuss the other strategies and their consequences, and then discuss what can be done.

IT 159
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Microsoft Introduces Project Petridish to Find the Best Neural Network for Your Problem

KDnuggets

The new algorithm takes a novel approach to neural architecture search.

Algorithm 160
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I wanna be a data scientist, but… how?

KDnuggets

It’s easy to say "I wanna be a data scientist," but. where do you start? How much time is needed to be desired by companies? Do you need a Master’s degree? Do you need to know every mathematical concept ever derived? The journey might be long, but follow this plan to help you keep moving forward toward your career goal.

Data 160
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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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Top 10 Technology Trends for 2020

KDnuggets

With integrations of multiple emerging technologies just in the past year, AI development continues at a fast pace. Following the blueprint of science and technology advancements in 2019, we predict 10 trends we expect to see in 2020 and beyond.

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The Book to Start You on Machine Learning

KDnuggets

This book is thought for beginners in Machine Learning, that are looking for a practical approach to learning by building projects and studying the different Machine Learning algorithms within a specific context.

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Top 5 must-have Data Science skills for 2020

KDnuggets

The standard job description for a Data Scientist has long highlighted skills in R, Python, SQL, and Machine Learning. With the field evolving, these core competencies are no longer enough to stay competitive in the job market.

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A Comprehensive Guide to Natural Language Generation

KDnuggets

Follow this overview of Natural Language Generation covering its applications in theory and practice. The evolution of NLG architecture is also described from simple gap-filling to dynamic document creation along with a summary of the most popular NLG models.

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

Speaker: Jay Allardyce, Deepak Vittal, Terrence Sheflin, and Mahyar Ghasemali

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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7 Resources to Becoming a Data Engineer

KDnuggets

An estimated 8,650% growth of the volume of Data to 175 zetabytes from 2010 to 2025 has created an enormous need for Data Engineers to build an organization's big data platform to be fast, efficient and scalable.

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Top 9 Mobile Apps for Learning and Practicing Data Science

KDnuggets

This article will tell you about the top 9 mobile apps that help the user in learning and practicing data science and hence is improving their productivity.

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The Most Useful Machine Learning Tools of 2020

KDnuggets

This articles outlines 5 sets of tools every lazy full-stack data scientist should use.

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When Will AutoML replace Data Scientists? Poll Results and Analysis

KDnuggets

Will AI always be 5-10 years away? The majority of respondents to this poll think that AutoML will reach expert level in 5-10 years. Interestingly, it is about the same as 5 years ago. We examine the trends by AutoML experience, industry, and region.

Data 159
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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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10 Python Tips and Tricks You Should Learn Today

KDnuggets

Check out this collection of 10 Python snippets that can be taken as a reference for your daily work.

Python 159
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Resources for Women in AI, Data Science, and Machine Learning

KDnuggets

For the international women's day, we feature resources to help more women enter and succeed in AI, Big Data, Data Science, and Machine Learning fields.

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Predict Electricity Consumption Using Time Series Analysis

KDnuggets

Time series forecasting is a technique for the prediction of events through a sequence of time. In this post, we will be taking a small forecasting problem and try to solve it till the end learning time series forecasting alongside.

IT 159