June, 2021

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Designing a Data Project to Impress Hiring Managers

Start Data Engineering

Introduction Objective Setup Pre-requisites Project 1. ETL Code 2. Test 3. Scheduler 4. Presentation 4.1. Formatting, Linting, and Type checks 4.2. Architecture Diagram 4.3. README.md 5. Adding Dashboard to your Profile Future Work Tear down infra Conclusion Further Reading References Introduction Building a data project for your portfolio is hard. Getting hiring managers to read through your Github code is even harder.

Project 130
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Turning the page

Cloudera

Today marks the beginning of an exciting new chapter for Cloudera. Cloudera will become a private company with the flexibility and resources to accelerate product innovation, cloud transformation and customer growth. Cloudera will benefit from the operating capabilities, capital support and expertise of Clayton, Dubilier & Rice (CD&R) and KKR – two of the most experienced and successful global investment firms in the world recognized for supporting the growth strategies of the businesses

Cloud 144
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Scaling of Uber’s API gateway

Uber Engineering

As a recap from the last article , Uber’s API Gateway provides an interface and acts as a single point of access for all of our back-end services to expose features and data to Mobile and 3rd party partners. Two … The post Scaling of Uber’s API gateway appeared first on Uber Engineering Blog.

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How to Better Manage Apache Kafka by Creating Kafka Messages from within Control Center

Confluent

Managing Apache Kafka® clusters can be tricky sometimes. To solve this problem, Confluent Control Center helps you easily manage and monitor your clusters and interact with other Confluent components, such […].

Kafka 138
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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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How Netflix uses eBPF flow logs at scale for network insight

Netflix Tech

By Alok Tiagi , Hariharan Ananthakrishnan , Ivan Porto Carrero and Keerti Lakshminarayan Netflix has developed a network observability sidecar called Flow Exporter that uses eBPF tracepoints to capture TCP flows at near real time. At much less than 1% of CPU and memory on the instance, this highly performant sidecar provides flow data at scale for network insight.

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A Candid Exploration Of Timeseries Data Analysis With InfluxDB

Data Engineering Podcast

Summary While the overall concept of timeseries data is uniform, its usage and applications are far from it. One of the most demanding applications of timeseries data is for application and server monitoring due to the problem of high cardinality. In his quest to build a generalized platform for managing timeseries Paul Dix keeps getting pulled back into the monitoring arena.

More Trending

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What is new in Cloudera Streaming Analytics 1.4?

Cloudera

At the end of March, we released the first version of Cloudera SQL StreamBuilder as part of CSA 1.3. It enabled users to easily write, run and manage real-time SQL queries on streams from Apache Kafka with an exceptionally smooth user experience. . Since then, we have been working hard to expose the full power of Apache Flink SQL and the existing Data Warehousing tools in CDP to combine it into a state-of-the-art real-time analytics platform.

Kafka 105
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Efficient and Reliable Compute Cluster Management at Scale

Uber Engineering

Introduction. Uber relies on a containerized microservice architecture. Our need for computational resources has grown significantly over the years, as a consequence of business’ growth. It is an important goal now to increase the efficiency of our computing resources. Broadly … The post Efficient and Reliable Compute Cluster Management at Scale appeared first on Uber Engineering Blog.

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Online, Managed Schema Evolution with ksqlDB Migrations

Confluent

Making changes to a database schema is a natural part of software development. Often, it’s important to carefully manage the timing of changes and keep track of them over time. […].

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7 Types of Classification Algorithms in Machine Learning

ProjectPro

This blog will help you master the fundamentals of classification machine learning algorithms with their pros and cons. You will also explore some exciting machine learning project ideas that implement different types of classification algorithms. So, without much ado, let's dive in. Imagine that the pandemic is over and today is a weekday. All the schools, colleges, and offices are open, and you should reach your institution by 8 A.M.

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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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Lessons Learned From The Pipeline Data Engineering Academy

Data Engineering Podcast

Summary Data Engineering is a broad and constantly evolving topic, which makes it difficult to teach in a concise and effective manner. Despite that, Daniel Molnar and Peter Fabian started the Pipeline Academy to do exactly that. In this episode they reflect on the lessons that they learned while teaching the first cohort of their bootcamp how to be effective data engineers.

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Hadoop vs Spark: Main Big Data Tools Explained

AltexSoft

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. But which one of the celebrities should you entrust your information assets to? To come to the right decision, we need to divide this big question into several smaller ones — namely: What is Hadoop?

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Cloudera named a Strong Performer in The Forrester Wave™: Streaming Analytics, Q2 2021

Cloudera

Cloudera has been named as a Strong Performer in the Forrester Wave for Streaming Analytics, Q2 2021. We are excited to be recognized in this wave at, what we consider to be, such a strong position. We are proud to have been named as one of “ The 14 providers that matter most ” in streaming analytics. The report states that richness of analytics, development tool options and near-effortless scalability are what streaming analytics customers should look for in a provider. .

Kafka 103
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Handling Flaky Unit Tests in Java

Uber Engineering

Introduction to Flaky Tests. Unit testing forms the bedrock of any Continuous Integration (CI) system. It warns software engineers of bugs in newly-implemented code and regressions in existing code, before it is merged. This ensures increased software reliability. It also … The post Handling Flaky Unit Tests in Java appeared first on Uber Engineering Blog.

Java 105
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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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Saxo Bank’s Best Practices for a Distributed Domain-Driven Architecture Founded on the Data Mesh

Confluent

Al data til folket (all data to the people) is a compelling proposition in an enterprise context. Yet the ability to quickly address integration challenges and deliver data to those […].

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Introducing Netflix Timed Text Authoring Lineage

Netflix Tech

A Script Authoring Specification By: Bhanu Srikanth, Andy Swan, Casey Wilms, Patrick Pearson The Art of Dubbing and Subtitling Dubbing and subtitling are inherently creative processes. At Netflix, we strive to make shows as joyful to watch in every language as in the original language, whether a member watches with original or dubbed audio, closed captions, forced narratives, subtitles or any combination they prefer.

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Make Database Performance Optimization A Playful Experience With OtterTune

Data Engineering Podcast

Summary The database is the core of any system because it holds the data that drives your entire experience. We spend countless hours designing the data model, updating engine versions, and tuning performance. But how confident are you that you have configured it to be as performant as possible, given the dozens of parameters and how they interact with each other?

Database 100
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Personalized Insurance: Auto and Telematics, Health, and Other Success Stories

AltexSoft

In today’s society, insurers can no longer ignore the mounting expectations of customers. Clients now expect insurers to provide different levels of personalization that are fast, adaptable, and up to date. That is why some insurers have gone further to provide insurance and risk management services that can be adjusted and rewritten in real-time depending on the changing risk in the consumer’s life.

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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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Telecommunications and the Hybrid Data Cloud

Cloudera

How to optimize an enterprise data architecture with private cloud and multiple public cloud options? As the inexorable drive to cloud continues, telecommunications service providers (CSPs) around the world – often laggards in adopting disruptive technologies – are embracing virtualization. Not only that, but service providers have been deploying their own clouds, some developing IaaS offerings, and partnering with cloud native content providers like Netflix and Spotify to enhance core telco bun

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Three Guiding Principles for Open Banking Platform Design

Teradata

Open Banking platforms require high-reliability, seamless interfaces and should be driven by efficiency. Read more.

Banking 85
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Streaming ETL and Analytics on Confluent with Maritime AIS Data

Confluent

One of the canonical examples of streaming data is tracking location data over time. Whether it’s ride-sharing vehicles, the position of trains on the rail network, or tracking airplanes waking […].

Data 118
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Exploring Data @ Netflix

Netflix Tech

By Gim Mahasintunan on behalf of Data Platform Engineering. Supporting a rapidly growing base of engineers of varied backgrounds using different data stores can be challenging in any organization. Netflix’s internal teams strive to provide leverage by investing in easy-to-use tooling that streamlines the user experience and incorporates best practices.

Data 62
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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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Bring Order To The Chaos Of Your Unstructured Data Assets With Unstruk

Data Engineering Podcast

Summary Working with unstructured data has typically been a motivation for a data lake. The challenge is imposing enough order on the platform to make it useful. Kirk Marple has spent years working with data systems and the media industry, which inspired him to build a platform for automatically organizing your unstructured assets to make them more valuable.

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Standing Up a DataOps Program for Practitioners

DataKitchen

In this five-module course, Mike Lampa & Chris Bergh teach data professionals to plan their organization's DataOps program for low errors & fast deployment. The post Standing Up a DataOps Program for Practitioners first appeared on DataKitchen.

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Validations – Cloudera Support’s Predictive Alerting Program

Cloudera

Cloudera Support’s cluster validations proactively identify known problem signatures contained in customers’ diagnostic data with the goal of increasing cluster health, performance, and overall stability. Cluster validations are included in a customer’s enterprise subscription at no additional cost. All customers with access to the Support case portal will also be able to take advantage of cluster validations.

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Look Out for Risks in Open Banking!

Teradata

Open Banking is re-shaping the landscape of financial services and introducing new types of risks extending beyond data security. Secure open banking is everyone’s responsibility.

Banking 59
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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.

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Are We There Yet? The Query Your Database Can’t Answer

Confluent

What if I told you there is a query your database can’t answer? That would probably surprise you. With decades of effort behind them, databases are one of the most […].

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Dynamic Pricing Strategy for Airlines: Exploring Current Problems and Adopting Continuous Pricing

AltexSoft

In the 1980s, American Airlines and its former president Robert Crandall started a revolution in airline pricing. Crandall is famous for many airline innovations that we use today, such as inventing the first frequent flier program and contributing to route optimization and central reservation system adoption. But he also pioneered yield management — the set of price optimization strategies that preceded revenue management.

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Accelerating ML Training And Delivery With In-Database Machine Learning

Data Engineering Podcast

Summary When you build a machine learning model, the first step is always to load your data. Typically this means downloading files from object storage, or querying a database. To speed up the process, why not build the model inside the database so that you don’t have to move the information? In this episode Paige Roberts explains the benefits of pushing the machine learning processing into the database layer and the approach that Vertica has taken for their implementation.

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Data Engineers of Netflix?—?Interview with Dhevi Rajendran

Netflix Tech

Data Engineers of Netflix?—?Interview with Dhevi Rajendran Dhevi Rajendran This post is part of our “Data Engineers of Netflix” interview series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Dhevi Rajendran is a Data Engineer on the Growth Data Science and Engineering team. Dhevi joined Netflix in July 2020 and is one of many Data Engineers who have onboarded remotely during the pandemic.

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What Is Entity Resolution? How It Works & Why It Matters

Entity Resolution Sometimes referred to as data matching or fuzzy matching, entity resolution, is critical for data quality, analytics, graph visualization and AI. Learn what entity resolution is, why it matters, how it works and its benefits. Advanced entity resolution using AI is crucial because it efficiently and easily solves many of today’s data quality and analytics problems.