Start Data Engineering

SEPTEMBER 26, 2020

Table of Contents Table of Contents Introduction Project description and requirements Infrastructure overview Apache Flink Apache Kafka Design Detect fraudulent accounts Log account actions Prerequisites Code Defining dependencies Inheritance Server logs generator Defining data flow in Apache Flink Create a streaming environment Creating a consumer to read events from Apache Kafka Detecting fraud and generating alert events Writing server logs to a PostgreSQL DB Fraud detection logic Open proces

Data Engineering 130

Data Engineering Data Engineer Project Engineering 130

Team Data Science

SEPTEMBER 2, 2020

"Where can I start if I want to become a Data Engineer?" This is a question I have heard many times before. My answer to it is actually always the same: Start doing a Data Engineering project! Choose a tool Your first step here should be to select a tool. Then start with that tool and then build the whole thing up. So you get some data and then start with a tool.

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Data Engineering Data Engineer Google Cloud Engineering 130

Confluent

SEPTEMBER 29, 2020

ksqlDB, the event streaming database, is becoming one of the most popular ways to work with Apache Kafka®. Every day, we answer many questions about the project, but here’s a […].

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Process Kafka Database Project 145

Cloudera

SEPTEMBER 28, 2020

Cloudera delivers an enterprise data cloud that enables companies to build end-to-end data pipelines for hybrid cloud, spanning edge devices to public or private cloud, with integrated security and governance underpinning it to protect customers data. Cloudera has found that customers have spent many years investing in their big data assets and want to continue to build on that investment by moving towards a more modern architecture that helps leverage the multiple form factors.

Cloud 132

Cloud Kafka Professional Services Metadata 132

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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?

Business Intelligence

Data Engineering Podcast

SEPTEMBER 28, 2020

Summary Kafka has become a de facto standard interface for building decoupled systems and working with streaming data. Despite its widespread popularity, there are numerous accounts of the difficulty that operators face in keeping it reliable and performant, or trying to scale an installation. To make the benefits of the Kafka ecosystem more accessible and reduce the operational burden, Alexander Gallego and his team at Vectorized created the Red Panda engine.

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Kafka Big Data BI Data Engineering 100

Netflix Tech

SEPTEMBER 2, 2020

Edgar helps Netflix teams troubleshoot distributed systems efficiently with the help of a summarized presentation of request tracing, logs, analysis, and metadata. by Elizabeth Carretto Everyone loves Unsolved Mysteries. There’s always someone who seems like the surefire culprit. There’s a clear motive, the perfect opportunity, and an incriminating footprint left behind.

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Metadata Transportation Engineering Systems 119

Team Data Science

SEPTEMBER 1, 2020

"Since I started exploring Data Engineering, it has been overwhelming. In the end I have the feeling of giving up." This is a message that reached me from a viewer on YouTube. And that's exactly how I feel sometimes! Sometimes I feel a bit overwhelmed by the whole thing. Because there is so much going on. All the technology and Data Science hype. There is always something new on the horizon.

Data Science 130

Data Science Hadoop Kafka Big Data 130

Confluent

SEPTEMBER 24, 2020

Operating critical Apache Kafka® event streaming applications in production requires sound automation and engineering practices. Streaming applications are often at the center of your transaction processing and data systems, requiring […].

Kafka 143

Kafka Engineering Systems Process 143

Cloudera

SEPTEMBER 29, 2020

Performance is one of the key, if not the most important deciding criterion, in choosing a Cloud Data Warehouse service. In today’s fast changing world, enterprises have to make data driven decisions quickly and for that they rely heavily on their data warehouse service. . In this blog post, we compare Cloudera Data Warehouse (CDW) on Cloudera Data Platform (CDP) using Apache Hive-LLAP to Microsoft HDInsight (also powered by Apache Hive-LLAP) on Azure using the TPC-DS 2.9 benchmark.

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Data Warehouse Cloud Storage Metadata Cloud 120

Data Engineering Podcast

SEPTEMBER 21, 2020

Summary Data engineering is a constantly growing and evolving discipline. There are always new tools, systems, and design patterns to learn, which leads to a great deal of confusion for newcomers. Daniel Molnar has dedicated his time to helping data professionals get back to basics through presentations at conferences and meetups, and with his most recent endeavor of building the Pipeline Data Engineering Academy.

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Data Engineering Data Engineer Engineering AWS 100

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.

Data

Netflix Tech

SEPTEMBER 18, 2020

Analytics at Netflix: Who We Are and What We Do An Introduction to Analytics and Visualization Engineering at Netflix by Molly Jackman & Meghana Reddy Explained: Season 1 (Photo Credit: Netflix) Across nearly every industry, there is recognition that data analytics is key to driving informed business decision-making. But there is far less agreement on what that term “data analytics” actually means?

BI 97

BI Engineering Data Science Data Warehouse 97

Teradata

SEPTEMBER 3, 2020

Taking the definition of physical gravity & extending it to data analytics, we explore the opportunities to combine data gravity with analytic processing, at scale with Vantage.

Process 93

Process Data Analytics Data IT 93

Team Data Science

SEPTEMBER 1, 2020

In which regions or countries is there a boom in the field of Data Sciences and thus a large number of jobs? This is a very interesting question, which newcomers or graduates often ask themselves. Maybe you have already asked yourself this question? The USA as an advanced country Companies in the USA are obviously very, very advanced with Data Science.

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Data Science Computer Science Manufacturing Education 130

Confluent

SEPTEMBER 16, 2020

Near-real-time insights have become a de facto requirement for Azure use cases involving scalable log analytics, time series analytics, and IoT/telemetry analytics. Azure Data Explorer (also called Kusto) is the […].

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Kafka Data Programming Cloud 139

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.

Manufacturing

Cloudera

SEPTEMBER 14, 2020

Everybody needs more data and more analytics, with so many different and sometimes often conflicting needs. Data engineers need batch resources, while data scientists need to quickly onboard ephemeral users. Data architects deal with constantly evolving workloads and business analysts must balance the urgency and importance of a concurrent user population that continues to grow.

Data Management 111

Data Management Cloud Management Business Analyst 111

Data Engineering Podcast

SEPTEMBER 14, 2020

Summary In memory computing provides significant performance benefits, but brings along challenges for managing failures and scaling up. Hazelcast is a platform for managing stateful in-memory storage and computation across a distributed cluster of commodity hardware. On top of this foundation, the Hazelcast team has also built a streaming platform for reliable high throughput data transmission.

Process 100

Process Unstructured Data Metadata Data Engineering 100

Netflix Tech

SEPTEMBER 8, 2020

How we migrated our Android endpoints out of a monolith into a new microservice by Rohan Dhruva , Ed Ballot As Android developers, we usually have the luxury of treating our backends as magic boxes running in the cloud, faithfully returning us JSON. At Netflix, we have adopted the Backend for Frontend (BFF) pattern : instead of having one general purpose “backend API”, we have one backend per client (Android/iOS/TV/web).

Java 95

Java Metadata Coding Architecture 95

Teradata

SEPTEMBER 14, 2020

The game had changed for the retail sector long ago – but it has taken the COVID-19 crisis for people to notice. A new appreciation for the role of data in retail has emerged.

Retail 93

Retail IT Data 93

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.

Systems

Rockset

SEPTEMBER 25, 2020

According to over 40,000 developers, MongoDB is the most popular NOSQL database in use right now. The tool’s meteoric rise is likely due to its JSON structure which makes it easy for Javascript developers to use. From a developer perspective, MongoDB is a great solution for supporting modern data applications. Nevertheless, developers sometimes need to pull specific workflows out of MongoDB and integrate them into a secondary system while continuing to track any changes to the underlying MongoDB

MongoDB 52

MongoDB Kafka Database NoSQL 52

Confluent

SEPTEMBER 1, 2020

If you are taking your first steps with Apache Kafka®, looking at a test environment for your client application, or building a Kafka demo, there are two “easy button” paths […].

Kafka 133

Kafka Building Cloud 133

Cloudera

SEPTEMBER 17, 2020

For enterprise organizations, managing and operationalizing increasingly complex data across the business has presented a significant challenge for staying competitive in analytic and data science driven markets. With growing disparate data across everything from edge devices to individual lines of business needing to be consolidated, curated, and delivered for downstream consumption, it’s no wonder that data engineering has become the most in-demand role across businesses — growing at an estima

Data Pipeline 104

Data Pipeline Data Engineering Data Engineer Engineering 104

Data Engineering Podcast

SEPTEMBER 7, 2020

Summary Databases are limited in scope to the information that they directly contain. For analytical use cases you often want to combine data across multiple sources and storage locations. This frequently requires cumbersome and time-consuming data integration. To address this problem Martin Traverso and his colleagues at Facebook built the Presto distributed query engine.

Architecture 100

Architecture Data Architecture SQL Engineering 100

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.

Project

Netflix Tech

SEPTEMBER 18, 2020

Part of our series on who works in Analytics at Netflix?—?and what the role entails by Julie Beckley & Chris Pham This Q&A provides insights into the diverse set of skills, projects, and culture within Data Science and Engineering (DSE) at Netflix through the eyes of two team members: Chris Pham and Julie Beckley. Photo from a team curling offsite?

Data Science 91

Data Science Consulting Food Algorithm 91

Teradata

SEPTEMBER 21, 2020

Get tips on how to cast a more critical eye on the seemingly endless amount of data-driven conclusions presented to us. Learn more.

Data 106

Data 106

Afterpay Tech

SEPTEMBER 24, 2020

Photo by Pietro Jeng on Unsplash By Letian Wang Context At Afterpay, we are generating lots of data from customer transactions, website views and consumer referrals every day. Being able to derive insights from this data, and to use those insights to  improve our consumer experience and provide value to our merchants and consumers, is a critical competitive differentiator for Afterpay.

Data Science 52

Data Science Building Data Lake Machine Learning 52

Confluent

SEPTEMBER 30, 2020

The ksqlDB team is pleased to announce ksqlDB 0.12.0. This release continues to improve upon the usability of ksqlDB and aims to reduce administration time. Highlights include query upgrades, which […].

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Process 98

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.

Government

Cloudera

SEPTEMBER 10, 2020

Digital transformation has been on the agenda for a long time, but the sudden need to respond to the unprecedented challenges of 2020, has meant the buzzword has become an executable reality for many enterprises. I recently came across a KPMG report that revealed that 80% of executives are increasing investments on emerging technologies now, to drive higher realized value in the future.

IT 103

IT Data Lake Healthcare Cloud 103

Grouparoo

SEPTEMBER 22, 2020

I have been working on the Salesforce integration. That experience will be its own story. In the process, though, I found something tricky that I might be uniquely experiencing given the combinatorics of the modern Node/Javascript/Typescript world. Grouparoo connects with sources, processes the data from them, and sends that data to destinations. When data comes from a source, we call it an import.

Coding 52

Coding Process Engineering IT 52

Netflix Tech

SEPTEMBER 4, 2020

HDMI?—?Scaling Netflix Certification Scott Bolter , Matthew Lehman , Akshay Garg ¹ At Netflix, we take the task of preserving the creative vision of our content all the way to a subscriber TV screen very seriously. This significantly increases the scope of our application integration and certification processes for streaming devices like set-top-boxes (STBs) and TVs.

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Certification Media Electronics Entertainment 66

Teradata

SEPTEMBER 7, 2020

The latest release of Teradata Vantage with Native Object Store enables companies to not only drive down costs by leveraging object store technologies, but also improve manageability and drive business insights with the power of Vantage.

Technology 90

Technology Management 90

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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.

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