Data Engineering Podcast

NOVEMBER 22, 2017

Summary With the wealth of formats for sending and storing data it can be difficult to determine which one to use. In this episode Doug Cutting, creator of Avro, and Julien Le Dem, creator of Parquet, dig into the different classes of serialization formats, what their strengths are, and how to choose one for your workload. They also discuss the role of Arrow as a mechanism for in-memory data sharing and how hardware evolution will influence the state of the art for data formats.

Hadoop 100

Hadoop Data Storage Data Pipeline Data Engineering 100

Cloudera

NOVEMBER 27, 2017

In an earlier VISION post, The Five Markers on Your Big Data Journey , Amy O’Connor shared some common traits of many of the most successful data-driven companies. In this blog, I’d like to explore what I believe is the most important of those traits, building and fostering a culture of data. . The most important elements to establishing a data-driven culture are having a strong executive sponsor and consistent communication.

Big Data 41

Big Data Building Telecommunication Data Ingestion 41

Zalando Engineering

NOVEMBER 29, 2017

Second in our series about the use of Apache Kafka’s Streams API by Zalando This is the second in a series about the use of Apache Kafka’s Streams API by Zalando, Europe’s leading online fashion platform. See Ranking Websites in Real-time with Apache Kafka’s Streams API for the first post in the series. This piece was first published on confluent.io Running Kafka Streams applications in AWS At Zalando, Europe’s leading online fashion platform, we use Apache Kafka for a wide variety of use cases.

Kafka 40

Kafka AWS Amazon Web Services Utilities 40

Data Engineering Podcast

NOVEMBER 14, 2017

Summary Buzzfeed needs to be able to understand how its users are interacting with the myriad articles, videos, etc. that they are posting. This lets them produce new content that will continue to be well-received. To surface the insights that they need to grow their business they need a robust data infrastructure to reliably capture all of those interactions.

Google Cloud 100

Google Cloud Data Ingestion Media AWS 100

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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

Cloudera

NOVEMBER 15, 2017

What’s more terrifying, knowing that you just lost your identity or unknowingly being manipulated? While they both seem awful, they are the reality of the digital world that we live in, just look at the news. With countless articles discussing the recent Equifax hack where thousands of social security numbers were compromised to organizations like Facebook, Google, and Twitter coming forward with Russian accounts that were buying ads to influence US elections.

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AWS Management Data 41

Cloudera

NOVEMBER 30, 2017

It’s almost indefensible today to say that there is a single more important asset to a modern business than the health and happiness of their customers. We simply can not grow as an enterprise without the support, voice, and participation of our users and constituents. However, rarely are our customers raising their hands to speak to us. That doesn’t mean that our customers aren’t talking to us.

BI 40

BI Big Data Data Mining Data Analytics 40

Cloudera

NOVEMBER 16, 2017

Cloudera Data Science Workbench (CDSW) is a self-service collaboration platform for data scientists. It offers: Secure access to Cloudera data. On-demand compute. Support for Python, R, and Scala. Workflow automation, version control, and sharing. GPU acceleration for deep learning on demand. Now, with Release 1.2, CDSW is easier than ever to deploy and manage.

Data Science 40

Data Science Deep Learning Scala Hadoop 40

Cloudera

NOVEMBER 13, 2017

As the market moves toward cloud-based big data and analytics, three qualities emerge as vital for success. While many services will get some traction without meeting all three goals, they will also disappoint users and cause perpetual headaches for IT. At Cloudera, we see these undisputable attributes to be: Easy – Certainly no one goes out looking for a harder way to do their job.

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Cloud Big Data Metadata Machine Learning 40

Cloudera

NOVEMBER 28, 2017

Today, we are thrilled to announce the upcoming beta release of Cloudera Altus Analytic DB. As the first data warehouse cloud service that brings the warehouse to the data, it delivers instant self-service BI and SQL analytics to anyone – easily, reliably, and securely. Business analysts get iterative and flexible analytics with no limits on the number of users or use cases, and IT can easily manage across all tenants with simplified security and governance.

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Cloud BI SQL Data Warehouse 40

Cloudera

NOVEMBER 8, 2017

Pattern recognition. Anomaly detection. Event prediction. All of these capabilities are driven by machine learning (ML.) And recently, ML has been a hot topic among our clients. We’ve seen a steep uptick in companies highlighting their successes in ML. Cloudera offers a unified platform for analytics and machine learning. Each customer that we work with has a unique story, executing numerous uses cases, sometimes spanning multiple divisions, to gain insights that were impossible to achieve with

Machine Learning 40

Machine Learning Aggregated Data Algorithm Data Science 40

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

Cloudera

NOVEMBER 6, 2017

A noteworthy point is that Cloudera complements popular cloud services, such as Amazon Web Services (AWS) and Microsoft Azure. While cloud services do provide useful resources — such as compute instances and object storage on demand — Cloudera offers the unified platform to organize, process, analyze, and store data at large scale… anywhere.

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Cloud Amazon Web Services AWS Metadata 40

Zalando Engineering

NOVEMBER 22, 2017

Using Apache and the Kafka Streams API with Scala on AWS for real-time fashion insights This piece was originally published on confluent.io The Fashion Web Zalando, Europe’s leading online fashion platform, cares deeply about fashion. Our mission statement is to, “Reimagine fashion for the good of all”. To reimagine something, first you need to understand it.

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Kafka Scala Hadoop Algorithm 40

Zalando Engineering

NOVEMBER 20, 2017

Zalando is using an event-driven approach for its new Fashion Platform. Conor Clifford examines why In a recent post , I wrote about how we went about building the core Article services and applications, of Zalando’s new Fashion Platform, with a strong event first focus. That new platform also has a strong overall event-driven focus, rather than a more “traditional” service-oriented approach.

Architecture 40

Architecture Project Systems Machine Learning 40

Zalando Engineering

NOVEMBER 15, 2017

Two brothers examine the pros and cons of UI testing Based on their different experiences in Partner Solutions and Zalando Media Solutions respectively, we speak to frontend developers, Vadym Kukhtin and Oleksandr Kukhtin about their opposing opinions on UI testing. The Case Against UI Testing - Vadym TL;DR It depends on preference, but I believe that UI testing isn’t required in every instance In my experience, it is a sisyphean task to force developers to write even basic Unit tests, nevermind

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Media Project Coding Process 40

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

Zalando Engineering

NOVEMBER 8, 2017

Agile Lead and Software Engineer at Zalon, Jan Helwich on how to work well At the beginning of 2017, we at Zalon decided to enable our teams to work in what we believe is the most effective and efficient way. At the heart of this restructuring process, we assigned cross-functional teams to business goals or user needs only and let them take full responsibility for solving these problems.

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Engineering Software Engineer Software Engineering Data Preparation 40

Zalando Engineering

NOVEMBER 6, 2017

Ana Peleteiro Ramallo takes ‘Data Scientist of the Year’ award at the DatSci’s There was a great turnout at the Dublin DatSci Awards at Dublin’s Croke Park, with Data Scientists from across companies, universities, startups and the public sector attending. Zalando Dublin had finalists in two major award categories, backed up with two tables for support.

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Data Science Deep Learning Media Machine Learning 40

Zalando Engineering

NOVEMBER 1, 2017

Learning from and overcoming the issues that slow our teams down As Agile Coaches we meet a lot of teams, engineers, product people, leads and managers throughout our daily work. Not all of them are agile experts and we understand that there are some misconceptions about “agile”. When we encounter a misconception several times, we see it as a pattern that we can overcome.

Management 40

Management Process Building Engineering 40

Cloudera

NOVEMBER 22, 2017

My leadership experience has taught me many things so far; humility, patience, discipline, respect, and inclusion. All these qualities are applicable in martial arts, one of my many passions outside of work. I have also seen some of my early mentors integrate these values into the DNA of their teams and today, I aspire to do the same for the teams I lead in Cloudera.

Data Science 41

Data Science Hospitality Healthcare Electronics 41

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