use case

Analytics at ING: Technology solutions to create a real-time, data-driven bank

Analytics at ING: Technology solutions to create a real-time, data-driven bank

January 2, 2020

Bas Geerdink explains why and how ING is becoming more and more data-driven, sharing use cases, architecture, and technology choices along the way.
Best practices with Kudu: An end-to-end user case from the automobile industry

Best practices with Kudu: An end-to-end user case from the automobile industry

January 2, 2020

Kudu is designed to fill the gap between HDFS and HBase. However, designing a Kudu-based cluster presents a number of challenges. Wei Chen and Zhaojuan Bian share a real-world use case from the automobile industry to explain how to design a Kudu-based E2E system. They also discuss key indicators to tune Kudu and OS parameters and how to select the best hardware components for different scenarios.
ITNW (If This Now What) - Orchestrating an Enterprise

ITNW (If This Now What) - Orchestrating an Enterprise

January 2, 2020

With growing demand for containers in the enterprise, Pearson chose to lay its foundation with Kubernetes. With 400+ development teams across varying business units, the platform is absolutely critica …
Human-in-the-loop: a design pattern for managing teams that leverage ML

Human-in-the-loop: a design pattern for managing teams that leverage ML

December 31, 2019

Human-in-the-loop is an approach which has been used for simulation, training, UX mockups, etc. A more recent design pattern is emerging for human-in-the-loop (HITL) as a way to manage teams working with machine learning (ML). A variant of semi-supervised learning called active learning allows for mostly automated processes based on ML, where exceptions get referred to human experts.
Industrial machine learning

Industrial machine learning

December 31, 2019

The ongoing digitization of the industrial-scale machines that power and enable human activity is itself a major global transformation. Joshua Bloom explains why the real revolutionin efficiencies and in improved and saved liveswill happen when machine learning automation and insights are properly coupled to the complex systems of industrial data.
Network Automation with State Machines

Network Automation with State Machines

December 31, 2019

Automation has become vital to building large scale networks. However, building these networks and managing their entire life cycle with minimal human intervention …
Cluster Federation in Kubernetes: Past, Present and the Future

Cluster Federation in Kubernetes: Past, Present and the Future

December 30, 2019

In this session, I want to briefly present the current state of cluster federation in Kubernetes mainly focusing on what we aimed to accomplish, where we are today and where we want to go. After that …
New Features in Kubernetes Storage

New Features in Kubernetes Storage

December 29, 2019

Two major features were recently added to kubernetes storage– volume selectors and dynamic provisioning using StorageClasses. The addition of persistent volume selectors greatly increases a users a …
Smart cities, the smart grid, the IoT, and big data

Smart cities, the smart grid, the IoT, and big data

December 29, 2019

Smart cities and the electricity smart grid have become leading examples of the IoT, in which distributed sensors describe mission-critical behavior by generating billions of metrics daily. Mark Donsky and Syed Rafice show how smart utilities and cities rely on Hadoop to capture, analyze, and harness this data to increase safety, availability, and efficiency across the entire electricity grid.
State of the GPU(nion)

State of the GPU(nion)

December 29, 2019

As Kubernetes becomes more popular, the number of use cases for it grow as well, bringing with them more specialized requirements. Scheduling and launch of containers that interact with GPUs is one of …
Application caching at Netflix: The hidden microservice

Application caching at Netflix: The hidden microservice

December 28, 2019

Netflix is well known for championing the microservice model, but within the complex layers of dependencies is a hidden service: the caching layer. Scott Mansfield explains how the EVCache service fits into the Netflix experience and how it works in the dynamic cloud environment to provide fast and scalable application data caching.
Enter the Matrix, Exploring Your Kubernetes Cluster in Virtual Reality

Enter the Matrix, Exploring Your Kubernetes Cluster in Virtual Reality

December 28, 2019

This is a combination of fun hack + potentially real-world use-case (sometime in the future). The idea is to use WebVR and a Kubernetes API client to render a Kubernetes cluster in a Virtual Reality e …
Suffering Withdrawal; an automated approach to connectivity evaluation

Suffering Withdrawal; an automated approach to connectivity evaluation

December 28, 2019

Todays routers generally make themselves more- or less-attractive to transit traffic through operators manipulation of their interfaces IGP metrics or overload s …
Train, predict, and serve: How to put your machine learning model into production

Train, predict, and serve: How to put your machine learning model into production

December 28, 2019

Aki Ariga explains how to put your machine learning model into production, discusses common issues and obstacles you may encounter, and shares best practices and typical architecture patterns of deployment ML models with example designs from the Hadoop and Spark ecosystem using Cloudera Data Science Workbench.
Segment Routing in Datacenter

Segment Routing in Datacenter

December 25, 2019

Segment Routing is a network technology that proposes to solve many of the limitations of traditional IP & MPLS networks. It's proposes to be the bridge between th …
A data-first approach to drive real-time applications

A data-first approach to drive real-time applications

December 16, 2019

Leading companies that are getting the most out of their data are not focusing on queries and data lakes; they are actively integrating analytics into their operations. Jack Norris reviews three customer case studies in ad/media, financial services, and healthcare to show how a focus on real-time data streams can transform the development, deployment, and future agility of applications.
Authorization in the cloud: Enforcing access control across compute engines

Authorization in the cloud: Enforcing access control across compute engines

December 16, 2019

Li Li and Hao Hao elaborate the architecture of Apache Sentry + RecordService for Hadoop in the cloud, which provides unified, fine-grained authorization via role- and attribute-based access control, to encourage attendees to adopt Apache Sentry and RecordService to protect sensitive data on the multitenant cloud across the Hadoop ecosystem.
Beyond Hadoop at Yahoo: Interactive analytics with Druid

Beyond Hadoop at Yahoo: Interactive analytics with Druid

December 16, 2019

Himanshu Gupta explains why Yahoo has been increasingly investing in interactive analytics and how it leverages Druid to power a variety of internal- and external-facing data applications.
Business insights driven by speed

Business insights driven by speed

December 14, 2019

The need to quickly acquire, process, prepare, store, and analyze data has never been greater. The need for performance crosses the big data ecosystem toofrom the edge to the server to the analytics software, speed matters. Raghunath Nambiar shares a few use cases that have had significant organizational impact where performance was key.
Choice Hotels's journey to better understand its customers through self-service analytics

Choice Hotels's journey to better understand its customers through self-service analytics

December 14, 2019

Narasimhan Sampath and Avinash Ramineni share how Choice Hotels International used Spark Streaming, Kafka, Spark, and Spark SQL to create an advanced analytics platform that enables business users to be self-reliant by accessing the data they need from a variety of sources to generate customer insights and property dashboards and enable data-driven decisions with minimal IT engagement.
Cloud computing and big data

Cloud computing and big data

December 14, 2019

Ben Sharma uses popular cloud-based use cases to explore how to effectively and safely leverage big data in the cloud to achieve business goals. Now is the time to get the jump on this trend before your competition gets the upper hand.
File format benchmark: Avro, JSON, ORC, and Parquet

File format benchmark: Avro, JSON, ORC, and Parquet

December 13, 2019

Picking the best data format depends on what kind of data you have and how you plan to use it. Owen O'Malley outlines the performance differences between formats in different use cases and offers an overview of the advantages and disadvantages of each to help you improve the performance of your applications.
Hadoop in the cloud: A Nielsen use case

Hadoop in the cloud: A Nielsen use case

December 12, 2019

Cloudera CEO Tom Reilly and James Powell, global CTO of Nielsen, discuss the dynamics of Hadoop in the cloud, what to consider at the start of the journey, and how to implement a solution that delivers flexibility while meeting key enterprise requirements.
How a Spark-based feature store can accelerate big data adoption in financial services

How a Spark-based feature store can accelerate big data adoption in financial services

December 12, 2019

Kaushik Deka and Phil Jarymiszyn discuss the benefits of a Spark-based feature store, a library of reusable features that allows data scientists to solve business problems across the enterprise. Kaushik and Phil outline three challenges they facedsemantic data integration within a data lake, high-performance feature engineering, and metadata governanceand explain how they overcame them.
How to achieve zero-latency IoT and FSI data processing with Spark

How to achieve zero-latency IoT and FSI data processing with Spark

December 11, 2019

Yaron Haviv explains how to design real-time IoT and FSI applications, leveraging Spark with advanced data frame acceleration. Yaron then presents a detailed, practical use case, diving deep into the architectural paradigm shift that makes the powerful processing of millions of events both efficient and simple to program.
Machine-learning techniques for class imbalances and adversaries

Machine-learning techniques for class imbalances and adversaries

December 11, 2019

Many areas of applied machine learning require models optimized for rare occurrences, such as class imbalances, and users actively attempting to subvert the system (adversaries). Brendan Herger offers an overview of multiple published techniques that specifically attempt to address these issues and discusses lessons learned by the Data Innovation Lab at Capital One.
Stream analytics in the enterprise: A look at Intels internal IoT implementation

Stream analytics in the enterprise: A look at Intels internal IoT implementation

December 10, 2019

Moty Fania shares Intels IT experience implementing an on-premises IoT platform for internal use cases. The platform was designed as a multitenant platform with built-in analytical capabilities and based on open source big data technologies and containers. Moty highlights the lessons learned from this journey with a thorough review of the platforms architecture.
Triggers in Apache Beam (incubating)

Triggers in Apache Beam (incubating)

December 9, 2019

Triggers specify when a stage of computation should emit output. With a small language of primitive conditions, triggers provide the flexibility to tailor a streaming pipeline to a variety of use cases and data sources. Kenneth Knowles delves into the details of language- and runner-independent semantics for triggers in Apache Beam and explores real-world implementations in Google Cloud Dataflow.