data analytics

When BGP meets Big-data

When BGP meets Big-data

January 20, 2020

The Internet is very much alive, with millions of BGP events occurring every day. BGP monitoring and reporting tools have been in use for many years now and are …
FPGA-accelerated data analytics (sponsored by Intel)

FPGA-accelerated data analytics (sponsored by Intel)

January 19, 2020

Microsoft has widely deployed field-programmable gate arrays (FPGAs) for accelerating search, networking, and machine learningwith a little help from Intel's software expertise and its FPGA programmers. Mike Strickland explains how a single FPGA can deliver significant acceleration for multiple workloads.
Overcoming traditional data analytics performance bottlenecks with inline acceleration (sponsored by Intel)

Overcoming traditional data analytics performance bottlenecks with inline acceleration (sponsored by Intel)

January 17, 2020

A new approach to data analytics acceleration is delivering benchmarked performance increases of 3X to 10X+ at the system level for traditional relational and NoSQL databases.
SMACK Stack and Beyond - Building Fast Data Pipelines

SMACK Stack and Beyond - Building Fast Data Pipelines

January 6, 2020

Our world seems to move faster and faster and so are our requirements for data analytics. For many use cases such as fraud detection or reacting on sensor data the response times of traditional batch …
How the separation of compute and storage impacts your big data analytics way of life (sponsored by Micro Focus Security and Big Data Analytics)

How the separation of compute and storage impacts your big data analytics way of life (sponsored by Micro Focus Security and Big Data Analytics)

January 2, 2020

Deepak Majeti explains why the separation of compute and storage has become critical to maximizing the benefits of cloud economics.
How to hire and test for data skills: A one-size-fits-all interview kit

How to hire and test for data skills: A one-size-fits-all interview kit

January 2, 2020

Given the recent demand for data analytics and data science skills, adequately testing and qualifying candidates can be a daunting task. Interviewing hundreds of individuals of varying experience and skill levels requires a standardized approach. Tanya Cashorali explores strategies, best practices, and deceptively simple interviewing techniques for data analytics and data science candidates.
Learning from higher education: How Ivy Tech is using predictive analytics and data democracy to reverse decades of entrenched practices

Learning from higher education: How Ivy Tech is using predictive analytics and data democracy to reverse decades of entrenched practices

January 1, 2020

As the largest community college in the US, Ivy Tech ingests over 100M rows of data a day. Brendan Aldrich and Lige Hensley explain how Ivy Tech is applying predictive technologies to establish a true data democracya self-service data analytics environment empowering thousands of users each day to improve operations, achieve strategic goals, and support student success.
Stream analytics with SQL on Apache Flink

Stream analytics with SQL on Apache Flink

December 30, 2019

Although the most widely used language for data analysis, SQL is only slowly being adopted by open source stream processors. One reason is that SQL's semantics and syntax were not designed with streaming data in mind. Fabian Hueske explores Apache Flink's two relational APIs for streaming analyticsstandard SQL and the LINQ-style Table APIdiscussing their semantics and showcasing their usage.
PNDA: Learn to Bootstrap an Open Source Big Data Platform

PNDA: Learn to Bootstrap an Open Source Big Data Platform

December 28, 2019

Innovation in the big data space is rapid, but combining multiple technologies into an endtoend solution is extremely complex and time consuming. The vision of PNDA, the open source big data analyti …
Unleashing intelligence and data analytics at scale (sponsored by Intel)

Unleashing intelligence and data analytics at scale (sponsored by Intel)

December 28, 2019

Advanced data analytics is reshaping the enterprise with new discoveries, better customer experiences, and improved products and services, all enabled by actionable insight. Ziya Ma shares how Intel is driving a holistic approach to powering advanced analytics and artificial intelligence workloads and unleashing intelligent and scalable insights from the edge to the cloud to the enterprise.
What I learned from teaching 1,500 analytics students

What I learned from teaching 1,500 analytics students

December 28, 2019

Engaging, teaching, mentoring, and advising mature, mostly employed, often enthusiastic and ambitious adult learners at University of Toronto has taught Jerrard Gaertner more about analytics in the real world than he ever imagined. Jerrard shares stories he learned about everything from hyped-up expectations and internal sabotage to organizational streamlining and creating transformative insight.
GeoNotebook: An extension to the Jupyter Notebook for exploratory geospatial analysis

GeoNotebook: An extension to the Jupyter Notebook for exploratory geospatial analysis

December 23, 2019

Chris Kotfila offers an overview of the GeoNotebook extension to the Jupyter Notebook, which provides interactive visualization and analysis of geospatial data. Unlike other geospatial extensions to the Jupyter Notebook, GeoNotebook includes a fully integrated tile server providing easy visualization of vector and raster data formats.
Achieve predictable performance (sponsored by Intel)

Achieve predictable performance (sponsored by Intel)

December 17, 2019

Alex Grbic explains how a single FPGA can deliver significant acceleration for multiple workloads. This new approach of integrating data analytics frameworks and existing databases enables enterprise customers to run unmodified applications without requiring any FPGA expertise and can be used with unstructured, NoSQL, and traditional relational databases, such as Swarm64.
Building deep learning-powered big data

Building deep learning-powered big data

December 4, 2019

Radhika Rangarajan explains how Intel works with its users to build deep learning-powered big data analytics applications (object detection, image recognition, NLP, etc.) using BigDL.
Data wrangling for insurance

Data wrangling for insurance

December 4, 2019

Drawing on use cases from Trifacta customers, the speaker explains how to leverage data wrangling solutions in the insurance industry to streamline, strengthen, and improve data analytics initiatives on Hadoop.
Lessons from piloting the London Office of Data Analytics

Lessons from piloting the London Office of Data Analytics

December 2, 2019

Eddie Copeland shares lessons learned from piloting the London Office of Data Analytics, a collaboration between the Greater London Authority, Nesta, and ASI Data Science that is exploring the potential of applying data analytics to reform public services.
Machine learning is a moonshot for us all (sponsored by Google)

Machine learning is a moonshot for us all (sponsored by Google)

December 2, 2019

Data analytics and machine learning are the drivers of the fourth industrial revolution. As technologists, we stand on the brink of incredible opportunity. Darren Strange explores the tremendous opportunity we have before us and asks, will we be pioneers creating new possibilities or will we hold on to the past?
Real-time intelligence gives Uber the edge

Real-time intelligence gives Uber the edge

December 1, 2019

M. C. Srivas covers the technologies underpinning the big data architecture at Uber and explores some of the real-time problems Uber needs to solve to make ride sharing as smooth and ubiquitous as running water, explaining how they are related to real-time big data analytics.
Stream analytics with SQL on Apache Flink

Stream analytics with SQL on Apache Flink

November 30, 2019

Although the most widely used language for data analysis, SQL is only slowly being adopted by open source stream processors. One reason is that SQL's semantics and syntax were not designed with streaming data in mind. Fabian Hueske explores Apache Flink's two relational APIs for streaming analyticsstandard SQL and the LINQ-style Table APIdiscussing their semantics and showcasing their usage.
The digital twin: Real and gaining ground

The digital twin: Real and gaining ground

November 30, 2019

A digital twin is a virtual model of a product or service that allows analysis of data and monitoring of systems to avert problems before they even occurand even plan for the future by using simulations. Shree Dandekar explores a new cloud-based service from the Honeywell Connected Plant that provides industrial users with around-the-clock monitoring of plant data and rigorous simulations.
Evolving and Supporting Stateful, Multi-Tenant Decisioning Applications in Production [A]

Evolving and Supporting Stateful, Multi-Tenant Decisioning Applications in Production [A]

November 29, 2019

With our adoption of Kubernetes at Capital One, we have simultaneously reduced our application delivery time-to-market while providing a common platform for streaming pipelines. We leverage Kubernetes …
Transport for London: Using data to keep London moving

Transport for London: Using data to keep London moving

November 29, 2019

Transport for London (TfL) and WSO2 have been working together on broader integration projects focused on getting the most efficient use out of London transport. Roland Major and Sriskandarajah Suhothayan explain how TfL and WSO2 bring together a wide range of data from multiple disconnected systems to understand current and predicted transport network status.
How Lufthansa German Airlines is using data analytics to create the next level of customer experience

How Lufthansa German Airlines is using data analytics to create the next level of customer experience

November 5, 2019

The aviation industry is facing a huge pressure in costs as well as a profound disruption in marketing and service. With ticket revenues dropping, increasing customer loyalty is key. Andreas Ribbrock explains how Lufthansa German Airlines uses data science and data-driven decision making to create the next level of digital customer experience along the full customer journey.
Paint the landscape and secure your data center with Apache Spot

Paint the landscape and secure your data center with Apache Spot

November 4, 2019

Cesar Berho and Alan Ross offer an overview of open source project Apache Spot (incubating), which delivers next-generation cybersecurity analytics architecture through unsupervised learning using machine-learning techniques at cloud scale for anomaly detection.
Seven steps to high-velocity data analytics with DataOps

Seven steps to high-velocity data analytics with DataOps

November 2, 2019

Data analysts, data scientists, and data engineers are already working on teams delivering insight and analysis, but how do you get the team to support experimentation and insight delivery without ending up in an IT versus data engineer versus data scientist war? Christopher Bergh and Gil Benghiat present the seven shocking steps to get these groups of people working together.
Using R for scalable data analytics: From single machines to Hadoop Spark clusters

Using R for scalable data analytics: From single machines to Hadoop Spark clusters

October 31, 2019

Join in to learn how to do scalable, end-to-end data science in R on single machines as well as on Spark clusters. You'll be assigned an individual Spark cluster with all contents preloaded and software installed and use it to gain experience building, operationalizing, and consuming machine-learning models using distributed functions in R.