Gatwick Airport lands passenger experience & operational efficiency with IoT, analytics and Splunk Cloud.
95% of passengers through security in 5 mins or less.
We’ve all been there, stuck at an airport, flight delayed, watching the departures board, trying to find somewhere to sit down and wanting to set off to where you’re going or just get home. Gatwick Airport, the busiest single runway airport in the world, processing up to 945 flights per day is striving to make this situation a thing of the past. I’m delighted to announce that they are using data from the Internet of Things and Splunk Cloud to improve the passenger experience and enhance operational efficiencies across the airport. Gatwick are using their machine data to deliver historic, real-time and predictive analytics to ensure a faster journey through the …
ING Bank at Gartner Symposium. Delivering business value from operational insights.
Last week was EMEA’s Gartner Symposium and it was a pretty busy week. Thousands of CIOs, senior IT leaders and IT companies converged on a very windy Barcelona. We were lucky enough to have ING Bank speaking about how it uses Splunk to deliver business value from IT and ensure its customers are happy. ING Bank Slaski in Poland has over four million customers monitored by Splunk. ING’s IT goal is to make sure they are listening to the voice of the customer “to stay a step ahead in life and business” by:
- Making it clear and easy to use ING’s banking services
- Allowing customers access to those services anytime and anywhere
- Empowering users to self serve and make use
Monitoring the customer experience in real time
Customer eXperience (CX) is the No 1 priority for companies who have invested in analytics software, according research conducted by Gartner. The goal for any company is to have an ‘always on’ view of how their operational performance impacts on the way that customers experience their brand across all touchpoints. This is now possible by using previously untapped machine data in combination with more traditional measures of customer satisfaction e.g. Net Promoter Score (NPS) generated from market research.
Many companies already have Voice of the Customer (VoC) programmes in place which capture Transactional NPS for key interactions / channels and store them in either an Enterprise Feedback Management (EFM) platform, a Business Intelligence (BI) tool or sometimes a tailor made …
How advances in technology are enabling data-driven decision making in retail
I spoke at a retail trends briefing yesterday organized by Cisco, where technology and innovation were very much the focus of all presentations.
It was clear that technological advances are moving extremely quickly. We learnt about: wireless networks that pinpoint customers’ precise location in store1; footfall tracking sensors that can be configured to track the customer journey around the store2; and apps that allow you to pay for any item and leave the shop without visiting a till3. These advances will deliver new and increasingly rich data sources that can be used to power analytics and deliver insights to retail businesses, especially when combined together.
As a result, the range of data sources that …
How to: Splunk Analytics for Hadoop on Amazon EMR.
Using Amazon EMR and Splunk Analytics for Hadoop to explore, analyze and visualize machine data
Machine data can take many forms and comes from a variety of sources; system logs, application logs, service and system metrics, sensors data etc. In this step-by-step guide, you will learn how to build a big data solution for fast, interactive analysis of data stored in Amazon S3 or Hadoop. This hands-on guide is useful for solution architects, data analysts and developers.
This guide will see you:
- Setup an EMR cluster
- Setup a Splunk Analytics for Hadoop node
- Connect to data in your S3 buckets
- Explore, visualize and report on your data
You will need:
- An Amazon EMR Cluster
- A Splunk Analytics for Hadoop Instance
Splunk your Google Analytics
Gain more insight into site performance and user activity by correlating Google Analytics data within Splunk.
A customer of mine recently wanted to understand more about the journey that retail consumers take when they arrive at its website. They recognized that consumers who have previously bought from the site will have more familiarity with the design and layout than those visiting the site for the first time. In addition, consumers who went directly to the site would have a greater brand engagement than those who were referred from an affiliate site.
If only we could implement a method to back up the data that gets submitted to Google Analytics, also sending it back to the local Apache web server logs …
I’m sensor-ing that the fourth industrial revolution is going to be data driven
I was lucky enough attend the IoT World conference this week in Berlin. Everyone who is anyone in Industrial IoT and the associated software industry was present. The list of speakers included Bosch, GE and Vodafone among many others.
During the course of the two days at the event I had a conversation with a robot (see below), I visited a pre-war ballroom and I received a cocktail from two juggling bar tenders! However the most memorable moment came during the key note speech from Professor Whalster, one of the founders of Industry 4.0 movement – which is alternatively known as the fourth industrial revolution.
In simplistic terms, Industry 4.0 is focussed on the “smart factory” i.e the computerisation of manufacturing. …
Detect IoT anomalies and geospatial patterns for logistics insights
In part 1 of this blog series we spoke about how to turn sensor data into logistics insights. In this part we outline one approach for anomaly detection and enrich our sensor data with location information to discover geospatial patterns.
Anomalies? Find them with a few lines of SPL.
Anomaly detection can be tricky and implementations vary from simple thresholding and baselining to highly sophisticated approaches based on machine learning. In this example we leveraged the Splunk Machine Learning Toolkit to detect numeric outliers using a sliding window approach to check against multiples of the standard deviation in this time series to spot anomalies.
And that’s how the SPL looks like:
| timechart span=1s avg(ax) as avx avg(ay) as
Turn IoT sensor data into Operational Intelligence for logistics
The Internet of Things (IoT) wave may impact businesses and industry verticals differently but with the same potential: IoT opens new doors to interesting use cases that have immediate business impact and value. Splunk has delivered Operational Intelligence and Analytics in IT and Security for years, so why not apply Operational Intelligence and Analytics to IoT?
Referring to the general definition of IoT we consider an object that is connected to the internet, in our case data coming from a sensor which measures acceleration. One use case I want to walk through here is not new to logistics, but a great example to show the value in IoT. As the diagram above depicts the globalized delivery of goods takes place …
If your plants could speak to you, what would they say?
I’m pretty sure mine would say “Hey Bozo, thanks for drowning me to death” or “Must… have… water… What is this, the Sahara?” Oh, and also “I hate it here, what’s it take to get some morning sun?”
I decided it was time to apply my inner nerd to reduce my plants suffering. That and happier plants mean a happier fiancé. Enter Splunk! The goal was:
- Keep track of moisture level in the soil.
- Determine best location for light intake.
- Combine current weather data, future forecasts and 1 and 2 above to create some machine learning models that predict when is best to water. (I’m still working on this part)
I shall call it… Operational Plantelligence! When first said aloud, …