Having supported Syncsort’s Big Data business for the past seven years, the industry conferences I’ve attended have revolved around Hadoop, Spark, and data lakes. But, last week, I departed from my familiar stomping grounds (Strata Data Conference in NYC, which was held the same week) and hit the road for Washington, DC, home to Splunk .conf2017.
As a newbie – or FTR (first time run) attendee in Splunk speak – I was in good company, as the number of attendees has exploded to almost 7,200 – up from about 5,000 last year. According to Splunk, attendees came from 65 countries and traveled a collective 30 million miles to get there – the equivalent of 60 trips to the moon and back!
Since Splunk describes itself as the “first in delivering ‘aha!’ moments from machine data,” I feel it’s fitting for me to share my own from their conference.
1. Use cases for machine data are limitless.
Everywhere I turned last week – whether it was keynotes, sessions, giant posters, videos or conversations on the show floor – I got the opportunity to hear customers sharing stories about how they use machine data. It was really fascinating to hear the range of uses across industries and roles.
Some of the use cases I found to be most interesting included Twitter feed analytics and enrichment to drive customer engagement, a police department using Splunk to solve cold cases, and several areas of innovation at Dubai Airport. This customer who was featured in the keynote, is using Splunk in a variety of very interesting ways – to reduce energy consumption by 20%, make security lines more efficient, provide the best WiFi service in the world, and eventually to predict exactly when a passenger’s bag will arrive on the baggage claim carousel.
One of the most noteworthy – and definitely the most inspiring – use case discussed was that of the Global Emancipation Network. Through the Splunk4Good project, this non-profit uses Splunk to connect and search data from disparate sources around the world, and make sense of that data, to fight global human trafficking.
2. Machine Learning is going mainstream sooner rather than later.
Machine Learning has been an industry buzz word for a while now – and also took center stage at Strata NYC – but still remains more hype than reality. That’s because, although the benefits can be enormous, implementing machine learning is a big challenge.
Splunk made several announcements at .conf to help make machine learning easier to implement. They’ve added packaged and custom models for predictive analytics in Splunk Enterprise, as well as advanced machine learning capabilities for Splunk ITSI 3.0, Splunk UBA 4.0 and its Machine Learning Toolkit.
Related eBook: Mainframe and Machine Learning for IT Service Intelligence
3. Data is nothing. Action is everything.
Across different industries, roles, use cases – all the participants’ stories had the same theme. Collecting lots of data is great, but it means nothing without tools to help them use that data to identify, investigate and solve problems quickly – and, eventually, with machine learning – anticipate them and adapt before they happen.
During Splunk .conf2017, Syncsort CEO Josh Rogers appeared live from the show floor, discussing two announcements Syncsort made during the event that expand on its success in the Big Iron to Big Data market with its innovative Ironstream product.
While at .conf, we announced a new offering of our own, Syncsort Ironstream® Transaction Tracing, to help organizations improve customer satisfaction with large-scale business services that span mobile, web and mainframe platforms. Ironstream Transaction Tracing integrates with Splunk Enterprise and Splunk ITSI to provide users with an end-to-end view to improve problem identification and better manage SLAs by correlating transactions initiated on mobile and web platforms with detailed z/OS backend transaction processing information.
To learn more about Ironstream Transaction Tracing, watch our recorded webcast: End-to-End Transaction Visibility from Mobile Devices to Your Mainframe