16. That data can be used for
almost anything and by everyone
17. D I F F E R E N T
A S K I N G D I F F E R E N T
O F T H E
Business
Analytics
IT
Operations
Security
Operations
Application
Delivery
Internet of
Things
Enterprise Machine Data Fabric
18. 18
Agenda
18
10:00-10:30 Splunk Security Vision, Strategy & Platform,
James Hanlon, EMEA Security Markets Director, Splunk
10:30-11:00 Customer Use Case
Eric Eifert, SVP Security Services, Darkmatter
11:00-11:30 Break
11:30 -13:00 Splunk for Security & Splunk for IT Operations
George Merhej, Senior Solution Architect, Splunk
13:00-14:00 Lunch
14:00 Event concludes
Fast Time-To-Value – Splunk can be downloaded and installed in minutes. If that’s not fast enough you can get a cloud instance in seconds.
Any Data – Splunk can ingest data from any machine data source. It’s not application, vendor, or hardware specific.
Ask any question – It’s impossible to know all the questions you will ask of your data. Often answering one question leads to another. The schema-on-the-fly approach allows you to ask any question of your data.
Visibility across stack – Because you can ingest this data from any source you can quickly gain visibility across all of them.
One Platform – This is more than log aggregation and search software. Let me show you.
Choose Splunk as a SaaS offering, on-premise or hybrid. You get one universal view of your data.
Looking out into the audience, I can see that most of you have gotten the chance, first hand, to see how much the “connectedness” of our world has changed everything.
Every industry, every business, in every country is experiencing the effects of digitization and change. Our world is in the midst of massive change
This technical renaissance or digital transformation has only just begun and it’s accelerating
Software defined everything, Big data, Web scale, Containerization and microservices, Cloud, Mobile, Analytics, and the world of IoT
Add to this, customer and end user expectations have never been higher
Option 2
Option 2
Option 2
The problem has been getting to and making sense of all this machine data. Until recently, the technology needed to collect, store, monitor and analyze this date was brittle, expensive to stand up and inaccessible to employees not trained as data scientists. Many companies would purge logs after a certain date, for example, losing out on historical events, trending and machine learning opportunities. Companies would routinely throw out what we now know to be a huge asset and the source of invaluable insights, relying instead on traditional BI approaches to data, which focuses on historical analysis of structured transactional data – which is only a small part of the picture. Organizations that use data, including machine data, to make better decisions gain a strategic advantage over their competitors.
For most organizations, teams doing data analysis are looking in the rear-view mirror while trying to drive forward.
They shouldn’t be using last month’s data, it should be real time.
But traditional approaches to collecting, storing and working with today’s (and tomorrow’s) explosion of machine data aren’t up to the task.
That’s where we come in. Spunk’s mission is to make machine data accessible, usable, and valuable to everyone.