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Make Your Data Dance

Make Your Data Dance. Demystifying Data Analytics & Visualization. Today’s Agenda. This guy? Definition & Discussion: “Big Data Hype” What is an analytic? How do we visualize Demo: of Data Analytics and Visualization Questions/Discussion. My Wife!. This Guy?. Creepy Kids.

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Make Your Data Dance

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  1. Make Your Data Dance Demystifying Data Analytics & Visualization

  2. Today’s Agenda • This guy? • Definition & Discussion: “Big Data Hype” • What is an analytic? • How do we visualize • Demo: of Data Analytics and Visualization • Questions/Discussion

  3. My Wife! This Guy? Creepy Kids My Wife Made

  4. Big Data or Big Hype? • Its everywhere • We all hear it, but what does it mean? • Does it really mean anything or is it just more marketing hype? • Is bigger really better?

  5. Logs Logs Everywhere • How many logs do we have now? • Too many to count • Not just on your file system, but in traffic too! • Human – Human • Machine – Human • Machine - Machine • Linux/Unix/Mac(BSD) • Microsoft • Bro Logs • Or plain Netflow generation • Snort or other IDS • Switches/Routers

  6. What do you do with all this?

  7. Get Them In Your Database • How do you decide which logs you want? • Compliance • Policy • Curiosity • Just because • Normalization • On the fly (streams) • On the remote/local file system (batch)

  8. Some Free Tools To Help • Tools for Transport: • Flume, fluentd, rsyslog, syslog-ng, sqoop, logstash • Tools for Storage: • Note: Relational/Non-relational is important • mySQL, cassandra, Hadoop (HDFS), Elasticsearch • Degree’s of Wholeness • ELSA, graylog2, Snare

  9. Data is Big... But So What? • All data is not gold • You need a strategy that gets you the right data at the right time

  10. Defining: Analytics • Wikipedia Definition – “the discovery and communication of meaningful patterns in data”

  11. Simply a Question • Simple! • What! • A question?! • I can understand that! • These questions can be used to create • Metrics • Statistics • Network behaviors • These all help the application of Analytics as analytics help are used to create them.

  12. Ask Questions of Your Data • I received an IDS alert, is there other similar behavior on my network that I did not receive an alert for? • I have an IP blacklist, what hosts on my network connected to those IP addresses? • Better yet, is there other similar behavior on my network to non–black-listed IP addresses?

  13. What Other Kinds of Insight • Unpatched Systems • Misconfigured Devices • File access • Rates • Personnel • Visibility • Of your network • Of your hosts

  14. Visualization. • So you normalized and stored the data • You’ve asked good questions of our data with analytics • Now what? • We visualize • But how?

  15. Demo Time!

  16. Questions? Source links in the notes on this slide jlawler@21ct.com

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