Dale Heath - Data’s dark side turning your information governance nightmare into competitive...

Data’s Dark Side:Turning Your Information Governance

Nightmare into Competitive Advantage

Dale HeathPrincipal Architect

Information Intelligence

INFORMATION IS THE MOST CRITICAL ASSET…

Copyright © 2017 Veritas Technologies LLC

The Truth About Enterprise Data: It’s Simply Unsustainable

26%

62%Dark Data

ROT

12%Clean

We don’t have a cluewhat most of it is.

Much of it goes untouchedand unleveraged.

Data Genomics Index, 2016The Global Databerg Report, 2016

But, we know a good chunkshould be deleted.



Data is Exploding…


We Keep Everything. Forever…

Who is the owner of the data? Who is the inferred owner of this data? Who has access to the data?

What unstructured data do you have throughout the environment?

Why am I keeping this data? Is it redundant? What is the value of the data? Is it critical or sensitive?

Where is my data located? Is it on the correct tier of storage? Could it be migrated to Cloud? Could it be archived?

When is it being accessed? How frequently is it being accessed?

How is the data being used? Is it secured correctly? Does it contain sensitive information?

Who Where

When

HowWhy

Data

What


The Unknows of Unstructured Data

What’s the big deal?

Potential $130k in piracy penalties


What about Piracy as a Business Risk?

File Name Copies Size (MB)

Bridge of Spies 14 47,367

Everest 12 39,000

Steve Jobs 6 19,488

Star Wars Episode 4 10 17,423

The Wolf of Wall Street 8 17,005

Movie Files By Size

Other Movies / TV Series include:

Gotham Mad Men The Big Bang Theory Game of Thrones

Pepper Pig House of Cards The Killing Homeland

Over 700GB of Home viewing on corporate file shares

$11,340Saving


Some Simple Resourcing Examples…

Visibility


Visibility: Information Map Connector Expansion


Retention Management

May 25, 2018

• ‘Right To Be Forgotten’• No more data hoarding• Data accountability

Fines of €20M or 4% of Global Annual Turnover

Bill of Data Protection Act POPIProtection of Personal Information

28 LawsPersonal

Information Protection & Electronic Documents

Act

Australian Privacy

Principles

Data Protection Act• Personal data must be stored

on Russian databases• Register of ‘infringers’ drives

website blocks

Personal Data Protection Act• Do Not Call registry• Protection of data

collection

• Hundreds of laws at the Federal & State level & across industries

• 50 Laws In California alone• FOIIA



Free Tool: Veritas Risk Analyzer

Average total data breach cost is $2.51 million $139 is the average cost per lost or stolen record

Ponemon Institute, June 2017

Financial services per record cost is $232 and have 6% abnormal churn

as a data breach result

‘Improvements in data governance programs will reduce the cost of data breach.’

Cost of Data Breach Study: Australia (2017)


Integrated Relative User Risk Score

Simple Risk Assessment

Understand High Risk Users and the Data They Interact With


User Risk: Visualisation

Social Networking Map Combined with Risk Score Changes Insider Threat Tracking

Proactive Real Time Alerts to Mitigate Damage

Find the Risky Behavior Before it’s a Problem


Insider Threat

Drivers forClassification

Gain insight – sales data, customer communications Knowledge Management

Locate information subject to regulationAutomate retention management Less Compliance Headaches

Less clutter to search Better e‐Discovery

Delete Personal Clutter ‐News Alerts, Social Media Notifications, Linked‐In Less Costly Management


Classification Use Cases


IntegratedClassification

Engine

Large amount of data across different business units.

>1 billion items

Items that contain Medical records, medicare numbers and medical information.

36.3 million items

Items containing Legal and regulatory content.

55.6 million items

Items containing non business data – social media notifications system alerts etc. 10% management & resource reduction

93 million items

Items containing sales and marketing content.

46 million items

Items classified as auto‐reply emails (Out of Office)

24 million items

Real World Classification Example (Large QLD Health Organisation)

Machine Learning based Classification Prioritization

Continuous growth of unstructured data creates a scale problem for inspecting file content

Predictive algorithm uses context to find the data most likely to contain tagged data

Find Personal data more quickly within Dark Data for a quicker time to value


Automated Smart Classification via Machine Learning

Intelligent DataManagement


Intelligent Data Management: Classification Policies

1. Gain Visibility

Determine valueReduce risk

2. Take ActionExecute decisions

Retention management

3. Assume ControlAutomated process

and policy


Three Step Approach: From Nightmare to Competitive Advantage

Thank you!

Dale Heath

[email protected]

0418 424 777

“Insanity is doing the same thing over and over again and expecting different results.”

The Compliance Platform for the Intelligent Enterprise

Dale Heath - Data’s dark side turning your information governance nightmare into competitive...

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