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Kon Leong, CEOwww.ZLTI.com

Turning The RIM Tide: How To Channel The Data Tsunami

Into A Data Lake

2015May 18th, 2:30 PM

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Turning the RIM Tide:How To Channel The Data Tsunami Into A “Data Lake”

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● The 3 Steps To The Data Lake 1. Gather All The Data 2. Enable All The Functions 3. All Together Now – The Data Lake

● Rethinking RIM … Again

● Back To The Future From IG To Information Management

● Case Studies

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Unified Collection of Unstructured Big Data

All D

ata

Type

s

E-mail Exchange, Lotus

Share-Point,Quickr

FileSystemXML

Black-berry

Bloom-berg IM

PST/NSFMIMEMSG OCS ECM Fax

SocialMedia

≡Al

l Col

lecti

on

Mod

es

ProactiveArchiving(by policy)

Index In-Place(without storing

a copy)

Reactive Archiving(on demand)

UNIFIEDCollection

Data-in-the-Cloud

Data-On-Premise

All D

ata

Loca

tions

Office365, Gmail, Salesforce, etc.

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Governance Functions

Reduce Storage Overload

User Need

Corporate / Gov’t Compliance - 100% Capture, Index, Store, Search - Tamper-Proofing - Monitoring & Surveillance

Litigation Support, eDiscovery* - Search, Hold, Attorney-Client - Save Discovery Costs - Case Management

Stay In Control, Minimize R.O.I.

Support Litigation, Slash Costs

Records Retention Management* - Enable Electronic Records Retention - Enforce Doc Level Granular Policy

Manage Electronic Corporate Records

Solution

Corporate eMemory Mgmt* - Enable Enterprise Data Mining - “Classified” Secure Access, Audits

“Big Data” Analyticsfor Competitive Advantage

“Silos” = duplicates

Storage Management* - Dedupe/Offload Large Email/Files - Avoid Storage Quota / Admin O’H - End-User Access, Productivity

10X

≡

2000

2002

2005

2008

2012

; inconsistent search; disjointed retention

circa

; differing viewsloss of data control Solution: Unified Archive: One Copy, One Policy Control Point, One Search, One View

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Getting It All Together

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● UNIFIED Applications e-Discovery

Compliance

Records

Storage

Analytics

One central console

Single data copy

No data moved between apps

● UNIFIED Architecture One Data Copy

One Policy Control Point

One Search

One Data Schema

Much Lower Admin O’H

Much Lower Storage Costs

Much Faster Performance

DATA CONTROL

● UNIFIED Data Types DominoExchange,

Files, ECM, ERP, Twitter,

IM, Soc.Media, Salesforce

Ingest all data types

All stored together, no silos

Notes/Exchange – no migration

Benefits

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The Architecture At 30,000 Feet

Exte

rnal

Dat

a

Hadoop, eDiscovery & Other Ecosystems

Analytics*

Storage

Records*

Compliance

E-Discovery*

Cloud Options

Hadoop-compatible Infrastructure

Dat

a M

anag

emen

t Lay

erak

a “D

ata

Lake

”

Unified ArchiveRepository must scale to BILLIONS of items

ONE Copy/Policy/Search/Data Schema/System

Capture: Single Instance │ Copy │In-Place │ Crawl │ Stub │ Classify │ OCR │ Encrypt │ Compress │ Restore

farm

Event LogsSys/Net Logs

Structured DataERP, BI,

STRU

CTU

RED

≡D

ata

Crea

tion

Laye

r

RIM

e-D

Storage

Analytics

IMSharedFiles

Share-Point

PSTNSF

ECM SocialMedia

EmailExchange, Domino

UN

STRUCTU

RED

Salesforce, Gmail

“lake”

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As one of the top broker-dealers in the U.S., this firm manages over 30,000 broker-dealers and employees. The company needed to manage files and email for SEC compliance, e-discovery, records management and storage optimization. Previous solutions were unstable and did not meet minimum requirements.

Challenge

Satisfied SEC compliance requirements on document retention, while cutting costs

Provided highly available access

Reduced server counts by 75%, while significantly increasing throughput

Centralized data flow from multiple silos

Solved multiple data coherency issues caused by silos under one unified system

Expected boost in marketing and management performance through analytics

Value

Deployed Unified Data Management Platform to provide compliance, e-discovery and records management for files, email and many other file types. Currently, evaluating early use cases for Analytics.

Solution

≡

Files, Email, IM, Bloomberg, Social Media Compliance, Records, e-Discovery

A Top Wealth Management FirmCASE

STUDY

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eTrash

Non-Records

Records

eTreasure?or

“Big Data Analytics” “Data Lake”

“Unified Repository”

Retention?

AccessPrivileges?

Classification?

Audit?

0% 100%Need for R I M

Scope of New Records Management

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The Future Of RIM

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Analytics

The Power of Unstructured BIG DATA

Legal Compliance

IT Records

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Who Will “Own” It?

Acquisition: Committee

Ownership: GC, CRO, CCO, IT

Operation: IT, RIM, GC, CCO

Analytics: CDO, CDS, 3rd Party

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Turning the RIM Tide:How To Channel The Data Tsunami Into A “Data Lake”

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● Avoid Data Silos

● Take A Unified Approach 1. Add Info Governance 2. Add Analytics

● Expand Scope Of RIM

● Prepare For Life Beyond IG

SUMMARY

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Kon Leong, CEOwww.ZLTI.com

Turning The RIM Tide: How To Channel The Data Tsunami

Into A Data Lake

2015

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to cost-justify the archive.

Analytics for Strategic Advantagewith Corporate eMemory®

CO

MP

LIA

NC

E

E-D

ISC

OV

ER

Y

ES

TO

RA

GE

RE

CO

RD

S

“Unified Archive”Unstructured / Structured Big Data

There are already 4 ROIs

AnalyticsUse Cases

Reduce Costs

and Risks

(Defensive)

Make Money,

MaximizeValue

(Offensive)*

IP – Prior Art KM

Governance

BoD

HR*SCM

Investigations* R&D Sentiment

Trending Topics Retiree*

Expert Network

Rev Rec

Effectiveness*Sales Analysis*

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Employee Effectiveness

Email

Phone Calls

Documents

Web Logs

Calendars

Influence

Expertise

Leadership

Efficiency

Effectiveness

Powerful Technology Competitive Advantage

Data Sources Inferences

≡

Dial For Priv

Dial For

Priacy

Dial For

Prvacy

Dial For Priacy

Privacy vs. Control

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People Analytics – Early Sample Use Cases

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HR/Sales● Who knows whom?● Who is likely to quit?● Analyze transactions, networks, roles*● When were our last visits to our top twenty clients?● Competitive intelligence on demand● Avg. 1,100 connections per salesperson. Map them.● Reduce the probation period 12 months to 1 month

HR/Expert Network● Who knows what? Domain expert database● Who fixed what when? Replay events, for crisis mgmt., product recalls, product liability● Retain knowledge of retired/moved/former employees● Identify experts, offer contracts

HR/Human Networking● Who knows whom (internal ↔ external)● Strength rankings of client/employee relationships

HR/Productivity/Sentiments● Who are the most productive employees?● Workforce sentiment ● Top Trending Topics

HR/Leadership● Who are the real “go-to” people, the most respected?● Who should be promoted?

Compliance/SarbOx● Revenue recognition detection. Identify side-letters● Detect bribery, collusion, FCPA violations

Security/Threat Prevention● 80% threats come from internal vs. external● Prevention – Detect anomalies vs. benchmark● Information Vectors – Detect Ed Snowdens in progress

Security/Investigations● Ad hoc investigations, organization-wide, in seconds● Replay events, instantaneously

Transparency/Org. Politics● Instantaneous transparency, identify political friction

Post-Merger Integration● Track progress, view bottlenecks, expose politics

R&D Resource Pooling● Coordinate global R&D, leverage past research, eliminate duplication, shorten timeframe● R&D patent / prior art research

Legal● De-dupe legal advice (reduce outside counsel fees)● Reuse legal language, check variances

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Gartner Says Beware of the Data Lake FallacyStamford, Conn., July 28, 2014

Information Leaders Must Understand the Gaps in Data Lake Concept and Take Necessary Precautions

The growing hype surrounding data lakes is causing substantial confusion in the information management space, according to Gartner, Inc. Several vendors are marketing data lakes as an essential component to capitalize on Big Data opportunities, but there is little alignment between vendors about what comprises a data lake, or how to get value from it. 

"In broad terms, data lakes are marketed as enterprise-wide data management platforms for analyzing disparate sources of data in its native format," said Nick Heudecker, research director at Gartner. "The idea is simple: instead of placing data in a purpose-built data store, you move it into a data lake in its original format. This eliminates the upfront costs of data ingestion, like transformation. Once data is placed into the lake, it's available for analysis by everyone in the organization." 

However, while the marketing hype suggests audiences throughout an enterprise will leverage data lakes, this positioning assumes that all those audiences are highly skilled at data manipulation and analysis, as data lakes lack semantic consistency and governed metadata …

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You have to manage your Data Lake – the fallacy of technology being magic

Steve Jones, Capgemini August 5, 2014 (excerpts)

 Gartner published a report calling Data Lakes a fallacy in which they point out many of the issues with an unmanaged Hadoop environment.  It’s a great headline but actually the paper itself raises exactly the points that we made in Capgemini back in 2011 about what companies should be doing in this space.  Back then we published a paper on Mastering Big Data which talked about how data governance was a core requirement to get value out of Big Data.

Gartner raised a very valid point, basically that Hadoop isn’t magic.  Just dumping data into a single repository doesn’t mean that it’s now magically easy to use.  But dismissing data lakes altogether is “throwing the baby out with the bathwater.”  

It’s great that Gartner is highlighting the need for governance and the need for considering both structured and unstructured information in a unified manner. 

At Capgemini, we’ve been championing governance in a Big Data world and it’s great to have Gartner agreeing with us.

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● Lot of labor / time to collect● Data may be old, incomplete● Adds data silos more risk

Working on Dead GrassLiving

Analytics – Today vs. Tomorrow

● Tap into data, instantaneously● Data is up to date, complete● Data is under governance, no silos

Reactive E-Discovery Proactive E-DiscoveryReactive Analytics Proactive Analytics