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Content Analytics for Legacy Data Retention

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Presentation on theme: "Content Analytics for Legacy Data Retention"— Presentation transcript:

1 Content Analytics for Legacy Data Retention
The Dayhuff Group has a long history of providing enterprise content management solutions in a wide variety of industries. In business since 1997 IBM Premier Business Partner Software ValueNet Partner Over 180 projects at 80 companies 96% customer satisfaction rating Content Analytics for Legacy Data Retention The Dayhuff Group

2 The information lifecycle governance problem
98% $3M 17% Companies that cite defensible disposal as key result of governance programs Average cost to collect, cull and review information per legal case1 Amount of IT budget spent on storage3 22% 70% 44x Companies that can defensibly dispose today Portion of information unnecessarily retained2 Projected information growth,

3 Watson and IBM ECM Today
Natural Language Processing (NLP) is the cornerstone to translate interactions between computers and human (natural) languages Watson uses IBM Content Analytics to perform critical NLP functions Unstructured Information Management Architecture (UIMA) is an open framework for processing text and building analytic solutions Several IBM ECM products leverage UIMA text analytics processing: IBM Content Analytics OmniFind Enterprise Edition IBM Classification Module IBM eDiscovery Analyzer

4 Going from raw information to rapid insight
Uncover business insight through unique visual-based approach Aggregate and extract from multiple sources Organize, analyze and visualize Search and explore to derive insight … to form large text-based collections from multiple internal and external sources (and types), including ECM repositories, structured data, social media and more. … enterprise content (and data) by identifying trends, patterns, correlations, anomalies and business context from collections. … from collections to confirm what is suspected or uncover something new without being forced to build models or deploy complex systems.

5 Why Content Analytics? #1 problem all accounts have, “don’t know what content they have” #2 problem “Uncontrollable Storage Cost” Want to discover the value that may exist in their existing information / content resources Want to know who, where, when & how to leverage their information / content assets Believe they too can demonstrate a three month return on investment Non-threatening to IT Low Cost investment Content Analytics “Try & Buy”

6 LEVEL 5 (Transformational)
Content Analytics Necessary Information Unnecessary Content In The Wild Content Analytics Dynamically analyze to know what you have Aggregate, correlate, visualize and explore your enterprise information to make rapid decisions about business value, relevance and disposition. Decommission what’s unnecessary Cut costs and reduce risk by eliminating obsolete, over-retained, duplicate, and irrelevant content – and the infrastructure that supports it. Preserve and exploit the content that matters Collect valued content to manage, trust and govern throughout its lifespan … policies that use rule-based metadata, advanced contextual classification, and advanced content analytics Slide 5: Charts and Graphs Use this slide when displaying charts or graphs that fill the slide. LEVEL 5 (Transformational) 6

7 How to decommission and preserve content
Identify Content Sources to be assessed IT Initial Assessment to decommission irrelevant content LOB Specific Assessments to decommission over-retained and obsolete content … and to collect and classify valued and obligated content. System and Application decommissioning by IT Periodic audits by IT and LOB keep content environments optimized. 5 Periodic Audit 1 2 3 4 Identify Content Sources Initial Assessment Specific Assessments System & Application Decommissioning Content Collection Content Collection

8 Content Collection w/ Content Classification
Content Analytics and RIM Step 1: Identify content sources Step 2: Exploration Examine sources and analyze content Records manager uses interface to explore & identify value-based content categories Define policies expressing required actions (delete, move, copy, ...) based on categories Step 3: Archival and Management of content IT manager encodes policies content collection mechanism Content identified by exploration process is collected Content collection is executed in an ongoing basis, as prescribed by policies Supports Selective Content Decommissioning: Operate on a subset of content in the original source Identify & extract records across the enterprise 1 Legacy ECM File SharePoint File 2 Content Exploration Content Collection w/ Content Classification 3 Policies Slide 5: Charts and Graphs Use this slide when displaying charts or graphs that fill the slide. Trusted ECM 8

9 Step 1: Identify content sources in the wild
Content Analytics and Dynamic ESI Collection 1 Step 1: Identify content sources in the wild Step 2: Exploration Examines sources and analyzes content IT or Legal user explores & identifies content relevant to case User determines content to be collected into a case set and invokes collection process Collection tool (embedded ICC) copies identified content into ECM evidence repository Step 3: eDiscovery Cull, hold, audit-track, export ESI Analytics-driven Early Case Assessment across all relevant evidentiary ESI Content Analytics Multi-case Evidentiary ECM based Dynamic on demand reactive collection requests Policy based collections 2 Content Collection Slide 5: Charts and Graphs Use this slide when displaying charts or graphs that fill the slide. 3 eDiscovery Tools 9

10 Unlock valuable insight from content What our clients are doing with Content Analytics

11 Basic questions to consider regarding content
Know your content Accelerate time to knowledge by providing greater accuracy and more complete business context with enterprise search Dynamically analyze what you have, decommission the unnecessary, and preserve the content that matters with content assessment Do we know what we have and can we find it? Is it properly managed and can we trust it? What does it all mean and how can we benefit from it? Trust your content Manage and govern content in trusted repositories, not in suspect environments, enabling confidence in your content Create and manage 360 degree trusted content views to enrich master data by connecting to enterprise content Leverage and Exploit your content Interactively discover content to derive unexpected business insights and take action with content analytics Exploit content analytics insights by enriching BI and predictive analytics as well as tailoring for industry and customer specific scenarios

12 Content Analytics for Legacy Data Retention
Addresses Two Objectives: Securely Retain Records Requiring Retention Defensibly Decommission duplicate, non-business and information which has satisfied its retention requirements One LARGE ROI: Storage Cost Savings ROI in less than 3 months $44m in Storage Savings for one client And Delivers

13 How CA for Legacy Data Retention Delivers
I need to dynamically collect electronically stored information (ESI) by knowing what I have, sorting out the case relevant information, declare a records and bring under hold management or decommission as necessary Content Assessment enables content-based decision making for: Decommissioning for cost savings – selected content or entire sources Dynamic collection Records Management for eDiscovery Ongoing proactive information governance Improving metadata & content organization Reduce Storage Cost

14 Content Analytics Admin
Content Sources File Systems Content Repositories Databases Collaboration Web Content Web Pages Portals Content Integration (custom crawlers) ...

15 Content Analytics Admin
Parse and Index Content Linguistic understanding of your content Industry and business specific dictionaries Understanding of Named Entities People, Places, Companies Integration with Classification Module Deep concept analysis Annotators specific to industry, business and specific uses Record Types Industry and company specific concepts Business specific concepts such as Employee Names , Products, etc. . . .

16 Content Analytics for Legacy Data Retention - How it works
Analyzed Content (and Data) Financial Record to be Declared Extracted Concept Trade Action Day Reason Adjective Verb Noun Prep Phrase stocks rose Monday on comments from ... Source Information Internal (ECM, Files, DBMS, etc.) and External (Social, News, etc.) Automatic Visualization for Interactive Exploration and Assessment

17 Content Analytics for Defensible Decomissioning – How it works
Analyzed Content (and Data) Non-record Decomissionable Extracted Concept Element of a plant Vegetation Reason Action Noun Noun Verb Noun stocks on the plants require trimming ... Source Information Internal (ECM, Files, DBMS, etc.) and External (Social, News, etc.) Automatic Visualization for Interactive Exploration and Assessment

18 Classification Process for Legacy Data Retention
Analyze Collect information & context needed to make an inform a decision (declare vs. decommission) Decide Assess the collected information and select a category (declare vs. decommission), accurately & repeatably Take Action Use the selected category to determine & initiate an appropriate response (declare vs. decommission) Ensure actions are taken consistently & correctly, creating defensible process Enforce

19 Content Analytics for Legacy Data Retention
Solution Overview IBM ECM 4 Enterprise Records 1 2 Content Collectors Content Analytics Electronic Discovery Classification Module 5 3

20 Demonstration of Content Analytics for Legacy Data Retention
Content Analytics for Legacy Data Retention is a solution to inventory and locate legacy data requiring retention or disposition The Dayhuff Group has created this solution using IBM Content Analytics tools to perform the heavy lifting of mining legacy information It allows data retention analysts to view and analyze their source content based on familiar concepts such as how the content fits into records series’ within their file plan

21 Facets – Record Types This view exposes facets which categorize the content based on the business’ record types within record series’

22 Select documents to Decommission or Declare
The analyst can graphically see content that is past it’s retention period available for decommissioning

23 Flag as Past Retention period
Documents are flagged based on their retention requirements identified using Content Analytics and the Record Type facets, then exported to Content Collector

24 decommissioned based on analysis results in Content Analytics
Collect to IER Content Collector Documents are decommissioned based on analysis results in Content Analytics or archived to Enterprise Records Decommission Unnecessary Content ECM Records Retention Programs & Policies

25 IBM Enterprise Records
Finance accounts payable treasury Budget & forecast payroll Documents are declared as records in Enterprise Records matching Record Type Facets analyzed in Content Analytics cash management Financial reporting tax accounts receivable customs general accounting insurance Cost accounting Sales & Marketing sales marketing communication dealer support product management market research Service warranty administration customer service quality assurance Legal

26 Content Analytics for Legacy Data Retention
Benefits: Reduced risk Increased productivity Quantifiable and measurable results Reduced cost Defensible process for evaluation Reduction of information through disposition Reduction of duplicated and old information


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