SlideShare a Scribd company logo
1 of 29
Index Engines Introduction
Product Overview
Introducing Index Engines
▪ Amazon partner – supports primary/secondary storage migration via S3
▪ Software company delivering enterprise indexing technology
▪ Direct indexing, reporting and access to backup data
▪ Supports data backed up by IBM, Dell EMC, Veritas, HP, etc.
▪ Cost effective migration from legacy tape to AWS S3
▪ Index Engines Overview
▪ Partners include: Amazon, Dell EMC, EY, FTI
▪ Clients include:
▪ JPMC, Citi, Barclays, TIAA-CREF, State of CA, DOJ, Catholic Health, Cincinnati Children’s, Qualcom, Merck
▪ Patented technology
Copyright Index Engines Inc. 2017 All rights reserved. 2
Unstructured Data & Email in the Enterprise
Documents
Spreadsheets
Presentations
Email
Archives (SharePoint)
Backups (Disk or Tape)
© Index Engines Inc. All Rights Reserved. 2016 3
 Dark data
 Difficult to develop/execute/audit data policies
 Hidden sensitive records/PII
 Unleveraged intellectual property
 ROT – Redundant, obsolete and trivial data
Gartner Recommendations*
Organizations are struggling with uncontrolled data growth. Risk-aware and
cost-conscious organizations are realizing they need a better understanding of
their data in order to:
▪ Effectively reduce the risk and inefficiencies buried in
unstructured data
▪ Better manage data in line with governance and policies
▪ Optimize data management and storage infrastructure
▪ Provide better access to unstructured data
▪ Facilitate business use of data that has previously been
deemed "dark"
© Index Engines Inc. All Rights Reserved. 2016 4
*Market Guide for File Analysis Software Published: 19 September 2016
Index Engines Overview
Know IT
Manage IT
Govern IT
▪ Data Classification & Profiling
▪ Enterprise class indexing software
▪ Metadata, full text, pattern/regex/PII, security ACLs, activity logs
▪ Reporting & classification on user files and email
▪ Defensible Disposition
▪ Delete, copy or migrate
▪ Integrated archiving & preservation
▪ Defensible audit trails and logs
▪ Automation and Monitoring
▪ Ongoing monitoring
▪ Automated management based on policy
▪ Instant access to personal data
Copyright Index Engines Inc. 2017 All rights reserved. 5
MANAGEMENTSEARCH/REPORTINDEX
Index Engines Overview
© Index Engines Inc. All Rights Reserved. 2016 6
Unstructured
Network Data
(NFS, CIFS, NDMP)
Email Servers
(EDB, PST, NSF)
SharePoint
Enterprise Vault
Backup Data
(Tape or Disk)
(IBM, Symantec, CVLT,
HP, EMC, etc.)
Backup
Catalogs
(TSM, NBU, CVLT)
Deduped
Unified
Search of
Data
Stored
Queries
and
Automate
Jobs
Auditable
Continual
Defensible
Disposition
Abandoned
Aged
Redundant
Personal
Risk
Archive
Active
Fast
( Up to 1TB/hr)
Efficient
Index
(5% Footprint)
Supports
Federation
for
Distributed
Data
Classify
Manage
Based
On
Policy
Automate
Schedule
Policies
Archive
Deletion
Cloud
Disk
Index Engines Advantages
Speed
The fastest indexing
engine on the market
today, reaching
speeds up to
1TB/hr/node
High speed queries
across large data sets
Access
Supports the widest
range of enterprise
data sources,
including backup data
Recognizes duplicate
content across
network and backup
data sources
Scale
Extreme scalability, to
PBs, with index
footprint of 5% or less
Supports federated
environments –
locally or
geographically
Flexible
Supports a range of
indexing from light
metadata to full
content
Extensive search and
reporting options
Enterprise
Ready
Active Directory
integration allowing
for reporting by group
membership
Flexible deployment
options
© Index Engines Inc. All Rights Reserved. 2016 7
Built from the ground up as an enterprise-class indexing platform
Search and Reporting Interface
© Index Engines Inc. All Rights Reserved. 2016 8
Client Deployments
Client Business Challenge Index Engines Deployment Benefits
Electronics
Manufacturing
Aged & outdated data requiring
frequent storage capacity upgrades
ROT Clean Up: LAN indexing of 3PBs data.
Delete redundant data/no access in 5+ years
Reclaimed >30% capacity and
eliminated a pending upgrade
Mid-Market
Financial
Risk associated with unmanaged
email (PSTs) and PII on the network
Security Audit: LAN indexing of 100TB of files
and email to find, review and secure PSTs/PII
Mitigated legal risk and supported
regulatory policies
Government
Agency
Support strategy of migrating aged
retention data to lower cost cloud
Cloud Migration: LAN indexing of 500TB of
aged servers, migrating data based to cloud
Reduced data center footprint by 20%
and eliminated aged storage platforms
Global Financial
Backup tape migration of legal hold
email to online archive
Legal Hold: Backup indexing of 200,000 tapes
and restoration of mailboxes to disk archive
Support ongoing litigation, eliminated
large, legacy tape infrastructure
Global
Pharmaceutical
Eliminate legacy tape
infrastructure, go tapeless
Tapeless: Catalog ingestion and tape
indexing/migration of LTR data to disk archive
Eliminate legacy tape infrastructure
and improve time to data for legal
Large
Healthcare
Consolidate non-production backup
catalogs/retire legacy infrastructure
Catalog Consolidation: Catalog ingestion, 75
media servers, report/access data
Faster time to find and access legacy
data in support of regulatory reqs
© Index Engines Inc. All Rights Reserved. 2016 9
LAN Data Overview
LAN Overview
▪ High speed indexing of network files, email, archives (SharePoint)
▪ Comprehensive search, reporting and classification
▪ Intelligent management to support migration and corporate data polices
▪ Supports following use cases:
• Defensible Deletion of aged data
• SharePoint Migration
• Cloud Migration
• Data Profiling & Assessments
• Email Management
• PII/PST & Security Audits
• Archiving & Preservation
© Index Engines Inc. All Rights Reserved. 2016 11
LAN Technology Overview
▪ Only solution on the market to support enterprise class data centers
▪ Agentless NFS/CIFS crawling for in-place indexing of files and email
▪ Supports NDMP for high speed ingestion of data
▪ Rapidly deployable, server or virtual options
▪ Enterprise scalability (5% index footprint) , supports petabytes
▪ Not a sampling of data, full scan of all content
▪ Support distributed environments via federation
▪ Fully integrated indexing, reporting, management and disposition
© Index Engines Inc. All Rights Reserved. 2016 12
ROT Analysis and Disposition
▪ Classify content by metadata
▪ Redundant – based on MD5 hash/document signature or metadata only analysis
▪ Obsolete – Not accessed in more than 3 years
▪ Trivial – Personal multimedia files (photos, iTunes, movies, etc.)
▪ ROT disposition
▪ Defensible deletion
▪ Migrate to lower cost storage/cloud
▪ Archive sensitive content and intellectual property
▪ Monitor data in place and manage based on retention policy
▪ Up to 33% of all data in a shared file server is ROT!
▪ Organization grow storage capacity up to 40% annually!
© Index Engines Inc. All Rights Reserved. 2016 13
Sample Client Deployments
Agriculture
Insurance
Internal auditing of
1,000 user
accounts/10TB data to
safeguard PII (SSN/Bank
Routing)
Key Features: Scale,
customized reporting,
comprehensive indexing
Financial
Holding
Internal auditing of
sensitive documents
across 20TB server
environment
Key Features: Flexible
indexing, speed and
automation, ease of use
Consumer
Goods
Reduce 1PB storage
footprint and migrate
data to the cloud for
LTR.
Key Features: Ease of
deployment, Speed,
PII/Keyword search,
flexible reporting
Technology
Networking
Profile 2.4PB of network
data to support clean up
of ROT and deeper
analysis of specific
content . Phase 2 will
expand to 60PB
Key features: Speed
and scalability,
comprehensive analysis
– not sampling.
Financial
Services
Implement
departmental
chargebacks to support
clean up/management
of 100TB
Key Features: Active
Directory integration,
Speed, automated
indexing, dynamic
reporting
© Index Engines Inc. All Rights Reserved. 2016 14
Backup Data Overview
Catalog Management
Ingestion TSM/NBU/CV/NW catalog
Rebuild HPDP/BUE/ARCServe/etc.
Retire legacy backup software
Use Index Engines to manage,
search and report on catalog
Restore On-Demand
Use Index Engines to search catalog
& find relevant tapes for restore
Index tape with IE, detailed search
for file/email
Restore individual files/email from
tape to disk
Legacy Data Migration
Profile legacy tape data based on
catalog reports
Select data of value for migration, or
single instance of everything
Migrate data from tape to
cloud/disk for LTR
Unlocking Backup
Index Engines’ software ingests and manages non-production backup catalogs
and delivers direct access to tape data without need for original software.
© Index Engines Inc. All Rights Reserved. 2016 16
Why Index Engines
© Index Engines Inc. All Rights Reserved. 2016 17
▪ Retire expensive legacy backup applications, infrastructure (libraries,
servers, etc.) and tape storage
▪ Profile LTR data to understand value and risk
▪ Improve access to legacy data to support legal and compliance
▪ Accelerate SLAs with faster time to data
▪ Migrate and manage LTR data on disk/cloud more effectively
▪ Go tapeless – apply go forward LTR policy on tape or disk backups
Direct Tape Processing
© Index Engines Inc. All Rights Reserved. 2016 18
Create Original
Environment
Restore 100%
of Tape
Content
Index Restored
Content
Dedupe
Results
Search for
Relevant Data
Extract
Relevant Data
(<5%)
Traditional Restore Process
Direct Indexing of
Tape Content
Search for
DeDuped/Relevant
Data
Extract Relevant
Data (<5%)
Automated Approach
100% of Data Moves from Tape
Relevant Data (<5%) Moves from Tape
Use Case 1: Catalog Ingestion/Rebuild
© Index Engines Inc. All Rights Reserved. 2016 19
Backup Catalog Ingestion
TSM NetBackup
Commvault
Maintaining non-production backup software to support restores
Planning on phasing out current backup software
NetWorker
Backup Catalog Rebuild
HP DP ArcServe
BackupExec Others
Consolidated Catalog Metadata
Single management for all backup catalogs
Search, report, manage, access legacy data
Retire legacy backup software
Use Case 2: On Demand Access
© Index Engines Inc. All Rights Reserved. 2016 20
Backup Catalog Ingestion
TSM NetBackup
Commvault
Maintaining non-production backup software to support restores
Planning on phasing out current backup software
NetWorker
Backup Catalog Rebuild
HP DP ArcServe
BackupExec Others
Single management for all backup catalogs
Search, report, manage, access legacy data
Retire legacy backup software
Support ongoing restoration needs (eDiscovery, compliance, etc.)
Tapes are maintained for LTR data
Restore native files and
email
Scan/Index tapes for
detailed search/restore
Search catalog find
relevant tapes/barcodes
Consolidated Catalog Metadata
Use Case 3: Tape to Cloud Migration
© Index Engines Inc. All Rights Reserved. 2016 21
Backup Catalog Ingestion
TSM NetBackup
Commvault
Maintaining non-production backup software to support restores
Planning on phasing out current backup software
NetWorker
Backup Catalog Rebuild
HP DP ArcServe
BackupExec Others
Single management for all backup catalogs
Search, report, manage, access legacy data
Retire legacy backup software
Consolidated Catalog Metadata
Two pass culling: Catalog cull followed by detailed culling
Culled data set or single instance archive migrated to cloud via S3
Legacy tapes are remediated
Analyze catalog, cull tapes
to relevant dataset
Scan/Index tapes for
detailed search/restore
Migrate data to cloud
Scan/Index tapes for
detailed search/restore
Restore native files and
email
Search catalog find
relevant tapes/barcodes
LTR data is managed in online archive containing LTR data
No longer store tapes in offsite storage, recycle the DR tapes
Eliminate the use of tape for LTR
Use Case 4: Go Tapeless
© Index Engines Inc. All Rights Reserved. 2016 22
Backup to Disk
Media Server
TSM NetBackup
Commvault
Backing up to disk, creating tapes off the back end for DR
NetWorker
HP DP ArcServe
BackupExec Others
Search and filter data
Define retention policy
Migrate LTR data from
backup as forensic copy
Index nightly backups
Intuitive Interface
© Index Engines Inc. All Rights Reserved. 2016 23
Hardware
• Servers (NDMP)
• Libraries
• Floor space
Resources
• Manpower
• Data center costs
Backup Software
• Maintenance
• Infrastructure
• Management
SLAs & Restores
• Time to restore data
• 3rd party restore
services
Tape Storage
• Offsite storage costs
• Tape management
• Tape purchases
Risk & Liability
• eDiscovery
• Regulatory
• Long-term risk
Key Performance Indicators
Cost Saving Using Cloud for LTR
0
50000
100000
150000
200000
250000
300000
350000
Business as Usual
(Yearly Costs)
Migration Costs
(One Time Charge)
Transformed Environment
(Yearly Costs)
Copyright Index Engines Inc. 2017 All rights reserved. 25
Backup/Restore Infrastructure Servers, libraries, disk, maint, floor space, staff
Backup Software Maintenance costs, and staffing
Tape Storage Offsite storage costs
Tape Management Cost to retrieve tapes to support legal
Migration Project Software, hardware, services
Cloud Infrastructure Software, hardware to access cloud data
Cloud Storage Costs to store and retrieve data in cloud
Staffing Staff to support cloud archive
BAU
Annual Costs
Migration Costs
One Time Fee
Transformed
Annual Costs
3 Year Savings
ROI
$295,600 $275,000 $100,000 $311,800 (35%)
Classifying and Culling Backup Data
Redundancy 90%!
Aged Data – Outside Retention
Irrelevant Files
User Files
Email
LTR
Option 1:
• Most efficient
• Cull to specific LTR data
• Data on legal hold
• Typically a small subset (1% or less)
Option 2:
• Single instance
• Eliminate duplicates
• Migrate files, email, databases
• A larger subset (10% or more)
Migration Case Study
Client with approximately 5,000 legacy tapes - migrated all
unique files and email from past 3 years to a single instance
archive
▪ 1,000 LTO-4, 2,000 LTO- 3, 2,000 LTO-2 (all NBU, compressed tapes)
▪ Total data storage = 3.6PB
▪ Migrate all unique email, and user documents from past three years.
▪ Cull 30% of tapes (past retention, eliminate incrementals)
▪ Total data remaining = 2.52PB
▪ Total data for migration = 126TB (95% of data duplicate (5% unique))
▪ Utilize four Index Engines servers, four libraries
▪ Data will be migrated to cloud storage in ~9 months
▪ Tapes shredded
▪ Legacy backup software, libraries, and servers retired
© Index Engines Inc. All Rights Reserved. 2016 27
IE Backup Migration Services
▪ Index Engines offers cost effective pricing that includes the
bundled software & services needed
▪ Legacy Data Migration Assurance Program
▪ Tapes remain on premise, IE engineers remotely manage the progress
▪ Client provides hardware and loads tapes
▪ Data Processing Lab
▪ Off premise, turnkey service
▪ IE manages the migration process in our secure lab based on clients
migration requirements
© Index Engines Inc. All Rights Reserved. 2016 28
Questions?
© Index Engines Inc. All Rights Reserved. 2016 29

More Related Content

What's hot

Architect’s Open-Source Guide for a Data Mesh Architecture
Architect’s Open-Source Guide for a Data Mesh ArchitectureArchitect’s Open-Source Guide for a Data Mesh Architecture
Architect’s Open-Source Guide for a Data Mesh ArchitectureDatabricks
 
Cost optimization - Don't overspend on AWS
Cost optimization - Don't overspend on AWSCost optimization - Don't overspend on AWS
Cost optimization - Don't overspend on AWSSandeep Cashyap
 
Best Practices for Architecting in the Cloud - Jeff Barr
Best Practices for Architecting in the Cloud - Jeff BarrBest Practices for Architecting in the Cloud - Jeff Barr
Best Practices for Architecting in the Cloud - Jeff BarrAmazon Web Services
 
CDC patterns in Apache Kafka®
CDC patterns in Apache Kafka®CDC patterns in Apache Kafka®
CDC patterns in Apache Kafka®confluent
 
Building Secure Architectures on AWS
Building Secure Architectures on AWSBuilding Secure Architectures on AWS
Building Secure Architectures on AWSAmazon Web Services
 
Creating the Cloud Business Case
Creating the Cloud Business CaseCreating the Cloud Business Case
Creating the Cloud Business CaseAmazon Web Services
 
FinOps: A Culture Transformation to Bring DevOps, Finance and the Business To...
FinOps: A Culture Transformation to Bring DevOps, Finance and the Business To...FinOps: A Culture Transformation to Bring DevOps, Finance and the Business To...
FinOps: A Culture Transformation to Bring DevOps, Finance and the Business To...Amazon Web Services
 
Full-Stack Observability for IoT Event Stream Data Processing at Penske
Full-Stack Observability for IoT Event Stream Data Processing at PenskeFull-Stack Observability for IoT Event Stream Data Processing at Penske
Full-Stack Observability for IoT Event Stream Data Processing at PenskeVMware Tanzu
 
Data Architecture Best Practices for Advanced Analytics
Data Architecture Best Practices for Advanced AnalyticsData Architecture Best Practices for Advanced Analytics
Data Architecture Best Practices for Advanced AnalyticsDATAVERSITY
 
Building a centralized observability platform
Building a centralized observability platformBuilding a centralized observability platform
Building a centralized observability platformElasticsearch
 
Using AIOps to reduce incidents volume
Using AIOps to reduce incidents volumeUsing AIOps to reduce incidents volume
Using AIOps to reduce incidents volumeAmazon Web Services
 
The Marriage of the Data Lake and the Data Warehouse and Why You Need Both
The Marriage of the Data Lake and the Data Warehouse and Why You Need BothThe Marriage of the Data Lake and the Data Warehouse and Why You Need Both
The Marriage of the Data Lake and the Data Warehouse and Why You Need BothAdaryl "Bob" Wakefield, MBA
 
Azure Cloud Adoption Framework + Governance - Sana Khan and Jay Kumar
Azure Cloud Adoption Framework + Governance - Sana Khan and Jay Kumar Azure Cloud Adoption Framework + Governance - Sana Khan and Jay Kumar
Azure Cloud Adoption Framework + Governance - Sana Khan and Jay Kumar Timothy McAliley
 
DEM14 Extending the Cisco SD-WAN Fabric to the AWS Cloud
DEM14 Extending the Cisco SD-WAN Fabric to the AWS CloudDEM14 Extending the Cisco SD-WAN Fabric to the AWS Cloud
DEM14 Extending the Cisco SD-WAN Fabric to the AWS CloudAmazon Web Services
 
Data Center Migration to the AWS Cloud
Data Center Migration to the AWS CloudData Center Migration to the AWS Cloud
Data Center Migration to the AWS CloudTom Laszewski
 
How to Choose the Right Database for Your Workloads
How to Choose the Right Database for Your WorkloadsHow to Choose the Right Database for Your Workloads
How to Choose the Right Database for Your WorkloadsInfluxData
 

What's hot (20)

Data Domain-Driven Design
Data Domain-Driven DesignData Domain-Driven Design
Data Domain-Driven Design
 
Architect’s Open-Source Guide for a Data Mesh Architecture
Architect’s Open-Source Guide for a Data Mesh ArchitectureArchitect’s Open-Source Guide for a Data Mesh Architecture
Architect’s Open-Source Guide for a Data Mesh Architecture
 
Cost optimization - Don't overspend on AWS
Cost optimization - Don't overspend on AWSCost optimization - Don't overspend on AWS
Cost optimization - Don't overspend on AWS
 
Best Practices for Architecting in the Cloud - Jeff Barr
Best Practices for Architecting in the Cloud - Jeff BarrBest Practices for Architecting in the Cloud - Jeff Barr
Best Practices for Architecting in the Cloud - Jeff Barr
 
CDC patterns in Apache Kafka®
CDC patterns in Apache Kafka®CDC patterns in Apache Kafka®
CDC patterns in Apache Kafka®
 
Building Secure Architectures on AWS
Building Secure Architectures on AWSBuilding Secure Architectures on AWS
Building Secure Architectures on AWS
 
The Benefits of Cloud Computing
The Benefits of Cloud ComputingThe Benefits of Cloud Computing
The Benefits of Cloud Computing
 
Creating the Cloud Business Case
Creating the Cloud Business CaseCreating the Cloud Business Case
Creating the Cloud Business Case
 
FinOps: A Culture Transformation to Bring DevOps, Finance and the Business To...
FinOps: A Culture Transformation to Bring DevOps, Finance and the Business To...FinOps: A Culture Transformation to Bring DevOps, Finance and the Business To...
FinOps: A Culture Transformation to Bring DevOps, Finance and the Business To...
 
Full-Stack Observability for IoT Event Stream Data Processing at Penske
Full-Stack Observability for IoT Event Stream Data Processing at PenskeFull-Stack Observability for IoT Event Stream Data Processing at Penske
Full-Stack Observability for IoT Event Stream Data Processing at Penske
 
Data Architecture Best Practices for Advanced Analytics
Data Architecture Best Practices for Advanced AnalyticsData Architecture Best Practices for Advanced Analytics
Data Architecture Best Practices for Advanced Analytics
 
Building a centralized observability platform
Building a centralized observability platformBuilding a centralized observability platform
Building a centralized observability platform
 
Emc data domain
Emc data domainEmc data domain
Emc data domain
 
Using AIOps to reduce incidents volume
Using AIOps to reduce incidents volumeUsing AIOps to reduce incidents volume
Using AIOps to reduce incidents volume
 
The Marriage of the Data Lake and the Data Warehouse and Why You Need Both
The Marriage of the Data Lake and the Data Warehouse and Why You Need BothThe Marriage of the Data Lake and the Data Warehouse and Why You Need Both
The Marriage of the Data Lake and the Data Warehouse and Why You Need Both
 
Azure Cloud Adoption Framework + Governance - Sana Khan and Jay Kumar
Azure Cloud Adoption Framework + Governance - Sana Khan and Jay Kumar Azure Cloud Adoption Framework + Governance - Sana Khan and Jay Kumar
Azure Cloud Adoption Framework + Governance - Sana Khan and Jay Kumar
 
From Mainframe to Microservices
From Mainframe to MicroservicesFrom Mainframe to Microservices
From Mainframe to Microservices
 
DEM14 Extending the Cisco SD-WAN Fabric to the AWS Cloud
DEM14 Extending the Cisco SD-WAN Fabric to the AWS CloudDEM14 Extending the Cisco SD-WAN Fabric to the AWS Cloud
DEM14 Extending the Cisco SD-WAN Fabric to the AWS Cloud
 
Data Center Migration to the AWS Cloud
Data Center Migration to the AWS CloudData Center Migration to the AWS Cloud
Data Center Migration to the AWS Cloud
 
How to Choose the Right Database for Your Workloads
How to Choose the Right Database for Your WorkloadsHow to Choose the Right Database for Your Workloads
How to Choose the Right Database for Your Workloads
 

Similar to Replacing Tape Backup with Cloud-Enabled Solutions by Index Engines

Cleaning up Redundant, Obsolete and Trivial Data to Reclaim Capacity and Mana...
Cleaning up Redundant, Obsolete and Trivial Data to Reclaim Capacity and Mana...Cleaning up Redundant, Obsolete and Trivial Data to Reclaim Capacity and Mana...
Cleaning up Redundant, Obsolete and Trivial Data to Reclaim Capacity and Mana...Index Engines Inc.
 
Balancing data democratization with comprehensive information governance: bui...
Balancing data democratization with comprehensive information governance: bui...Balancing data democratization with comprehensive information governance: bui...
Balancing data democratization with comprehensive information governance: bui...DataWorks Summit
 
Webinar: Practical Technology Playbook for the GDPR
Webinar: Practical Technology Playbook for the GDPRWebinar: Practical Technology Playbook for the GDPR
Webinar: Practical Technology Playbook for the GDPRIndex Engines Inc.
 
Tackling the GDPR Dell EMC Index Engines Webinar
Tackling the GDPR Dell EMC Index Engines WebinarTackling the GDPR Dell EMC Index Engines Webinar
Tackling the GDPR Dell EMC Index Engines WebinarIndex Engines Inc.
 
ADV Slides: The Evolution of the Data Platform and What It Means to Enterpris...
ADV Slides: The Evolution of the Data Platform and What It Means to Enterpris...ADV Slides: The Evolution of the Data Platform and What It Means to Enterpris...
ADV Slides: The Evolution of the Data Platform and What It Means to Enterpris...DATAVERSITY
 
Hortonworks Hybrid Cloud - Putting you back in control of your data
Hortonworks Hybrid Cloud - Putting you back in control of your dataHortonworks Hybrid Cloud - Putting you back in control of your data
Hortonworks Hybrid Cloud - Putting you back in control of your dataScott Clinton
 
Smarter Data Protection And Storage Management Solutions
Smarter Data Protection And Storage Management SolutionsSmarter Data Protection And Storage Management Solutions
Smarter Data Protection And Storage Management Solutionsaejaz7
 
VILT - Archiving and Decommissioning with OpenText InfoArchive
VILT - Archiving and Decommissioning with OpenText InfoArchiveVILT - Archiving and Decommissioning with OpenText InfoArchive
VILT - Archiving and Decommissioning with OpenText InfoArchiveVILT
 
Got data?… now what? An introduction to modern data platforms
Got data?… now what?  An introduction to modern data platformsGot data?… now what?  An introduction to modern data platforms
Got data?… now what? An introduction to modern data platformsJamesAnderson599331
 
Enterprise content management (in short)
Enterprise content management  (in short)Enterprise content management  (in short)
Enterprise content management (in short)Anatoliy Arkhipov
 
Modern Data Management for Federal Modernization
Modern Data Management for Federal ModernizationModern Data Management for Federal Modernization
Modern Data Management for Federal ModernizationDenodo
 
DAMA & Denodo Webinar: Modernizing Data Architecture Using Data Virtualization
DAMA & Denodo Webinar: Modernizing Data Architecture Using Data Virtualization DAMA & Denodo Webinar: Modernizing Data Architecture Using Data Virtualization
DAMA & Denodo Webinar: Modernizing Data Architecture Using Data Virtualization Denodo
 
Best Practices Using Big Data on AWS | AWS Public Sector Summit 2017
Best Practices Using Big Data on AWS | AWS Public Sector Summit 2017Best Practices Using Big Data on AWS | AWS Public Sector Summit 2017
Best Practices Using Big Data on AWS | AWS Public Sector Summit 2017Amazon Web Services
 
CWIN17 India / Bigdata architecture yashowardhan sowale
CWIN17 India / Bigdata architecture  yashowardhan sowaleCWIN17 India / Bigdata architecture  yashowardhan sowale
CWIN17 India / Bigdata architecture yashowardhan sowaleCapgemini
 
Transforming GE Healthcare with Data Platform Strategy
Transforming GE Healthcare with Data Platform StrategyTransforming GE Healthcare with Data Platform Strategy
Transforming GE Healthcare with Data Platform StrategyDatabricks
 
Track 1 Session 6_建立安全高效的資料分析平台加速金融創新_HC+EMQ Cliff(已檢核,上下無黑邊).pptx
Track 1 Session 6_建立安全高效的資料分析平台加速金融創新_HC+EMQ Cliff(已檢核,上下無黑邊).pptxTrack 1 Session 6_建立安全高效的資料分析平台加速金融創新_HC+EMQ Cliff(已檢核,上下無黑邊).pptx
Track 1 Session 6_建立安全高效的資料分析平台加速金融創新_HC+EMQ Cliff(已檢核,上下無黑邊).pptxAmazon Web Services
 
A Logical Architecture is Always a Flexible Architecture (ASEAN)
A Logical Architecture is Always a Flexible Architecture (ASEAN)A Logical Architecture is Always a Flexible Architecture (ASEAN)
A Logical Architecture is Always a Flexible Architecture (ASEAN)Denodo
 
Data Fabric - Why Should Organizations Implement a Logical and Not a Physical...
Data Fabric - Why Should Organizations Implement a Logical and Not a Physical...Data Fabric - Why Should Organizations Implement a Logical and Not a Physical...
Data Fabric - Why Should Organizations Implement a Logical and Not a Physical...Denodo
 
Why a Data Services Marketplace is Critical for a Successful Data-Driven Ente...
Why a Data Services Marketplace is Critical for a Successful Data-Driven Ente...Why a Data Services Marketplace is Critical for a Successful Data-Driven Ente...
Why a Data Services Marketplace is Critical for a Successful Data-Driven Ente...Denodo
 

Similar to Replacing Tape Backup with Cloud-Enabled Solutions by Index Engines (20)

Cleaning up Redundant, Obsolete and Trivial Data to Reclaim Capacity and Mana...
Cleaning up Redundant, Obsolete and Trivial Data to Reclaim Capacity and Mana...Cleaning up Redundant, Obsolete and Trivial Data to Reclaim Capacity and Mana...
Cleaning up Redundant, Obsolete and Trivial Data to Reclaim Capacity and Mana...
 
Balancing data democratization with comprehensive information governance: bui...
Balancing data democratization with comprehensive information governance: bui...Balancing data democratization with comprehensive information governance: bui...
Balancing data democratization with comprehensive information governance: bui...
 
Webinar: Practical Technology Playbook for the GDPR
Webinar: Practical Technology Playbook for the GDPRWebinar: Practical Technology Playbook for the GDPR
Webinar: Practical Technology Playbook for the GDPR
 
Tackling the GDPR Dell EMC Index Engines Webinar
Tackling the GDPR Dell EMC Index Engines WebinarTackling the GDPR Dell EMC Index Engines Webinar
Tackling the GDPR Dell EMC Index Engines Webinar
 
Benefits of a data lake
Benefits of a data lake Benefits of a data lake
Benefits of a data lake
 
ADV Slides: The Evolution of the Data Platform and What It Means to Enterpris...
ADV Slides: The Evolution of the Data Platform and What It Means to Enterpris...ADV Slides: The Evolution of the Data Platform and What It Means to Enterpris...
ADV Slides: The Evolution of the Data Platform and What It Means to Enterpris...
 
Hortonworks Hybrid Cloud - Putting you back in control of your data
Hortonworks Hybrid Cloud - Putting you back in control of your dataHortonworks Hybrid Cloud - Putting you back in control of your data
Hortonworks Hybrid Cloud - Putting you back in control of your data
 
Smarter Data Protection And Storage Management Solutions
Smarter Data Protection And Storage Management SolutionsSmarter Data Protection And Storage Management Solutions
Smarter Data Protection And Storage Management Solutions
 
VILT - Archiving and Decommissioning with OpenText InfoArchive
VILT - Archiving and Decommissioning with OpenText InfoArchiveVILT - Archiving and Decommissioning with OpenText InfoArchive
VILT - Archiving and Decommissioning with OpenText InfoArchive
 
Got data?… now what? An introduction to modern data platforms
Got data?… now what?  An introduction to modern data platformsGot data?… now what?  An introduction to modern data platforms
Got data?… now what? An introduction to modern data platforms
 
Enterprise content management (in short)
Enterprise content management  (in short)Enterprise content management  (in short)
Enterprise content management (in short)
 
Modern Data Management for Federal Modernization
Modern Data Management for Federal ModernizationModern Data Management for Federal Modernization
Modern Data Management for Federal Modernization
 
DAMA & Denodo Webinar: Modernizing Data Architecture Using Data Virtualization
DAMA & Denodo Webinar: Modernizing Data Architecture Using Data Virtualization DAMA & Denodo Webinar: Modernizing Data Architecture Using Data Virtualization
DAMA & Denodo Webinar: Modernizing Data Architecture Using Data Virtualization
 
Best Practices Using Big Data on AWS | AWS Public Sector Summit 2017
Best Practices Using Big Data on AWS | AWS Public Sector Summit 2017Best Practices Using Big Data on AWS | AWS Public Sector Summit 2017
Best Practices Using Big Data on AWS | AWS Public Sector Summit 2017
 
CWIN17 India / Bigdata architecture yashowardhan sowale
CWIN17 India / Bigdata architecture  yashowardhan sowaleCWIN17 India / Bigdata architecture  yashowardhan sowale
CWIN17 India / Bigdata architecture yashowardhan sowale
 
Transforming GE Healthcare with Data Platform Strategy
Transforming GE Healthcare with Data Platform StrategyTransforming GE Healthcare with Data Platform Strategy
Transforming GE Healthcare with Data Platform Strategy
 
Track 1 Session 6_建立安全高效的資料分析平台加速金融創新_HC+EMQ Cliff(已檢核,上下無黑邊).pptx
Track 1 Session 6_建立安全高效的資料分析平台加速金融創新_HC+EMQ Cliff(已檢核,上下無黑邊).pptxTrack 1 Session 6_建立安全高效的資料分析平台加速金融創新_HC+EMQ Cliff(已檢核,上下無黑邊).pptx
Track 1 Session 6_建立安全高效的資料分析平台加速金融創新_HC+EMQ Cliff(已檢核,上下無黑邊).pptx
 
A Logical Architecture is Always a Flexible Architecture (ASEAN)
A Logical Architecture is Always a Flexible Architecture (ASEAN)A Logical Architecture is Always a Flexible Architecture (ASEAN)
A Logical Architecture is Always a Flexible Architecture (ASEAN)
 
Data Fabric - Why Should Organizations Implement a Logical and Not a Physical...
Data Fabric - Why Should Organizations Implement a Logical and Not a Physical...Data Fabric - Why Should Organizations Implement a Logical and Not a Physical...
Data Fabric - Why Should Organizations Implement a Logical and Not a Physical...
 
Why a Data Services Marketplace is Critical for a Successful Data-Driven Ente...
Why a Data Services Marketplace is Critical for a Successful Data-Driven Ente...Why a Data Services Marketplace is Critical for a Successful Data-Driven Ente...
Why a Data Services Marketplace is Critical for a Successful Data-Driven Ente...
 

More from Amazon Web Services

Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...
Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...
Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...Amazon Web Services
 
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...Big Data per le Startup: come creare applicazioni Big Data in modalità Server...
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...Amazon Web Services
 
Esegui pod serverless con Amazon EKS e AWS Fargate
Esegui pod serverless con Amazon EKS e AWS FargateEsegui pod serverless con Amazon EKS e AWS Fargate
Esegui pod serverless con Amazon EKS e AWS FargateAmazon Web Services
 
Costruire Applicazioni Moderne con AWS
Costruire Applicazioni Moderne con AWSCostruire Applicazioni Moderne con AWS
Costruire Applicazioni Moderne con AWSAmazon Web Services
 
Come spendere fino al 90% in meno con i container e le istanze spot
Come spendere fino al 90% in meno con i container e le istanze spot Come spendere fino al 90% in meno con i container e le istanze spot
Come spendere fino al 90% in meno con i container e le istanze spot Amazon Web Services
 
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...Amazon Web Services
 
OpsWorks Configuration Management: automatizza la gestione e i deployment del...
OpsWorks Configuration Management: automatizza la gestione e i deployment del...OpsWorks Configuration Management: automatizza la gestione e i deployment del...
OpsWorks Configuration Management: automatizza la gestione e i deployment del...Amazon Web Services
 
Microsoft Active Directory su AWS per supportare i tuoi Windows Workloads
Microsoft Active Directory su AWS per supportare i tuoi Windows WorkloadsMicrosoft Active Directory su AWS per supportare i tuoi Windows Workloads
Microsoft Active Directory su AWS per supportare i tuoi Windows WorkloadsAmazon Web Services
 
Database Oracle e VMware Cloud on AWS i miti da sfatare
Database Oracle e VMware Cloud on AWS i miti da sfatareDatabase Oracle e VMware Cloud on AWS i miti da sfatare
Database Oracle e VMware Cloud on AWS i miti da sfatareAmazon Web Services
 
Crea la tua prima serverless ledger-based app con QLDB e NodeJS
Crea la tua prima serverless ledger-based app con QLDB e NodeJSCrea la tua prima serverless ledger-based app con QLDB e NodeJS
Crea la tua prima serverless ledger-based app con QLDB e NodeJSAmazon Web Services
 
API moderne real-time per applicazioni mobili e web
API moderne real-time per applicazioni mobili e webAPI moderne real-time per applicazioni mobili e web
API moderne real-time per applicazioni mobili e webAmazon Web Services
 
Database Oracle e VMware Cloud™ on AWS: i miti da sfatare
Database Oracle e VMware Cloud™ on AWS: i miti da sfatareDatabase Oracle e VMware Cloud™ on AWS: i miti da sfatare
Database Oracle e VMware Cloud™ on AWS: i miti da sfatareAmazon Web Services
 
Tools for building your MVP on AWS
Tools for building your MVP on AWSTools for building your MVP on AWS
Tools for building your MVP on AWSAmazon Web Services
 
How to Build a Winning Pitch Deck
How to Build a Winning Pitch DeckHow to Build a Winning Pitch Deck
How to Build a Winning Pitch DeckAmazon Web Services
 
Building a web application without servers
Building a web application without serversBuilding a web application without servers
Building a web application without serversAmazon Web Services
 
AWS_HK_StartupDay_Building Interactive websites while automating for efficien...
AWS_HK_StartupDay_Building Interactive websites while automating for efficien...AWS_HK_StartupDay_Building Interactive websites while automating for efficien...
AWS_HK_StartupDay_Building Interactive websites while automating for efficien...Amazon Web Services
 
Introduzione a Amazon Elastic Container Service
Introduzione a Amazon Elastic Container ServiceIntroduzione a Amazon Elastic Container Service
Introduzione a Amazon Elastic Container ServiceAmazon Web Services
 

More from Amazon Web Services (20)

Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...
Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...
Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...
 
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...Big Data per le Startup: come creare applicazioni Big Data in modalità Server...
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...
 
Esegui pod serverless con Amazon EKS e AWS Fargate
Esegui pod serverless con Amazon EKS e AWS FargateEsegui pod serverless con Amazon EKS e AWS Fargate
Esegui pod serverless con Amazon EKS e AWS Fargate
 
Costruire Applicazioni Moderne con AWS
Costruire Applicazioni Moderne con AWSCostruire Applicazioni Moderne con AWS
Costruire Applicazioni Moderne con AWS
 
Come spendere fino al 90% in meno con i container e le istanze spot
Come spendere fino al 90% in meno con i container e le istanze spot Come spendere fino al 90% in meno con i container e le istanze spot
Come spendere fino al 90% in meno con i container e le istanze spot
 
Open banking as a service
Open banking as a serviceOpen banking as a service
Open banking as a service
 
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...
 
OpsWorks Configuration Management: automatizza la gestione e i deployment del...
OpsWorks Configuration Management: automatizza la gestione e i deployment del...OpsWorks Configuration Management: automatizza la gestione e i deployment del...
OpsWorks Configuration Management: automatizza la gestione e i deployment del...
 
Microsoft Active Directory su AWS per supportare i tuoi Windows Workloads
Microsoft Active Directory su AWS per supportare i tuoi Windows WorkloadsMicrosoft Active Directory su AWS per supportare i tuoi Windows Workloads
Microsoft Active Directory su AWS per supportare i tuoi Windows Workloads
 
Computer Vision con AWS
Computer Vision con AWSComputer Vision con AWS
Computer Vision con AWS
 
Database Oracle e VMware Cloud on AWS i miti da sfatare
Database Oracle e VMware Cloud on AWS i miti da sfatareDatabase Oracle e VMware Cloud on AWS i miti da sfatare
Database Oracle e VMware Cloud on AWS i miti da sfatare
 
Crea la tua prima serverless ledger-based app con QLDB e NodeJS
Crea la tua prima serverless ledger-based app con QLDB e NodeJSCrea la tua prima serverless ledger-based app con QLDB e NodeJS
Crea la tua prima serverless ledger-based app con QLDB e NodeJS
 
API moderne real-time per applicazioni mobili e web
API moderne real-time per applicazioni mobili e webAPI moderne real-time per applicazioni mobili e web
API moderne real-time per applicazioni mobili e web
 
Database Oracle e VMware Cloud™ on AWS: i miti da sfatare
Database Oracle e VMware Cloud™ on AWS: i miti da sfatareDatabase Oracle e VMware Cloud™ on AWS: i miti da sfatare
Database Oracle e VMware Cloud™ on AWS: i miti da sfatare
 
Tools for building your MVP on AWS
Tools for building your MVP on AWSTools for building your MVP on AWS
Tools for building your MVP on AWS
 
How to Build a Winning Pitch Deck
How to Build a Winning Pitch DeckHow to Build a Winning Pitch Deck
How to Build a Winning Pitch Deck
 
Building a web application without servers
Building a web application without serversBuilding a web application without servers
Building a web application without servers
 
Fundraising Essentials
Fundraising EssentialsFundraising Essentials
Fundraising Essentials
 
AWS_HK_StartupDay_Building Interactive websites while automating for efficien...
AWS_HK_StartupDay_Building Interactive websites while automating for efficien...AWS_HK_StartupDay_Building Interactive websites while automating for efficien...
AWS_HK_StartupDay_Building Interactive websites while automating for efficien...
 
Introduzione a Amazon Elastic Container Service
Introduzione a Amazon Elastic Container ServiceIntroduzione a Amazon Elastic Container Service
Introduzione a Amazon Elastic Container Service
 

Replacing Tape Backup with Cloud-Enabled Solutions by Index Engines

  • 2. Introducing Index Engines ▪ Amazon partner – supports primary/secondary storage migration via S3 ▪ Software company delivering enterprise indexing technology ▪ Direct indexing, reporting and access to backup data ▪ Supports data backed up by IBM, Dell EMC, Veritas, HP, etc. ▪ Cost effective migration from legacy tape to AWS S3 ▪ Index Engines Overview ▪ Partners include: Amazon, Dell EMC, EY, FTI ▪ Clients include: ▪ JPMC, Citi, Barclays, TIAA-CREF, State of CA, DOJ, Catholic Health, Cincinnati Children’s, Qualcom, Merck ▪ Patented technology Copyright Index Engines Inc. 2017 All rights reserved. 2
  • 3. Unstructured Data & Email in the Enterprise Documents Spreadsheets Presentations Email Archives (SharePoint) Backups (Disk or Tape) © Index Engines Inc. All Rights Reserved. 2016 3  Dark data  Difficult to develop/execute/audit data policies  Hidden sensitive records/PII  Unleveraged intellectual property  ROT – Redundant, obsolete and trivial data
  • 4. Gartner Recommendations* Organizations are struggling with uncontrolled data growth. Risk-aware and cost-conscious organizations are realizing they need a better understanding of their data in order to: ▪ Effectively reduce the risk and inefficiencies buried in unstructured data ▪ Better manage data in line with governance and policies ▪ Optimize data management and storage infrastructure ▪ Provide better access to unstructured data ▪ Facilitate business use of data that has previously been deemed "dark" © Index Engines Inc. All Rights Reserved. 2016 4 *Market Guide for File Analysis Software Published: 19 September 2016
  • 5. Index Engines Overview Know IT Manage IT Govern IT ▪ Data Classification & Profiling ▪ Enterprise class indexing software ▪ Metadata, full text, pattern/regex/PII, security ACLs, activity logs ▪ Reporting & classification on user files and email ▪ Defensible Disposition ▪ Delete, copy or migrate ▪ Integrated archiving & preservation ▪ Defensible audit trails and logs ▪ Automation and Monitoring ▪ Ongoing monitoring ▪ Automated management based on policy ▪ Instant access to personal data Copyright Index Engines Inc. 2017 All rights reserved. 5
  • 6. MANAGEMENTSEARCH/REPORTINDEX Index Engines Overview © Index Engines Inc. All Rights Reserved. 2016 6 Unstructured Network Data (NFS, CIFS, NDMP) Email Servers (EDB, PST, NSF) SharePoint Enterprise Vault Backup Data (Tape or Disk) (IBM, Symantec, CVLT, HP, EMC, etc.) Backup Catalogs (TSM, NBU, CVLT) Deduped Unified Search of Data Stored Queries and Automate Jobs Auditable Continual Defensible Disposition Abandoned Aged Redundant Personal Risk Archive Active Fast ( Up to 1TB/hr) Efficient Index (5% Footprint) Supports Federation for Distributed Data Classify Manage Based On Policy Automate Schedule Policies Archive Deletion Cloud Disk
  • 7. Index Engines Advantages Speed The fastest indexing engine on the market today, reaching speeds up to 1TB/hr/node High speed queries across large data sets Access Supports the widest range of enterprise data sources, including backup data Recognizes duplicate content across network and backup data sources Scale Extreme scalability, to PBs, with index footprint of 5% or less Supports federated environments – locally or geographically Flexible Supports a range of indexing from light metadata to full content Extensive search and reporting options Enterprise Ready Active Directory integration allowing for reporting by group membership Flexible deployment options © Index Engines Inc. All Rights Reserved. 2016 7 Built from the ground up as an enterprise-class indexing platform
  • 8. Search and Reporting Interface © Index Engines Inc. All Rights Reserved. 2016 8
  • 9. Client Deployments Client Business Challenge Index Engines Deployment Benefits Electronics Manufacturing Aged & outdated data requiring frequent storage capacity upgrades ROT Clean Up: LAN indexing of 3PBs data. Delete redundant data/no access in 5+ years Reclaimed >30% capacity and eliminated a pending upgrade Mid-Market Financial Risk associated with unmanaged email (PSTs) and PII on the network Security Audit: LAN indexing of 100TB of files and email to find, review and secure PSTs/PII Mitigated legal risk and supported regulatory policies Government Agency Support strategy of migrating aged retention data to lower cost cloud Cloud Migration: LAN indexing of 500TB of aged servers, migrating data based to cloud Reduced data center footprint by 20% and eliminated aged storage platforms Global Financial Backup tape migration of legal hold email to online archive Legal Hold: Backup indexing of 200,000 tapes and restoration of mailboxes to disk archive Support ongoing litigation, eliminated large, legacy tape infrastructure Global Pharmaceutical Eliminate legacy tape infrastructure, go tapeless Tapeless: Catalog ingestion and tape indexing/migration of LTR data to disk archive Eliminate legacy tape infrastructure and improve time to data for legal Large Healthcare Consolidate non-production backup catalogs/retire legacy infrastructure Catalog Consolidation: Catalog ingestion, 75 media servers, report/access data Faster time to find and access legacy data in support of regulatory reqs © Index Engines Inc. All Rights Reserved. 2016 9
  • 11. LAN Overview ▪ High speed indexing of network files, email, archives (SharePoint) ▪ Comprehensive search, reporting and classification ▪ Intelligent management to support migration and corporate data polices ▪ Supports following use cases: • Defensible Deletion of aged data • SharePoint Migration • Cloud Migration • Data Profiling & Assessments • Email Management • PII/PST & Security Audits • Archiving & Preservation © Index Engines Inc. All Rights Reserved. 2016 11
  • 12. LAN Technology Overview ▪ Only solution on the market to support enterprise class data centers ▪ Agentless NFS/CIFS crawling for in-place indexing of files and email ▪ Supports NDMP for high speed ingestion of data ▪ Rapidly deployable, server or virtual options ▪ Enterprise scalability (5% index footprint) , supports petabytes ▪ Not a sampling of data, full scan of all content ▪ Support distributed environments via federation ▪ Fully integrated indexing, reporting, management and disposition © Index Engines Inc. All Rights Reserved. 2016 12
  • 13. ROT Analysis and Disposition ▪ Classify content by metadata ▪ Redundant – based on MD5 hash/document signature or metadata only analysis ▪ Obsolete – Not accessed in more than 3 years ▪ Trivial – Personal multimedia files (photos, iTunes, movies, etc.) ▪ ROT disposition ▪ Defensible deletion ▪ Migrate to lower cost storage/cloud ▪ Archive sensitive content and intellectual property ▪ Monitor data in place and manage based on retention policy ▪ Up to 33% of all data in a shared file server is ROT! ▪ Organization grow storage capacity up to 40% annually! © Index Engines Inc. All Rights Reserved. 2016 13
  • 14. Sample Client Deployments Agriculture Insurance Internal auditing of 1,000 user accounts/10TB data to safeguard PII (SSN/Bank Routing) Key Features: Scale, customized reporting, comprehensive indexing Financial Holding Internal auditing of sensitive documents across 20TB server environment Key Features: Flexible indexing, speed and automation, ease of use Consumer Goods Reduce 1PB storage footprint and migrate data to the cloud for LTR. Key Features: Ease of deployment, Speed, PII/Keyword search, flexible reporting Technology Networking Profile 2.4PB of network data to support clean up of ROT and deeper analysis of specific content . Phase 2 will expand to 60PB Key features: Speed and scalability, comprehensive analysis – not sampling. Financial Services Implement departmental chargebacks to support clean up/management of 100TB Key Features: Active Directory integration, Speed, automated indexing, dynamic reporting © Index Engines Inc. All Rights Reserved. 2016 14
  • 16. Catalog Management Ingestion TSM/NBU/CV/NW catalog Rebuild HPDP/BUE/ARCServe/etc. Retire legacy backup software Use Index Engines to manage, search and report on catalog Restore On-Demand Use Index Engines to search catalog & find relevant tapes for restore Index tape with IE, detailed search for file/email Restore individual files/email from tape to disk Legacy Data Migration Profile legacy tape data based on catalog reports Select data of value for migration, or single instance of everything Migrate data from tape to cloud/disk for LTR Unlocking Backup Index Engines’ software ingests and manages non-production backup catalogs and delivers direct access to tape data without need for original software. © Index Engines Inc. All Rights Reserved. 2016 16
  • 17. Why Index Engines © Index Engines Inc. All Rights Reserved. 2016 17 ▪ Retire expensive legacy backup applications, infrastructure (libraries, servers, etc.) and tape storage ▪ Profile LTR data to understand value and risk ▪ Improve access to legacy data to support legal and compliance ▪ Accelerate SLAs with faster time to data ▪ Migrate and manage LTR data on disk/cloud more effectively ▪ Go tapeless – apply go forward LTR policy on tape or disk backups
  • 18. Direct Tape Processing © Index Engines Inc. All Rights Reserved. 2016 18 Create Original Environment Restore 100% of Tape Content Index Restored Content Dedupe Results Search for Relevant Data Extract Relevant Data (<5%) Traditional Restore Process Direct Indexing of Tape Content Search for DeDuped/Relevant Data Extract Relevant Data (<5%) Automated Approach 100% of Data Moves from Tape Relevant Data (<5%) Moves from Tape
  • 19. Use Case 1: Catalog Ingestion/Rebuild © Index Engines Inc. All Rights Reserved. 2016 19 Backup Catalog Ingestion TSM NetBackup Commvault Maintaining non-production backup software to support restores Planning on phasing out current backup software NetWorker Backup Catalog Rebuild HP DP ArcServe BackupExec Others Consolidated Catalog Metadata Single management for all backup catalogs Search, report, manage, access legacy data Retire legacy backup software
  • 20. Use Case 2: On Demand Access © Index Engines Inc. All Rights Reserved. 2016 20 Backup Catalog Ingestion TSM NetBackup Commvault Maintaining non-production backup software to support restores Planning on phasing out current backup software NetWorker Backup Catalog Rebuild HP DP ArcServe BackupExec Others Single management for all backup catalogs Search, report, manage, access legacy data Retire legacy backup software Support ongoing restoration needs (eDiscovery, compliance, etc.) Tapes are maintained for LTR data Restore native files and email Scan/Index tapes for detailed search/restore Search catalog find relevant tapes/barcodes Consolidated Catalog Metadata
  • 21. Use Case 3: Tape to Cloud Migration © Index Engines Inc. All Rights Reserved. 2016 21 Backup Catalog Ingestion TSM NetBackup Commvault Maintaining non-production backup software to support restores Planning on phasing out current backup software NetWorker Backup Catalog Rebuild HP DP ArcServe BackupExec Others Single management for all backup catalogs Search, report, manage, access legacy data Retire legacy backup software Consolidated Catalog Metadata Two pass culling: Catalog cull followed by detailed culling Culled data set or single instance archive migrated to cloud via S3 Legacy tapes are remediated Analyze catalog, cull tapes to relevant dataset Scan/Index tapes for detailed search/restore Migrate data to cloud Scan/Index tapes for detailed search/restore Restore native files and email Search catalog find relevant tapes/barcodes
  • 22. LTR data is managed in online archive containing LTR data No longer store tapes in offsite storage, recycle the DR tapes Eliminate the use of tape for LTR Use Case 4: Go Tapeless © Index Engines Inc. All Rights Reserved. 2016 22 Backup to Disk Media Server TSM NetBackup Commvault Backing up to disk, creating tapes off the back end for DR NetWorker HP DP ArcServe BackupExec Others Search and filter data Define retention policy Migrate LTR data from backup as forensic copy Index nightly backups
  • 23. Intuitive Interface © Index Engines Inc. All Rights Reserved. 2016 23
  • 24. Hardware • Servers (NDMP) • Libraries • Floor space Resources • Manpower • Data center costs Backup Software • Maintenance • Infrastructure • Management SLAs & Restores • Time to restore data • 3rd party restore services Tape Storage • Offsite storage costs • Tape management • Tape purchases Risk & Liability • eDiscovery • Regulatory • Long-term risk Key Performance Indicators
  • 25. Cost Saving Using Cloud for LTR 0 50000 100000 150000 200000 250000 300000 350000 Business as Usual (Yearly Costs) Migration Costs (One Time Charge) Transformed Environment (Yearly Costs) Copyright Index Engines Inc. 2017 All rights reserved. 25 Backup/Restore Infrastructure Servers, libraries, disk, maint, floor space, staff Backup Software Maintenance costs, and staffing Tape Storage Offsite storage costs Tape Management Cost to retrieve tapes to support legal Migration Project Software, hardware, services Cloud Infrastructure Software, hardware to access cloud data Cloud Storage Costs to store and retrieve data in cloud Staffing Staff to support cloud archive BAU Annual Costs Migration Costs One Time Fee Transformed Annual Costs 3 Year Savings ROI $295,600 $275,000 $100,000 $311,800 (35%)
  • 26. Classifying and Culling Backup Data Redundancy 90%! Aged Data – Outside Retention Irrelevant Files User Files Email LTR Option 1: • Most efficient • Cull to specific LTR data • Data on legal hold • Typically a small subset (1% or less) Option 2: • Single instance • Eliminate duplicates • Migrate files, email, databases • A larger subset (10% or more)
  • 27. Migration Case Study Client with approximately 5,000 legacy tapes - migrated all unique files and email from past 3 years to a single instance archive ▪ 1,000 LTO-4, 2,000 LTO- 3, 2,000 LTO-2 (all NBU, compressed tapes) ▪ Total data storage = 3.6PB ▪ Migrate all unique email, and user documents from past three years. ▪ Cull 30% of tapes (past retention, eliminate incrementals) ▪ Total data remaining = 2.52PB ▪ Total data for migration = 126TB (95% of data duplicate (5% unique)) ▪ Utilize four Index Engines servers, four libraries ▪ Data will be migrated to cloud storage in ~9 months ▪ Tapes shredded ▪ Legacy backup software, libraries, and servers retired © Index Engines Inc. All Rights Reserved. 2016 27
  • 28. IE Backup Migration Services ▪ Index Engines offers cost effective pricing that includes the bundled software & services needed ▪ Legacy Data Migration Assurance Program ▪ Tapes remain on premise, IE engineers remotely manage the progress ▪ Client provides hardware and loads tapes ▪ Data Processing Lab ▪ Off premise, turnkey service ▪ IE manages the migration process in our secure lab based on clients migration requirements © Index Engines Inc. All Rights Reserved. 2016 28
  • 29. Questions? © Index Engines Inc. All Rights Reserved. 2016 29