crimson 3 - final case presentation
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The Future of Cummins Data Warehousing Architecture and Strategy
Pragnya BalamurukesanGraham CenkoMichael KhamisPavithra Thevasenapathy
Crimson 3
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Agenda
Crimson 3
Our Understanding
Data Warehousing Trends
Recommendations
Risks and Mitigations
Financials
Implementation Timeline
Conclusion
Our Understanding
Crimson 33
Cummins has six Data Warehouses on the
Oracle Exadata platform, a Data Lake
environment in Hadoop and a Teradata
warehousing appliance, which are not integrated
The current Data Warehouse architecture
and strategy does not meet the business
intelligence or future needs of the company
What Data Warehouse architecture and
strategy would meet Cummins’ needs and
support future growth initiatives?
Our Understanding DW trends Recommendations Timeline Financials Risks and Mitigations Conclusion
Future trends that should be incorporated into Cummins’ Data Warehousing strategy
Crimson 34
Cloud
Data Warehous
e
Business Intelligenc
e Tools
Big Data
Big Data Analytics
Hadoop Platform
Real-Time
DataStreaming
Analytics & Reporting
Consolidation
Physical
Logical
Foley, John. “The Top 10 Trends in Data Warehousing.” Forbes. 10 March 2014Satell, Matt. “The Future of Data Warehousing: 7 Industry Experts Share Their Predictions. BetterBuys. 5 November 2014
Our Understanding DW trends Recommendations Timeline Financials Risks and Mitigations Conclusion
Cummins should adopt this Data Warehouse architecture to satisfy future trends and growth initiatives
Crimson 35
Cloud Files Office files Web services Social Feeds Sensor Web logs
Data Sources
Enterprise Information Management BPM ECM CEM Discovery Info exchange
Data Warehouse Hadoop
Stream Computing
Master Data Management
Data Virtualization
Reporting Statistical analysis Visualization
Business Intelligence Tools
Our Understanding DW trends Recommendations Timeline Financials Risks and Mitigations Conclusion
Cummins should take these five actions to achieve the recommended Data Warehouse architecture
Crimson 36
Governance
Our Understanding DW trends Recommendations Timeline Financials Risks and Mitigations Conclusion
Move certain databases from Oracle Data Warehouse to Teradata Active Data Warehouse
Private Cloud
Implement Hadoop-as-a-Service using Google Compute Engine and MapR
Adopt Cisco Composite Data Virtualization Platform
Add IBM InfoSphere Stream, Tableau and Spotfire to the Business Intelligence & Analytics
tools
Crimson 37
TERADATA ADW PRIVATE CLOUDEDW
Components Power Gen
Engine Distribution
Active events Customer-sales representative interaction, worker in
shipping & receiving
Active load Arrival of damaged critical supplies
Active enterprise integration Fitting into existing portals, Web services, SOA
components
Active workload management Controlling mixed workloads
Active availabilityIncreasing the DW availability from business critical to
mission critical
Active access Out-of-stock situation, inventory manager makes
decisions
ORACLE
Corporate Components
Engine
Power Gen
Distribution
Supply chain, Logistics, Sales, Marketing, Inventory & Operational data
Cummins should move certain Databases from Oracle Exadata to Teradata Active Data Warehouse Private Cloud
Our Understanding DW trends Recommendations Timeline Financials Risks and Mitigations Conclusion
Rec 1 Rec 2 Rec 3 Rec 4 Rec 5
BENEFITS
Teradata(2015) “Enabling the Agile Enterprise with Active Data Warehousing”
Cummins should adopt Teradata private cloud for the following reasons
Crimson 38
Challenges in Public Cloud
Worldwide private cloud adoption- Forbes
Consolidate to Teradata private ADW
Reduced costs through server utilization
Pay what you use ,when you need
Faster less than five minutes
Elastic performance
Quick decision making
Leading Healthcare company saves 4.3 billion, delivering
250,000 self service reports, improving
performance by 10x
Government agency which took 20
hours for running queries can run in
15 minutes
Why private cloud model ?
• High Active Performance
• Effortless Scalability
• Operational Availability
• Enterprise Concurrency
• Investment Protection
Success stories
Characteristics of Teradata ADW private cloudBenefits of Teradata ADW private cloud
Teradata News Release (2012) Teradata Active Data Warehouses Provide Private Cloud Benefits
Our Understanding DW trends Recommendations Timeline Financials Risks and Mitigations Conclusion
Rec 1 Rec 2 Rec 3 Rec 4 Rec 5
Cummins should implement Hadoop-as-a-Service using Google Compute Engine and MapR
Crimson 39
Google Cloud Storage
MapRMapR CLDB
(Container Location Database)
<cluster> [Master] MapRMapR FileServer
<cluster> 000 [Worker]
<cluster> 001 [Worker]
<cluster> nnn [Worker]
MapRMapR FileServer
MapRMapR FileServer
1
1 An application downloads data file from Google Cloud Storage and pushes it MapR-FS2
2 The CLDB distributes the file to MapR-FS based on the query
3
3 The result of the query is written to the file on Google Cloud Storage
DATA FLOW
FEATURES12345
Operational IntelligenceEnterprise Data HubInternet of ThingsSecurity and Risk ManagementMarketing Optimization
MapR (2014) “MapR, Hive, and Pig on Google Compute Engine”
Our Understanding DW trends Recommendations Timeline Financials Risks and Mitigations Conclusion
Rec 1 Rec 2 Rec 3 Rec 4 Rec 5
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Cummins should implement Hadoop-as-a-Service using MapR for the following reasons
Crimson 3
Cost Scalability
Enhanced productivity Collaboration
Elasticity Efficiency
MapR Cloudera Hortonworks
Data Ingest Batch and streaming writes
Batch Batch
Hbase Performance
Consistent low latency
Latency spikes Latency spikes
High Availability
Self healing across multiple failures
Single failure recovery
Single failure recovery
Replication Data + metadata
Data Data
File I\O Read/write Append only Append only
Write level authentication
Kerberos, Native
Kerberos Kerberos
Vendor
Criteria
Robert D. Schneider (2014) “Hadoop Buyer’s Guide, Ubantu”
Why we chose cloud deployment ?
Why we chose MapR ?
Our Understanding DW trends Recommendations Timeline Financials Risks and Mitigations Conclusion
Rec 1 Rec 2 Rec 3 Rec 4 Rec 5
Cummins should implement Composite Data Virtualization Platform to provide a unified logical view of all the data
Crimson 311
OperationalStores
SaaSApplications
Data Warehousesand Marts
Data Virtualization PlatformAbstra
ct Federate Cache
CacheOptimizer
Discovery
Traditional, Big data & cloud sources
Cisco Information Server
InstantAccess to all data
End-End data management
Faster response to BI & Analytics
Features
BI & Analytic tools
Logical view of Cisco Composite
Unified logical enterprise view of all the data
Our Understanding DW trends Recommendations Timeline Financials Risks and Mitigations Conclusion
David Bescmer. Jan 2014. Cisco Data Virtualization
Rec 1 Rec 2 Rec 3 Rec 4 Rec 5
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Cummins should install Composite Data Virtualization Platform for the following reasons
Crimson 3
Composite Informatica IBM
Federated Query language
3 2 2
Caching 3 2 2
Profiling 3 1 2
Metadata support
3 1 1
Customer base 3 2 2
Compatibility with existing technologies
3 2 2
Total 18/18 10/18 11/18
VendorCriteria
Profit Growth
Risk Reduction
Technology Optimization
Staff Productivity
Time-to-Solution Acceleration
Benefits of Virtualization
Our Understanding DW trends Recommendations Timeline Financials Risks and Mitigations Conclusion
Rec 1 Rec 2 Rec 3 Rec 4 Rec 5
Cisco “Data Virtualization”
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Cummins should reevaluate their existing BI Toolset and purchase Tableau and Spotfire for visualization and analytics
Crimson 3
Existing - Reporting• Action: Continue Using
OBIEE and MSBI for reporting. Phase out the other four traditional platforms
• Benefit: Reduced licensing and training costs, standardized reports and less complexity
Tableau - Visualization• Action: Purchase
Tableau Online for an easy to use data visualization platform that is designed for end business users
• Benefit Enables self-service BI to the entire organization, no support from IT needed
Tibco Spotfire – Statistical Analysis• Action: Purchase Tibco
Spotfire Platform for advanced analytical capabilities to be used by business analysts
• Benefit: Predictive and Prescriptive analytical capabilities and ability to consume structured and unstructured data
Tibco Software Company. “Tibco Spotfire Platform.” 15 December 2015Tableau. “Tableau Online.” 15 December 2105
Our Understanding DW trends Recommendations Timeline Financials Risks and Mitigations Conclusion
Rec 1 Rec 2 Rec 3 Rec 4 Rec 5
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Cummins should adopt IBM InfoSphere Streams to enable real time business intelligence
Crimson 3
Avadhoot Patwardhan (2015) “Introduction: Real-Time Analytics on Data in Motion”Aladdabigdata (2015)Real-time Analytics using IBM InfoSphere Streams
ACQUIREReal time data from
several different streams having different formats
ANALYZEThe data in real time
using applications developed by either
Cummins or IBM
ACTOn the Business
Intelligence delivered in real time
Integrated Development Environment Scale – Out Runtime Analytic Toolkits
Benefits of Stream Computing
Our Understanding DW trends Recommendations Timeline Financials Risks and Mitigations Conclusion
Rec 1 Rec 2 Rec 3 Rec 4 Rec 5
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Cummins should establish the following teams for effective governance over the Data Warehouse initiative
Crimson 3
Change Management
• Comprised of senior managers and supervisors of each business unit
• Communicate change to the company and each business unit
• Manage training of employees
Vendor Management
• Comprised of Cummins IT professionals
• Assigns tasks to vendors while monitoring the performance of each vendor
• Re-negotiating contracts
Support Team
• Comprised of Cummins IT technicians for each business unit
• Groups will be assigned to each layer of the architecture
BICC Team
• Comprised of business managers from each business unit
• Champion BI technologies defining standards, business alignment, project prioritization and management
Information Governance
• Comprised of C-suite member, IT professionals, business managers, paralegal, and members from each business unit
• Manage information throughout its lifecycle
IT Steering CommitteeBusiness & IT Leaders
Our Understanding DW trends Recommendations Timeline Financials Risks and Mitigations Conclusion
Rec 1 Rec 2 Rec 3 Rec 4 Rec 5
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It will take 3 years for Cummins to implement the recommended Data Warehouse strategy
Crimson 3
Year 2Year 1 Year 3
Our Understanding DW trends Recommendations Timeline Financials Risks and Mitigations Conclusion
The project will costs Cummins $11,370,000 and result in the following benefits
Crimson 317
Emission controlUsing real time data to
track emission of engines, Increasing the quality of
Cummins engines
Investment in the right technologiesUsing BI tools to predict where market trends in engine technology are headed
Leading projects in major markets Using BI tools to improve alignment with organization strategy
BenefitsBusiness Value is derived from the actions taken as a result of the analysis enabled by
the BI tools Cost Savings: ~$2 million
Cloud storage, Operating Expense, and People
Software Hardware
Cloud StorageTools
End user TrainingCost of AdministrationMaintenance Support
External ContractTotal Costs
$ 1,400,000$ 675,000$ 65,000$ 5,750,000$ 200,000$ 200,000$ 2,680,000$ 400,000$ 11,370,000
*See appendix for detailed cost description and more sources
CostGlobal expansion
Using BI tools to find existing and potentially new areas with demand
that is not being exploited
Potential Business Value Benefits
Sallem,Rita. Sept. 2012, “Customer rate their BI /vendors on Costs.”Sheffield, Glen. March 2015, “How much does Teradata warehouse Cost.”
Our Understanding DW trends Recommendations Timeline Financials Risks and Mitigations Conclusion
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Risks and Mitigations
Crimson 3
Risk Mitigation
Data maybe breached when we store it in the Teradata cloud Teradata is partnered with Protegrity and utilizes Tokenization technology which is applied to data before entering into the warehouse
Data virtualization Cisco platform can bring up data security concerns because the all the business data is used by this platform
1.The manager that resides in the Cisco Information Server takes care of security, metadata , source code and more. 2.The IT security team of Cummins will be given training on the new security policies and data governance, data standards. 3. Change management team will make sure that there is effective communication between the vendor management, in-house IT teams and C-suite level about security measures
The data stored in Google Compute Engine or being used by MapR’s services maybe breached
MapR is equipped with authentication mechanisms (Kerberos, Native), authorization mechanisms (Access Control Expressions, Unix File Permissions, Access Control Lists) encryption mechanisms (Over-the-Wire Encryption, Encryption at Rest, Field-Level Encryption, Format-preserving Encryption and Masking) and governance guidelines
Employees responsible for reporting, visualization or analytics may become dissatisfied while learning new tools
Reporting tools will remain the same and it will be the Change Management Team’s responsibility to set the tone from the top
Inconsistent data from legacy systems will remain in the new Data Warehousing Architecture
Information Governance Team and MDM tool will ensure consistent and reliable data across platforms and databases
Our Understanding DW trends Recommendations Timeline Financials Risks and Mitigations Conclusion
Teradata. “Our Partners.” 2015MapR (2014) “MapR, Hive, and Pig on Google Compute Engine
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Following these recommendations will lead to a successful data warehouse architecture that has the capabilities to allow users to make intelligent business decisions
Crimson 3
Our Understanding DW trends Recommendations Timeline Financials Risks and Mitigations Conclusion
Data Warehouse architecture and strategy that meets
business needs and future
trends
Move certain Databases from Oracle to Teradata Active Data Warehouse
Private Cloud
Re-evaluate existing BI Toolset and purchase
Tableau and Spotfire for visualization and analytics
Establish robust governance for effective use of the Data
Warehouse initiative
Implement Cisco Composite Data Virtualization Platform
to provide unified logical view of all the data
Implement Hadoop-as-a-Service using Google
Compute Engine and MapR
Appendix
Crimson 320
HadoopWhy MapR?Why Hadoop-as-a-Service?SecurityMapR Architecture
Enterprise Information ManagementCapabilitiesArchitectureWhy OpenText?
Master Data ManagementBusiness Intelligence Tools
Vendor MatrixAnalytical maturity modelIBM InfoSphere StreamsWhy InfoSphere?Security
CISCO Composite Virtualization layerFunctionalitiesWhy virtualization?Why Composite?CISCO ArchitecturesSuccess stories
TeradataCharacteristicsWhy Private Cloud?Operational IntelligenceSecurity
Information Governance teamCosts
ComponentsToolsCategorySavings
Why not the Oracle Exadata proposal
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Comparative study of MapR, Cloudera, Hortonworks and Forrester’s ranking
Crimson 3
Robert D. Schneider (2014) “Hadoop Buyer’s Guide, Ubantu”Experfy.com
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Benefits of moving Hadoop to the cloud
Crimson 3
1. Cost : The on-premise model for deploying Hadoop would require a large number of servers, electricity as well as a housing facility. Whereas the cloud deployment would be more cost effective since it offers better scalability and pay only for what you use.2. Scalability : The on-premise model would require time consuming addition of physical servers. The cloud offers massively scalable services extremely quickly3. Enhanced productivity : Using a cloud based Hadoop platform would enable data access anytime from anywhere, therefore providing greater and faster access to data4. Collaboration : A cloud based Hadoop platform would enable seamless collaboration across the business units. Since syncing and sharing of files would be simultaneous, the collaboration would be real time5. Elasticity : Hadoop clusters cannot be added or removed quickly, whereas Hadoop-as-a-service has the ability to increase or decrease number of clusters (instances) as per demand6. Handling Batch jobs : The on-premise Hadoop model has scheduled jobs that process the incoming data on a fixed, temporal basis. The Hadoop-as-a-Service can be optimized by having the appropriate sized clusters available for the jobs to run7. Simplifying Hadoop operations : In the on-premise model, as clusters are consolidated there is no resource isolation for different users. Hadoop-as-a-Service allows provisioning of clusters with different configurations and characteristics. Therefore management of a multi-tenant environment is simplified
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Hadoop Security
Crimson 3
MapR offers several capabilities to help Cummins secure their data. At the product level MapR prevents unauthorized access to secure the Hadoop and NoSQL data. At the solution level MapR offers deployment of a large-scale anomaly detection solution that alerts you to network intrusion, phishing, and other cyberattacks.Authentication is performed through 1. Kerberos Integration2. Native authenticationAuthorization is the configuration of permissions for users. The authorization mechanisms offered by MapR are 3. Access Control Expressions4. Unix File Permissions 5. Access Control Lists
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Hadoop Security
Crimson 3
MapR also accounts for regulatory compliance and therefore provides four types of auditing which are 1. maprcli commands that are related to cluster management2. Authentications to the MapR Control System (MCS)3. Operations on directories and files and Operations on MapR-DB tables. As an additional means of preventing unauthorized access of sensitive data, MapR supports encryption. The encryption mechanisms available are 4. Over-the-Wire Encryption5. Encryption at Rest6. Field-Level Encryption 7. Format-preserving Encryption and MaskingMapR also supports features that facilitate effective data governance. Among these are 8. Data Integration9. Security10. Data Lineage11. Information Lifecycle Management12. Auditing.
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Security in MapR
Crimson 3
Kerberos Authentication Native Authentication
MapR (2014) “MapR, Hive, and Pig on Google Compute Engine”
26Crimson 3
Security in MapR
Authorization
Auditing
Encryption
MapR (2014) “MapR, Hive, and Pig on Google Compute Engine”
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Capabilities of the Enterprise Information Management suite
Crimson 3
Enterprise Content management : Information management of all types and sources of data, throughout it’s life cycle
Business Process Management : Rapid modeling and automation of process applications and the ability to constantly improve them
Customer Experience Management : Using information to build rich customer experiences that support collaboration, build relationships and provides support on any channel such as web, mobile etc.
Information exchange : Exchanging information with any party and system securely and verifiably
Discovery : Ability to find and learn about the right information at the right time and place, independent of it’s location
OpenText (2015) “OpenText Process Suite Platform Architecture”
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Gartner declares OpenText to be a leader in Enterprise Content Management
Crimson 3
https://en.wikipedia.org/wiki/Enterprise_information_management
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Master Data Management
Crimson 3
5 Steps to implementing MDM1. Document: identify sources while
defining master data2. Analyze: Evaluate the way the data
flows in addition to defining transformation rules
3. Construction: Building the actual MDM warehouse according to the architecture/rules created
4. Implement: Population the data warehouse
5. Sustain: Make sure policies and compliance are upheld through Cummins governance structure
Reasons for having Master data Management• Standardization of data• Source identification• Data classification • Employee information management • Product information management • Eliminate duplicated data
Added business value because it organizes master data, making it possible to have effective BI tools. This then enable tools (being used properly) to receive information on business decisions.
https://www.quora.com/What-is-the-best-master-data-management-software
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Buyer’s Matrix for BI Tools
Crimson 3
Solutions Review. “2016 Solutions Review Matrix Report.” 2015
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Analytical Maturity Model
Crimson 3
“As an analytics platform, Spotfire offers you a variety of add-on capabilities as the sophistication of your environment grows, or as you climb up the analytics maturity curve, so to speak.” - Rishi Bhatnagar from Syntelli Solutions
Analytics Maturity Curve from Tom DavenportBhatnagar, Rishi. “How Much Does Spotfire Cost?” Syntelli Solutions. 25 July 2015
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IBM InfoSphere Stream example
Crimson 3
Example of streaming data sources associated with smart meters
Typical Streams runtime deployment of a streaming application
IBM Analytics (2015) “Top industry use cases for stream computing”IBM Analytics (2015) “IBM Streams”
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Forrester gives IBM high scores
Crimson 3
Forrester Wave : Big Data Streaming Analytics Platforms, Q3 ‘14
Mike G., Rowan C. (2014) “The Forrester Wave™: Big Data Streaming Analytics Platforms, Q3 2014”
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InfoSphere Security
Crimson 3
Security is provided in InfoSphere Streams through user authorization and authentication. User authorization is managed through Access Control Lists which contains the roles and their access rights. User authentication is done either using an LDAP server or PAM authentication service. Authentication keys, session time outs and client authentication for web management services are some of the mechanisms adopted.
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Discovery, optimize and caching for composite
Crimson 3
Discovery:1. Introspect available data2. Discover hidden relationships3. Model individual view/service4. Validate view/service5. Modify as requiredBenefits• Automates difficult work• Improves time to solution• Increases object reuseOptimization : 1. Application invokes request2. Optimized query (single statement) executes3. Deliver data in proper formBenefits:• Up-to-the-minute data• Optimized performance• Less replication requiredCaching :
1. Cache essential data2. Application invokes request3. Optimized query (leveraging cached data) executes4. Deliver data in proper form
http://www.compositesw.com/products-services/data-discovery/
42Crimson 3
Business case for virtualization• Profit Growth – Data virtualization delivers the information your organization
requires to increase revenue and reduce costs.• Risk Reduction – Data virtualization’s up-to-the-minute business insights help
you manage business risk and reduce compliance penalties. Plus data virtualization’s rapid development and quick iterations lower your IT project risk.
• Technology Optimization – Data virtualization improves utilization of existing server and storage investments. And with less storage required, hardware and governance savings are substantial.
• Staff Productivity – Data virtualization’s easy-to-use, high-productivity design and development environments improve your staff effectiveness and efficiency.
• Time-to-Solution Acceleration – Your data virtualization projects are completed faster so business benefits are derived sooner. Lower project costs are an additional agility benefit
http://www.compositesw.com/data-virtualization/
43Crimson 3
Virtualization versus Cloud• Security – Data integration in cloud , putting
the entire data of the business in cloud is a huge risk.
• Capacity management – Peak times, Holiday sales
• Redundancy of data without complete utilization of hardware resources
• In- house capabilities to handle http://www.businessnewsdaily.com/5791-virtualization-vs-cloud-computing.html
44Crimson 3
Key benefits of composite PROVIDES INSTANT ACCESS TO ALL DATA: • Complete information – Business needs the complete picture. Cisco’s data federation technology virtually integrates
data from multiple sources, without the cost and overhead of physical data consolidation.• Up-to-the-minute information – Cisco’s query optimization algorithms and techniques are fastest in the industry,
delivering the timely information business requires without impacting source system performance.• Fit-for-purpose information – Cisco’s powerful data abstraction functions simplify complex data, transforming it from
native structures and syntax into easy-to-understand business views and data servicesRESPOND FASTER TO ANALYTIC AND BI TRENDS:• Streamlined process – Building business views and data services in Cisco is far faster, with far fewer moving parts, than
building physical data stores and filling them using ETL.• Rapid IT response – Cisco’s reusable views and services, flexible data virtualization architecture, and automated impact
analysis provide the IT agility required to keep pace with business change.• Quick iterations – Prototyping new solutions is far faster with Cisco DV. Cisco’s rapid development tools surface live
data in just minutes, enabling extraordinary business and IT collaboration.END TO END DATA MANAGEMENT :• Data Discovery – Cisco’s introspection and unique-in-the-industry data discovery uncover existing information assets,
unlocking them for valuable new uses.• Standards-based – Cisco’s numerous standards-based access and delivery options support all the information types
business users require.• Data Governance – Information is a critical asset. To maximize control, Cisco’s data governance centralizes metadata
management, ensures data security, improves data quality and provides full auditability and lineagehttp://www.compositesw.com/products-services/data-virtualization-platform/
45Crimson 3
Criteria Composite Informatica IBM DenedoFederated query technology 5 4 3 1
Scalability 5 4 5 4Data quality 4 5 5 4Maintenance and support 4 5 4 4
Caching 5 4 4 2Profiling 5 4 3 2Costs 3 1 1 4Version upgrades 4 3 2 3Complexity of integrated Portfolio management
4 3 2 3
Metadata support 5 4 4 2Area of skills and Best practice documentation
4 3 3 2
Customer base 5 4 4 3Agility 5 4 4 3Time to value 5 4 4 3Compatibility with existing technologies
5 4 4 4
Forrester ranking 5 4 4 3Master data management 4 5 5 4
Total 72 65 61 55
Vendor evaluation matrix for composite
46Crimson 3
Cisco’s Data Virtualization Platform
Development Environment
Cisco Information Server
Runtime Server Environment Management Environment
XML
Packaged Apps RDBMS Excel Files Data Warehouse OLAP Cubes Hadoop / “Big Data” XML Docs Flat Files Web Services
Data WarehouseExtend / Offload
Governance, Risk & Compliance
Business Intelligence
Customer Experience Management
Mergers & Acquisitions
Single View of Enterprise Data
Supply Chain Management Analytics
Discovery
Studio
Adapters
Manager
Monitor
Active Cluster
http://www.compositesw.com/products-services/data-virtualization-platform/
47Crimson 3
Cisco’s Data Virtualization Platform
http://www.compositesw.com/products-services/data-virtualization-platform/
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Composite creates virtual marts, views and services
Crimson 3
http://www.compositesw.com/data-virtualization/virtual-data-marts/http://www.compositesw.com/data-virtualization/operational-data-stores/
49Crimson 3
Packaged Apps Web Services
Success stories of Composite
Company Before After
QualcommBI projects took
3 - 4 months Days/Weeks
PfizerManagement requests
for data took weeks Hours/Days
Northern Trust
100% data replication 20% replication
http://www.slideshare.net/CiscoPublicSector/composite-data-virtualization
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Characteristics of Teradata ADW Private cloud
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Main characteristics of Teradata ADW Private cloud include :Virtualized resources – Teradata virtualizes all processing and storage so users do not have to be concerned about the location or availability of system resources – only that they are getting timely answers to all their business questions automatically without performance penalty.
• Business analytics – a Teradata Data Lab makes it easier for business users to explore unique data sets or prototype new analytic ideas.
• Consistent performance – enables IT to meet business user service level agreements and to ensure user satisfaction by leveraging Teradata’s industry leading workload management as well as key technologies such as hybrid storage and columnar.
• Elasticity – delivers the analytic resources dynamically and in real time as business user demand increases and decreases.
• Scalability – enables the environment to scale seamlessly across multiple dimensions including number of users, number of queries, and data volumes with support for data scalability up to 92 petabytes.
http://www.teradata.com/News-Releases/2012/Teradata-Active-Data-Warehouses-Provide-Private-Cloud-Benefits-Today/?LangType=1033&LangSelect=true
51Crimson 3
Features of Teradata ADW private cloud
• Active access – high-speed inquiries, analysis, or alerts retrieved from the ADW and delivered to operational users, devices, or systems.
• Active events – operational events that need to be continuously monitored, filtered, and alerts sent based on business rules.
• Active load – high-frequency data loading throughout the business day to ensure data are fresh enough to support active access and active events.
• Active enterprise integration – links the ADW to existing applications, portals, Web services, service-oriented architectures, and the enterprise service bus.
• Active workload management – dynamic management of operational and strategic workloads in the same database, ensuring response times and maximum throughput.
• Active availability – increasing the data warehouse availability from business critical to mission critical.http://www.teradata.com/resources/white-papers/Enabling-the-Agile-Enterprise-with-Active-Data-Warehousing-eb4931/?LangType=1033&LangSelect=true
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Private cloud adoption
Crimson 3
http://www.datamation.com/cloud-computing/what-is-private-cloud.html
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Teradata provides operational intelligence
Crimson 3
http://www.teradata.com/resources/white-papers/Enabling-the-Agile-Enterprise-with-Active-Data-Warehousing-eb4931/?LangType=1033&LangSelect=true
http://www.teradata.com/resources/white-papers/Enabling-the-Agile-Enterprise-with-Active-Data-Warehousing-eb4931/?LangType=1033&LangSelect=true
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Teradata provides operational intelligence - Framework
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http://www.teradata.com/resources/white-papers/Enabling-the-Agile-Enterprise-with-Active-Data-Warehousing-eb4931/?LangType=1033&LangSelect=true
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Security in Teradata
Teradata’s Active Data Warehouse can make data available predictably and securely by leveraging Protegrity’s Vaultless Tokenization technology. Tokenization is applied to the sensitive data before it enters the warehouse, using the enterprise’s own security policies. This provides a security layer for all information in the database wherever it flows, without affecting the business’s ability to perform rapid analysis on that data. The solution relies upon Protegrity’s patent-pending Vaultless Tokenization, which deploys a very small set of lookup tables of random values without having to store either the sensitive data or the tokens. Tokenized data can be mined and manipulated by business processes without having to return the data to its original form, improving accessibility and performance while keeping the data protected.
Crimson 3
http://www.teradata.com/partners/Protegrity-USA/?LangType=1033&LangSelect=true
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Information Governance Team• Legal: Department works with IT. Driven by policy issues
such as compliance and privacy
• Records/compliance/audit: Deal with record compliance, document workflow, and archiving strategies. Also make sure that policy is carried out enterprise wide
• IT: Helps with more technical issues making sure policies are configured in systems architecture.
• Info Security: assures that sensitive data is being held in secure repositories and the data does not leak into unsecure areas.
• Business Unit: Help to spread the policy and compliance information to the rest of their BU.
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Managing information through its lifecycle and supporting the organization’s strategy, operations, regulatory, legal, risk and environmental requirements.
This team will manage records, business intelligence and MDM policies, rules and
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Cost of each component
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Hadoop $4000 per node for support• Software is one time cost• Cloud is ~$600 per TBMDM• $13,000 per collaboration server user (2) assuming $500 per user assuming 20 usersTeradata $2000 per TB• $2.5 million for in house supportOpentext• $2000 per user
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Cost Savings
Crimson 3
These cost savings are based on how much cheaper it is to store data on the cloud as opposed to not
Also Operating expenses is an estimate that is derived from the increased amount of projects Cummins will be able to do with proper BI tools
People cost savings are derived from the less amount of people that will have to provide support
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Cost Sources
Crimson 3
Componentshttp://googlecloudplatform.blogspot.com/2015/07/understanding-https://blogs.oracle.com/datawarehousing/entry/updated_price_comhttp://estore.gemini-systems.com/ibm/software-http://sheffieldview.com/2015/03/11/how-much-does-a-teradata-data-warehouse-appliance-cost/https://core.opentext.com/pricing.html
Tools http://www.ciosummits.com/Online_Assets_IT_Central_Station_Business_Intelligence_Tools_Report.pdfhttp://www.tableau.com/gartner-business-intelligence-costshttp://www.practicaldb.com/data-visualization-consulting/tableau-vs-spotfire/http://www.practicaldb.com/data-visualization-consulting/tableau-vs-spotfire/https://www.betterbuys.com/bi/roi-business-intelligence/
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Our recommended solutions is better than the previously proposed Oracle Exadata solution for the following reasons
• Future trends like Cloud, Big data, consolidation across platforms and real time analytics is not supported by Oracle Exadata.
• High Scalability• High Availability • 90-95% Resource utilization • Data management • Easily can respond to changing BI and analytic trends • Cost savings – cut on maintenance and support costs, hardware costs, labor costs etc• Hadoop Cloud with MapR technologies has huge advantages – efficiency, collaboration
and scalability etc• Moving operational data to Teradata can provide near- real time data warehousing
which helps intelligent business decisions• Cummins end goal is to have single truth of data with availability, data quality, usability
which is met by Cisco composite data virtualization platform.
Crimson 3
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