The deluge of information companies face today is not manageable using traditional data integration approaches which prevent fast and rich data flow throughout the organization. This is demonstrated through IT’s struggle to obtain up-to-date information for the business, as views and reports of company operations become outdated before they get delivered.
Data virtualization can complement and boost data warehousing and ETL technologies by building a sort of "Logical Data Warehouse" abstraction layer, which facilitates broader and faster data integration across the enterprise. In this presentation you can learn how to spend less time manually reconciling data between silos and help your company improve performance and business agility from order to cash. Mike Ferguson will provide you the latest insights about this technology and Mark Pritchard shows some data virtualization use cases.
The Ultimate Guide to Choosing WordPress Pros and Cons
Improving Agility While Widening Profit Margins Using Data Virtualization
1. Improving Agility And Profitability Using Data Virtualization
- The impact of the Logical Data Warehouse on the value chain
Mike Ferguson
Managing Director
Intelligent Business Strategies
Denodo Webinar
June 2016
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Information spread across
different systems
IT responds with point-to-
point data integration
Takes too long to get
answers to business users
The Challenge
Data Is Siloed Across Disparate Systems
MarketingSales ExecutiveSupport
Database
Apps
Warehouse Cloud
Big Data
Documents AppsNo SQL
“Data bottlenecks create business bottlenecks.”
– Create a Road Map For A Real-time, Agile, Self-Service Data
Platform, Forrester Research, Dec 16, 2015
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The Solution
Data Abstraction Layer
Abstracts access to
disparate data sources
Acts as a single repository
(virtual)
Makes data available in
real-time to consumers
DATA ABSTRACTION LAYER
“Enterprise architects must revise their data
architecture to meet the demand for fast data.”
– Create a Road Map For A Real-time, Agile, Self-Service Data
Platform, Forrester Research, Dec 16, 2015
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Data Virtualization
Real-time Data Integration
“Data virtualization integrates disparate data sources in real time or near-real time
to meet demands for analytics and transactional data.”
– Create a Road Map For A Real-time, Agile, Self-Service Data Platform, Forrester Research, Dec 16, 2015
Publishes
the data to applications
Combines
related data into views
Connects
to disparate data sources
2
3
1
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Benefits of Data Virtualization
“Get it Real-time and Get it Fast!”
Better Data Integration
Lower integration costs by 80%.
Flexibility to change.
Real-time (on-demand) data services.
Complete Information
Focus on business information needs.
Include web / cloud, big data,
unstructured, streaming.
Bigger volumes, richer/easier access to
data.
Better Business Outcome
Projects in 4-6 weeks.
ROI in <6 months.
Adds new IT and business capabilities
“Benefits of Data Virtualization: get it real-time and get it fast!”
– William McKnight, President, McKnight Consulting Group
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Common Data Virtualization Use Cases
Data Virtualization
BIG DATA, CLOUD INTEGRATION
Advanced Analytics
Data Warehouse Offloading
Big Data for Enterprise
Cloud / SaaS Integration
AGILE BUSINESS INTELLIGENCE
Logical Data Warehouse
Virtual Data Marts
Self-Service BI
Operational BI / Analytics
SINGLE VIEW APPLICATIONS
Single Customer View - Call Centres, Portals
Single Product View - Catalogues
Single Inventory View – Reconciliation
Vertical Specific - Single View of Wells
DATA SERVICES
Unified Data Services Layer
Logical Data Abstraction
Agile Application Development
Linked Data Services
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Customer Case Studies
Data Virtualization
AGILE BUSINESS INTELLIGENCE
Major UK General Insurance Company
Streamlined operational reporting on policy admin system.
Exposed all policy data for operational MI and
Intra-day reports to all business stakeholders (analysts,
sales, actuarial, underwriters).
DATA SERVICES
Global Chip Manufacturer
Delivered data services to streamline business processes
across the entire value chain
Achieved faster time-to-market and increased revenue
BIG DATA, CLOUD INTEGRATION
Advanced Analytics
Data Warehouse Offloading
Big Data for Enterprise
Cloud / SaaS Integration
SINGLE VIEW APPLICATIONS
Single Customer View - Call Centres, Portals
Single Product View - Catalogues
Single Inventory View - Reconciliation
Vertical Specific - Single View of Wells
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• Opportunities in New Markets
• Changing Customers
• New Competition
• Proliferation of Channels
• Regulatory Change
• New Technology
UK General Insurance Company
Market Trends Changing Industry Approach
Traditional
Evolving
Exposure
Scale
Underwriting
expertise
Competitive
advantage
Creative
data
sourcing
Distinctive
analytical
method
Competitive
advantage
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UK General Insurance Company
• Cost of change prohibitive to generating value from data
• Slower time to market inhibiting impact of good analytics
• Complexity of solution can cause delivery bottlenecks
• Bespoke coded solutions require unique resource to maintain
Challenges to Agility
Reduce
Cost
Flex
Resource
Raise
throughput
Accelerate
change
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UK General Insurance Company
Target State Agile BI Architecture
DataSources
Virtual
Staging
Virtual
Semantic
AtomicWarehouse
VisualisationAnalytics
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Business Requirement
• Daily Operational Reporting
• Multiple consumers
• Brand new system
Technical Challenges
• Complex XML extract
• Fast pace of change
• XML Schema not available
• Varying data items and structure
UK General Insurance Company
Use Case: Agile Operational Reporting
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UK General Insurance Company
• Cost model reduced
• Significantly quicker time to market
• Greater throughput
• Resource pool expanded
Summary
Reduce
Cost
Flex
Resource
Raise
throughput
Accelerate
change
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Issues
Global Chip Manufacturer
Data Service Layer for streamlining business processes in the value chain
“Lack of consistent capability to integrate data from disparate data sources
and delivery using agile standardized methods.
• Data is globally distributed across heterogeneous tools & technologies
• New data sources (eg: big data) & consumers (eg: emergence of SaaS)
• New information exchange channels (eg: mobility) ”.
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Data Virtualization
Global Chip Manufacturer
Data Service Layer for streamlining business processes in the value chain
“An agile method that simplifies information access”.
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Benefits
Global Chip Manufacturer
Data Service Layer for streamlining business processes in the value chain
“Reduced time-to-market, increased agility, end-to-end manageability”
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Use Case: Supplier Master Data
Global Chip Manufacturer
Data Service Layer for streamlining business processes in the value chain
Supplier Master Data:
information about companies
that the company purchases
from, pays, outsource
manufactures with
Choosing a Supplier is the
point of entry to many
business process. If it fails
or is slow, it impacts all 70+
downstream consumers
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Use Case: MySamples
Global Chip Manufacturer
Data Service Layer for streamlining business processes in the value chain
Need to show the latest
status of samples requests.
• Customer information from
MySamples app
• Samples request
information (if requested)
from ERP system
• Samples shipment status
(if shipped) from Event
Management system
Source: Intel EDW 2015
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Summary
Global Chip Manufacturer
Data Service Layer for streamlining business processes in the value chain
“An agile data integration method that simplifies
information access
–Agility, time-to-market, Manageability & Reuse
Created enterprise standards to promote understandability,
reduce chaos, and help drive consistency”