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1

Next Generation

Data Warehouses

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About the Presenter

• Gautam Gupta – Practice Manager, BI

and Data Warehousing at YASH

Technologies

• Over 20 years of experience in the IT

industry, including extensive consulting

experience in US and Europe.

• Currently heads the BI and Data

Warehousing competency at YASH

since 2005, and has successfully

delivered and managed multiple BI and

Data Warehousing projects across the

world.

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Topics

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DW – What is it

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Data Warehouse Platforms

Note: A data warehouse platform manages a data warehouse, but the two are separate.

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Evolving State of Data

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Evolving State of Data

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Why care about Data Warehouse Platforms ?

Business face changes rapidly

Support changing business requirements

DW mature through multiple lifecycle stages

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Buzz About Big Data

• Global Internet population grew by 7% from

2011 to 2012 and now represents about 3 billion

people approx.

• Every Minute

– 571 new websites

– 217 New Users

– 48 Hours of You Tube footage uploaded

– Two million Google search queries

– 648 478 Facebook users sharing content

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Challenges in current Data Warehouse

Platforms

• Support for Advanced Analytics

• Real-time or On-demand workloads

• Support for Large Data Volume

• Support of Large number of Concurrent Users

• Scaling Cost

• Inadequate support for web-services and SOA

• Inadequate support for in-memory processing

• SMP Vs MPP

• Speed

• Support for Mashed Data

• Availability

• 64 Bit

• Data Vertulization

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New Analytics Needs

• Acquisition of environment data

• Correlation of subjective data

• Visualization of complex data

• Analysis of Event Stream data

• Need for pattern discovery

• Need for predictive modeling and scoring

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Demands on New Architecture

• Fast Analytics

• Flexible ad-hoc transformations

• Storage of granular AND semi-transformed data

• Storage of temporal data

• Interpretation of subjective data

• Ability to add new data for new analysis with no disruption

• Cost-effective scaling

• Statistical analysis / Predictive modeling

• Automated meta-data extraction / learning

• Ability to analyze real-time event-streams

• Provide existing operational reporting, online ad-hoc queries, “state-of-the-business”

dashboards

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Candidate Architecture

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Candidate Architecture

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Candidate Architecture

* Intelligent Business Strategies

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Big Data Portfolio

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18

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Candidate Arch. - DWA

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Cloud Computing and Software-as-a-Service (Saas)

Here?

3-5 yrs?

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Workloads ready now for cloud computing: TOP 25

Analytics • Data mining, text mining or

other analytics • Data warehouses or data

marts • Transactional databases

Business services • Customer relationship

management (CRM) or sales force automation

• E-mail • Enterprise resource planning

(ERP) applications • Industry-specific applications

Collaboration • Audio/video/Web

conferencing • Unified communications • VoIP infrastructure

Desktop and devices Desktop Service/help desk

Development and test Development environment Test environment

Infrastructure Application servers Application streaming Business continuity/

disaster recovery Data archiving Data backup Data center network capacity Security Servers Storage Training infrastructure Wide area network (WAN)

capacity

Source: IBM Market Insights, Cloud Computing Research, July 2012.

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Workloads may be at different levels of readiness for cloud

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There is a spectrum of deployment options for

cloud computing

Private Public

Hybrid

IT capabilities are provided “as a

service,” over an intranet, within the

enterprise and behind the firewall

Internal and external service delivery

methods are integrated

IT activities / functions are

provided “as a service,” over

the Internet

Third-party

operated

Third-party hosted

and operated

Enterprise data center

Enterprise data center

Private cloud Hosted private cloud

Managed private cloud

Enterprise

Shared cloud services

A

Enterprise

B

Public cloud services

A

Users

B

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How Can We Bridge the Cloud & On Premise Worlds?

Home-grown

Applications

Packaged

Applications

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Summary: Key Benefits of Cloud

• Cloud enables the dynamic availability of IT

applications and infrastructure, regardless of

location.

– Enhanced service delivery reinforces efforts for

customer retention, faster time to market and

horizontal market expansion.

• Cloud computing promotes IT optimisation so

that IT resources are configured for maximum

cost-benefit.

– It supports massive scalability to meet periods of

demand while avoiding extended periods of under-

utilised IT capacity

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Recommendations

• Plan for the next generation data warehouse that is in your near future

• Recognize that next generation technology drivers are really business drivers

• Avoid assembling your own data warehouse platform

• Plan for big data

• Be open to low-cost DW platform options

• Don’t forget options outside the DW platform

• Expect analytics to be a priority for your next generation DW platform

• Note that some next generation options are a critical path to others

• Realize that your next generation DW platform may require multiple platforms

• Be open to alternative DBMSs

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Thank You!

mailto: gautamg@yash.com

website : www.yash.com

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