achieve business agility through data virtualization

Achieve business agility through data virtualization

Dr. Bas van Gils

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Bas van Gils

+31-(0)6-484 320 88

b.vangils@bizzdesign.nl

http://linkedin.com/in/basvg

http://blog.bizzdesign.com

http://www.twitter.com/basvg

“Life is and will ever remain an equation incapable of solution, but it contains certain known factors.”--Nikola Tesla (1935)

Competitive playing field

Substitutes &Complementors

(e.g. changed product range,new technological standard)

New Entrants(e.g. new business model,

diversification strategy,new alliance)

Buyers(e.g. changed needs,

increased price sensitivity,lower brand loyalty

Suppliers(e.g. innovative products,

new foreign entrants,consolidation)

Political/Regulatory Drivers(e.g. new trade regulations,

environmental protection laws,privatization moves)

Socio-CulturalDrivers

(e.g. changing health needs, environmental awareness,

consumption habits)

TechnologicalDrivers

(e.g. new scientific breakthroughs,innovative technologies,

standards)

Economic Drivers

(e.g. changing exchange rates,economic growth, labor

productivity)

Incumbent Rivals(e.g. improved competences, newproducts, new brand positioning)

Business agility

Business agility is mandatory in the competitive arena• Respond to ever changing demands

by (potential) customers• Respond to aggressive moves by

competitors• Adapt to changing regulations• Utilize advanced technological

developmentsAll in order to stay alive and thrive in the long run

Organizing for agility

Agility in the market place

Agility of the organization

Process standardizationPr

oces

s in

tegr

ation

• Operating model:• Process focus• Data is forever, systems are

temporary• Architecture:

• Long-term view• Incremental delivery

Every organization is different. As a consequence, there is no single “best” recipe that helps organizations organize for agility

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Focus on Data

The 21st century business features information as the fuel. We don’t replace process; we enable operators in existing processes.

The bottom line is: if information is fuel – then improper treatment is risky. Fuel can be volatile. Fuel can explode

Ladley, J. (2010). Making enterprise information management (EIM) work for business: A guide to understanding information as an asset. Morgan Kaufmann.

Data challenges

Paradox:• Organizations face the challenge of

information overflow: the amount of information available is too big to process

• Delivery of information is slow due to tight coupling between information systems and data

A more agile infrastructure for information delivery is required to face the challenges that come with increased data-based decision making

Data virtualization

“Data virtualization is a technology that makes a heterogeneous set of databases and files look like one integrated database.”

• Increasingly popular, with the expectation that it continues to grow in popularity

• Many different implementations by various vendors

• Important enabling technology for e.g. MDM, Data Warehousing, DQ improvement etc.

Using data virtualization

Source data in transaction systems, unstructured data, etc.

Virtualized (& potentially cached) representation of source data as enabler for restructuring, as well as prevent heavy workload for source systems

Business-focused data structures based on virtual tables: standardization of concepts, definitions & delivery in a format that makes business sense (e.g. dimensional structures)

Delivery in environments tuned for specific groups of stakeholders, also allowing for access control etc.

Using data virtualization

Data access can be optimized for various stakeholders with different needs, concept definitions, permissions etc.

Virtualized access to structured and unstructured data allows for uniform querying. Caching avoids heavy work-loads on the

original transaction systems

Decouple access to data from the source systems. This allows further manipulation of data without impacting the

original systems

Virtualization allows for rapid, incremental development & delivery of information with minimal impact on source systems

An architecture for agile information delivery

Key takeaway: data agility for success

• Focus on supporting business processes

• Data is forever, systems are temporary

• Data virtualization allows for decoupling between – source systems,

– data manipulation / structuring,

– data delivery that is tuned to business needs

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