Conference Day 2: 9 November 2011

Understanding and Implementing Information Risk Management
Victoria Winningham, Principal, Metalethia LLC

Data Integration for the Cloud, Web, Big Data and Social Media
David García Hernando, Business Exchange Manager, The Phone House
Suresh Chandrasekaran, Senior Vice President, Denodo Technologies

Wednesday
9 November
08:00-08:45

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Wednesday
9 November
09:00-10:00

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Here, you will learn how to identify the Critical-to-Quality Information Characteristics to ensure you understand the true degree of IQ problems you measure. You learn how to apply statistical methods to establish the truth about critical Information Quality.

Without statistical quality measurements, your assessments may not be accepted as accurate by key Information Stakeholders. You learn how to avoid this scenario.

Featured Speaker:

Larry English President and Principal Information Impact International, Inc. To Speaker's Bio

Wednesday
9 November
10:30-11:30

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Managing the Information Quality Function in a Major Bank

Although there are a number of good books and theories in the field of data quality, the implementing of this approach varies in any organization. Different branches, countries, organisational cultures. The unique set of managers and employees. What is the starting point? Is it real? It is real. This presentation is about practice and results. Using the example of Alfa-Bank, which is the biggest Russian private bank, Andrey will show:

• The importance of trust for information and data
• The real example of Information Quality Framework and strategy for the huge full service bank
• The real examples of business cases for Information quality initiatives
• The scope and results of several successful Information Quality projects

Wednesday
9 November
10:30-11:30

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• What exactly are NoSQL database servers?
• Different categories of NoSQL products, including document stores, wide-column stores, key/value stores, multi-value stores, and graph data stores
• Haven't we always had non-SQL products?
• What are the advantages and disadvantages of NoSQL products?

Wednesday
9 November
10:30-11:30

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A Single Version of the Truth

• Is a single version of the truth attainable in any field of human endeavour?
• What does this mean for BI/DW programmes?
• Even if the destination remains out of reach, is the journey worth it?

Wednesday
9 November
10:30-11:30

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This session will walk through business cases in technology, finance and government and illustrate where agreeing on business semantics requires a collaborative and iterative approach. 

Wednesday
9 November
10:30-11:30

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• What is End User Computing
• What are the risks of End User Computing with regards to Data Quality and Reliability
• Why do we have End User Computing
• How to Mitigate the risks of End User Computing

Wednesday
9 November
11:35-12:35

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• ABPD algorithms discover all process variations, show business processes in graphical format
• Point out bottlenecks and provide accurate measurement results
• ABPD applied to ERP systems like SAP help organizations to save costs, speed up the process, make better quality
• Facilitates compliance with agreed practices and re-document IT system usage

Wednesday
9 November
11:35-12:35

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Wednesday
9 November
11:35-12:35

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• Right Information: from anywhere, internal or external
• Right Time: real-time to batch
• Right Access: secure by user, any device or format
  

Customer case studies - ranging from real-time reporting to predictive analytics, user-driven BI to competitive intelligence - will illustrate how an Agile Data Services platform, that leverages your existing infrastructure and extends it using Data Virtualization, provides this capability.

What you will learn:

• What Agile BI is and why it is important for transforming business\
• The foundations for Agile Data Services and other key elements to achieve Agile BI
• Customer examples on the use of Data Services to power Agile BI
• How Data Virtualization technology helps create a unified Agile Data Services layer in the enterprise

Wednesday
9 November
11:35-12:35

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In this session we will look at:

• Should you put effort into valuating your information assets?
• Methods to estimate the value of your data and information
• A sample comprehensive valuation method

Wednesday
9 November
11:35-12:35

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Understanding and Implementing Information Risk Management
Victoria Winningham, Principal, Metalethia LLC

Attendees will learn:

• What risk is, and what its components are
• The diverse ways in which risk is related to data
• How basic data quality projects can be part of a risk management framework
• Different approaches to risk mitigation
• Dealing with risk events after they have occurred.
  

Wednesday
9 November
13:10-13:50

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Session 1: Proven Strategies for Data Governance
Clarke Patterson, Product Marketing Data Quality, Informatica

Wednesday
9 November
13:10-13:50

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Session 2: Beyond Data Governance: Building Your Corporate Data Strategy
Jill Dyché, Vice President, Thought Leadership, DataFlux

Of course, your situation might not be as dire. Perhaps you’re just beginning your BI journey and want to position data as part of your overall program. Or maybe you need business help prioritizing your data projects.  How to get management’s attention? In this presentation noted consultant and author Jill Dyché will present a framework for a corporate data strategy that transcends the platforms and buzzwords-du-jour and positions information as worthy of its own investment and inarguably business-enabling.

What You Will Learn:

• Whether or not to try to quantify data as a corporate asset
• Which frameworks get traction with business executives
• How Jill knows on the first day of a project whether a company’s data will really be viewed as a corporate asset

Wednesday
9 November
14:00-15:00

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Embedding Information Quality Improvements into Organisations: The Case at Remploy

• The significance of the role of ‘Champions’ at all levels
• The importance of data quality performance management systems
• The necessity for systems and people that use them to be allowed to mature

Wednesday
9 November
14:00-15:00

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Wednesday
9 November
14:00-15:00

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Wednesday
9 November
14:00-15:00

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Laying A Foundation For Enterprise MDM at Shell

What delegates will take away from this session:

• How Shell approached the MDM Proof of Concept
• How Shell is deploying an Enterprise MDM Service
• Overview of challenges and key learnings
  

Wednesday
9 November
14:00-15:00

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In this session, we’ll discuss

• The reasons behind the gap,
• The not insignificant problems that the gap causes
• Ways that data governance can bring IT and the Business together to the benefit of all.
  

Wednesday
9 November
15:25-16:25

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A plethora of Information Quality Tools, Technologies, Consultancies are flooding the market. The treatment applied is allopathic in nature that suppresses the root of the 'Poor Information Quality (PIQ)' disease. This presentation covers:

• Simple ways to stop the Information Quality damage, as it starts to happen
• Realise dollar savings by using publicly available information
• Human and Non-human causes for PDQ. Examples provided

Wednesday
9 November
15:25-16:25

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Wednesday
9 November
15:25-16:25

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He will look at the aspect of information consumption and information creation with the universal aspects of information criteria and definition.

As such, he will show that information governance and strategy are the key drivers to manage the information capabilities, and go into detail on the architectural possibilities and the link between MDM and BI.

• The important role of Master Data Management in Business Intelligence
• Essential Information Governance methods
• Using an information strategy to scope your MDM and BI
• Expanding your BI to proper Information Governance and strategy

Wednesday
9 November
15:25-16:25

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Data Management at Statoil – A Methodology Case Study

• Data Management methodology and enablers
• Information architecture
• Master data management

Wednesday
9 November
15:25-16:25

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Data Integration for the Cloud, Web, Big Data and Social Media

• Integration of both key telecommunication and service providers applications using Cloud/Web Integration resulting in overall business improvements: 50% increase of in-store efficiency, 75% reduction of client wait times, streamlined go to market strategies for new product launches, etc.
• Leverage of Cloud and social media data to enrich loan/debt files and improve collection rates by over 40% (money goes straight to bottom line!) and improved search process productivity multiplied by 40, increasing agents capacity by over 5,300%.
• Integration for location based content services that are aggregated / enriched from hundreds of cloud sources, integrate social media in real-time and use large data stores on Hadoop.

Wednesday
9 November
16:30-17:30

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Wednesday
9 November
16:30-17:30

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The Intelligent Data Warehouse - A Meta Data Driven Approach

The “Nursery Approach” provides a framework and method for iteratively delivering value from the BI/DW platform whilst protecting core live services. The “Nursery approach” has been adapted from the best of traditional BI/DW method and agile methods.

This session will walk through a “Nursery Approach” study including patterns and techniques that include:-

• Nurseries – Data Laboratories / Development Sandpits and User Play pens.
• Self Service BI –including  linkage of local data.
• Data Services / Metadata driven approach.
• Front room / back room delivery
• Transplanting - Quality gates and assurance.
• Operational support & Security

Wednesday
9 November
16:30-17:30

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• Key terms including facts, dimensions, star schemas, and snowflakes
• When a dimensional model works, and when it can be pure evil
• The value of subject area, logical, and physical dimensional data models

Wednesday
9 November
16:30-17:30

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TimeInterval - A New Data Type - A Case Study

• Time-intervals (not just “points in time”)
• Consistency checks on time intervals
• Referential constraints across points of time and intervals

Wednesday
9 November
16:30-17:30

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Growing Your Customers and Revenue Through Better Use
of Your Master Data

Examples cited will be taken from projects in diverse industries including professional services, media/telecoms and high-value manufacturing.  The projects referenced include complexities such as multiple languages, rigorous compliance regimes and master data records numbering in the millions.