Conference Day 2: 5 November 2010

Friday
5 November
08:00-08:45

Back to top

Friday
5 November
09:00-10:00

Back to top

• How to Extend BI to Address a Wider Range of Business Problems and Business Users
• How to Make Information More Consumable Using Collaborative BI
• When To Use New BI Deployment Approaches Such as Open Source, Analytic DBMSs and Cloud Computing

Featured Speaker:

Colin White Founder BI Research To Speaker's Bio

Friday
5 November
10:30-11:30

Back to top

Mr. English describes the essentials for sustainable information quality management as a way out of the financial quagmire.

• Elevate the pain level until Executive Leadership Team (ELT) "feels the pain"
• Find the most significant business problems the ELT recognizes and measure the extent and costs of poor quality information
• Facilitate a Process Improvement Event for the broken Information Process
• Document the Return-on-Investment of the improved process
• Put the Information Process in Control to prevent recurrence of defects and business process failure

Friday
5 November
10:30-11:30

Back to top

Managing Metric Metadata

Attendees will learn about:

• The advantages and pitfalls of a generic approach to metric metadata management
• The added value of "Back-to-Front" metric metadata in the dashboard creation chain
• Some Dos and Don'ts when embarking on a dashboard project using metric metadata

Friday
5 November
10:30-11:30

Back to top

Concepts addressed will be:

• Determining where IT stops and business starts
• Developing effective organizations
• Maintaining efficient cost / benefit ratios
• Dealing with spread marts and culture change
• Internal process changes that will happen
• Deriving metrics to produce on going success

Friday
5 November
10:30-11:30

Back to top

Establishing and Operationalising Data Governance

• The challenges, pitfalls and success factors
• strategies to adopt
• How to establish and operationalise a Data Quality Management Program

Friday
5 November
10:30-11:30

Back to top

• The basics of cloud environments, and what sets them apart from previous generations of IT
• How enterprises are using the cloud today, and likely future directions
• Governance for cloud use, including security, and the challenge of master data management
• The structure and design challenges of columnar databases, such as Bigtable
• Basic techniques in columnar databases, such as MapReduce, indexing, and integrity.
• "Big data" and semantic applications built on cloud databases

Friday
5 November
11:35-12:35

Back to top

A Canadian Healthcare Organization Awakens to Data Quality

• Which process changes led to the largest DQ improvements
• Forcing functions - Data profiling, integrating DQ into the strategic technology roadmap and our staff teaching a University DQ course
• Our Data Quality Management Framework - diagrams, models and flows

Friday
5 November
11:35-12:35

Back to top

• Spreadsheet implications - the good, the bad and the ugly
• Balancing agility and control in decision making
• The Adaptive Analytic Cycle - a new model for analytic work
• The role of social computing in adaptive analytics
• Promoting individual innovation to corporate governance

Friday
5 November
11:35-12:35

Back to top

Virgin Money Leverages Open Source Business Intelligence to Help Charities and Fundraisers

The IT team was experienced with modern, open, standards-based technologies. To keep costs low without sacrificing functionality or performance, the team quickly established a preference for open source technologies for Web application and presentation, database management, data integration, and Business Intelligence (BI). They evaluated leading open source BI platforms-and chose a solution for its ease of integration and more robust reporting requirements anticipated for the larger charities. The team found the technology to be stable, high-performing, and robust. As a result, the site has been well-received by philanthropies. The service is powerful, easy to use and low cost.

Friday
5 November
11:35-12:35

Back to top

• How we keep data managers in the centre of strategic conversations
• Forces for radical change in data management
• Highlighting clear business benefits for data management
• Best practices identified

Friday
5 November
11:35-12:35

Back to top

We will be discussing several key factors that lead to project success, including:

• Methodology
• Team Structure
• Unique documentation and testing approach (Technical)
• Abstraction of rules, re-usability, and object oriented approaches (Technical)
• Planning and testing
• Lessons Learned
• Questions

Friday
5 November
13:20-13:50

Back to top

Session 1: Agile BI & Agile Data Services: A Perfect Fit
Suresh Chandrasekaran, Sr. VP, Denodo Technologies

You will learn:

• What is Agile BI and why it is important for transforming business
• Agile Data Services foundation and other key elements to achieve Agile BI
• Customer Examples on use of Data Services to power Agile BI
  

Friday
5 November
13:20-13:50

Back to top

Session 2: Top 10 things NOT to do when outsourcing/off shoring BI/DW applications
Rajesh Shashikant Naik, UK Practice Head (BI/DW), Wipro Technologies

1. Peculiarities of DW/BI outsourcing/off shoring.
2. What should be avoided (and what should not be).
3. How to leverage the outsourcing partner's strengths to achieve the purpose.

Friday
5 November
14:00-15:00

Back to top

You Will Learn:

• Why it is important to have an objective measure of data model quality\
• How to apply the core ten categories that make up the Scorecard including correctness and completeness
• How to introduce the scorecard into a development methodology and your company culture

Friday
5 November
14:00-15:00

Back to top

What are the economic drivers that are demanding better Business Intelligence, How are vendors rising to the challenge ? What are early adopters doing now and next ?

Friday
5 November
14:00-15:00

Back to top

• The role of a Master Data repository from a BI-perspective
• Usage scenarios for MDM (Analytical Operational, Collaborative) and how it relates to BI
• ETL and Master Data challenges
• Why the data warehouse in some cases is too late in the information supply chain to create a single version of the truth

Friday
5 November
14:00-15:00

Back to top

Corporate Data Strategy: Insights From Proven Approaches Using the Example of Nestlé

• What is so strategic with corporate data;
• The business value of corporate data;
• Nestlé's experiences and future plans.

The presentation will report on the experiences of the Competence Center Corporate Data Quality which is a consortium research program comprising a number of enterprises from various industries (Bayer, Beiersdorf, Deutsche Telekom, Deutsche Bahn, IBM, Nestlé, Novartis, Siemens among others), plus the Institute for Information Management of the University of St. Gallen (IWI-HSG).

Friday
5 November
14:00-15:00

Back to top

Business Semantics Driven Information Governance: a Case for the Flemish Public Administration
Stijn Christiaens, COO, Collibra

In this talk you will learn:

• That your organization already has much valuable metadata as building blocks for business semantics
• Reconciliation of these metadata into sharable and reusable semantic patterns requires a systematic approach and careful selection of technologies
• The application of business semantics for EAI is much better than traditional point-to-point or hub-and spoke approaches
• Identify business drivers that convince senior management to prioritize and free the necessary budget and resources accordingly
• Outline a road map to implement business semantics management as part of the overall information architecture and governance plan.

We illustrate these points with a realistic case in the Flemish Ministry of Education and Training, and point out important challenges for the future.

Friday
5 November
15:30-16:30

Back to top

Drawing on historical parallels from industry, psychology, and a case study from a leading European financial services organisation, this tutorial aims to provide practical tools as well as raising other significant issues which should be considered by information Quality Leaders in organisations today.

Friday
5 November
15:30-16:30

Back to top

• The different types of operational BI: Traditional data analytics versus Event analytics
• Architectural components of operational BI
• Extending the traditional BI environment to support operational BI
• Developing an operational BI strategy
• New operational BI techniques: Low-latency data analytics using traditional BI, Analyzing current data using data federation, Embedding BI services in business processes, stream analytics

Friday
5 November
15:30-16:30

Back to top

• This structured and agile, top-down architecture and bottom-up implementation approach supports co-existing but distinct BI/PM initiatives in organizations well.
• This approach turns Excel from the most used into the most usable and useful BI/PM tool.
• Generate the ETL code to build and fill the Data Warehouse and Data Marts, based on the knowledge in the organization that is captured in a Semantic Wiki.
• Store the facts and the knowledge in the organization continuously, present the user at any time all the truth (s)he requires at that time.

Friday
5 November
15:30-16:30

Back to top

Shell's Journey in Deploying a Global Data Architecture Strategy

• pre-requisites and business benefits
• the basic building blocks that need to be in place
• how Shell is getting them there
• the already realized and hoped for benefits
  

Friday
5 November
15:30-16:30

Back to top

How Do You Get a Business Person to Read a Data Model?
Christopher Bradley, Business Consulting Director, IPL

This session discusses:

• How to use high-level data models to communicate with businesspeople to get the core information you require to build robust database applications
• What core information is needed, how this can be easily communicated to businesspeople, and what visual constructs to use to get their attention
• A real-world case study at a major international oil company
• Templates and guidelines for a step-by-step approach to implementing a high-level data model in your organization
  

Friday
5 November
16:30-17:30

Back to top

IQ Management Implementation at NATO HQ - A Data Manager Presentation

• Set up a Monitoring System to analyze, target and correct data and bring visual results to the Process Owners and the Management.
• Meeting the Process Owners to coordinate Business Procedures understanding and review. Data correction will be supervised at process level.
• Constantly improve the Monitoring System to control quality: decision to assign CTQ error codes, elaborate complex reports and accuracy checks.
• Assessing Information Quality: calculate 6 sigma levels into processes and downstream, generate Pareto Diagrams to conduct quality improvements, measure cost of scrap and rework.

Friday
5 November
16:30-17:30

Back to top

• Hard and soft information - how they differ and why it matters
• Modelling soft information and the real meaning of metadata
• New storage paradigms - from reinventing relational to the NoSQL debate
• Balancing the requirements for hard and soft information - a unified information store
• Merging BI query and content search for pervasive information usage

Friday
5 November
16:30-17:30

Back to top

• How to apply the core ten categories that make up the Scorecard to your data warehouse
• How to change focus when a dimensional model is chosen over a relational
• How data warehouse architecture influences data model review criteria

Friday
5 November
16:30-17:30

Back to top

Insight Driven 1:1 Customer Management - a Programme Management Approach Applied to Leveraging Data Assets

• Building a Data Warehouse is only half the story
• Creating the means to utilise it is just as important
• Thought leadership avoids re-inventing wheels
• Incremental steps balanced between architectural elegance of the solution and the realisation of benefit ensures momentum
• A programme management approach ensures focus on business outcomes benefits

Friday
5 November
16:30-17:30

Back to top

Generating XML Schemas from a Logical Data Model - A Practical Example
George McGeachie, Metadata and Modelling Specialist, Metadata Matters Ltd

In this session, we will examine the factors to be considered when designing XML Schemas based upon a Logical Data Model, and demonstrate the capabilities and approaches of two mainstream data modelling tools to successfully generate and manage XML Schemas (XSDs). Attendees will take away an understanding of:

• the benefits of managing XML Schemas in the same way as we manage database schemas
• the data design challenges to be overcome
• the decisions and trade-offs to be made when generating XML Schemas from Logical Data Models