For many companies today, there is a real desire to become data-driven. A key first step in achieving this, is to create a data strategy that sets out a roadmap on how to get there.  When defining a data strategy, most companies are faced with two broad challenges.

The first is how to reduce risk to get data under control, govern it, and build trusted data products that they can consume and use. This needs to happen in an environment where regulation is increasing, data complexity is growing with thousands of data sources, and many different types of data stores both on-premises, in SaaS applications and in one or more clouds. The second is how to maximize the use of data and analytics for competitive advantage to disrupt the market(s) you compete in. Data strategy therefore needs to be defensive as well as offensive. 

So how do you do this? What do you need to do to build a data strategy? What things should be in a data strategy? What should you include in a defensive data strategy versus an offensive one? This 1-day course looks at this challenge and seeks to find a way to build a data strategy that enables both defensive and offensive data programs and brings them together to create a competitive advantage in a data-driven enterprise. 

Why attend

You will learn how to build a data strategy for a data-driven enterprise that delivers business value while improving data governance.

Who should attend

Chief Data Officers, Chief Information Officers, Heads of Data Governance, Data Architects, Data Engineers, Solution Architects, Heads of Analytics,  Data Warehouse Managers, Data Administrators and Business Unit Managers responsible for Data.

Code: DST2024
Price: EUR 725

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  • What is a data strategy?
  • Why is it needed?
    • Key stages in building a data strategy
    • Business strategy alignment – a critical success factor
    • Understanding your current setup
    • Defining a future setup to reduce risk and improve competitive advantage
    • Providing a roadmap to help achieve your business goals, priorities, and targets

Business Strategy Alignment

  • Understanding the components of a business strategy
    • Business vision
    • Strategic business objectives
    • Key performance indicators (KPIs)
    • KPI Targets
    • Executives accountable for achieving targets and goals
    • Strategic business priorities
    • Business initiatives and budgets
  • Defining a vision for becoming a data-driven enterprise

Understanding and Assessing Your Current Setup

  •  Understanding and assessing how your business currently works
    • Critical operational business processes
    • Critical managerial analytical business processes
    • Identifying problems caused by data
  • Understanding and assessing existing
    • Organisational structure currently managing and governing data
    • Data and analytical projects
    • Skillsets
  • Understanding and assessing
    • Existing data estate
      • Data sources, types of data stores on-premises, in multiple clouds, SaaS applications and at the edge
    • Existing data capabilities in use
      • File systems, content management systems, transaction data stores, data warehouses, data lakes, lakehouses, graph databases, streaming data systems, master data management
    • Existing analytics capabilities in use
      • BI reports, ML models, AI-bots
    • Existing data architecture
    • Critical operational business process data flows within and across systems
    • Existing analytical system data flows
    • Existing business unit data capture and processing
    • Existing data and analytics technologies
      • Data stores, data integration tools, data catalogs, application and business process integration tools, BI and data science tools
    • Existing data governance setup 
      • Data governance disciplines, people, processes, policies, technologies, data governance capabilities, regulatory obligations, policy enforcement techniques, and current projects
    • Identifying the impact of ungoverned data on business processes, business performance and compliance
  • Documenting and ranking business cases where data issues restrict business from achieving its goals 
  • SWOT and Gap analysis 
  • Gauging where you are on a maturity model

Defining Your Future Setup

  • Defining future organizational structures for:
    • A Data Program Office
    • Data Governance
    • Implementing operational data flows
    • Building data products for use in analytics
    • Knowledge management
  • Defining future data architecture for operational and analytical data flows, content and knowledge management
  • Recommending new data capabilities
  • Recommending new data technologies
  • Defining a defensive data strategy
    • Defining operational data flows to reduce risk
    • Use data and analytics to reduce risk
      • Defining what data products, analytical products needed to reduce different types of risk
      • Align with business strategy compliance and risk objectives and priorities
    • Defining a data governance framework
    • Defining data governance disciplines and policies for compliance and risk reduction, e.g., data privacy, data access security, data loss prevention
    • The role of data observability, data intelligence and active real-time data governance
  • Creating an offensive data strategy to drive competitive edge
    • Align data products, analytical products, and decision services with business objectives and priorities to improve profitability
    • Growing revenue
      • Define what data capabilities, data products, analytical products, decision services needed to grow revenue
      • Creating a Customer 360o data platform and analytics to drive revenue
      • Integrating customer data and insights into marketing, sales and customer service
    • Reducing cost
      • Defining common application and business process integration capabilities
      • Defining new operational data flows to improve efficiency and reduce costs
      • Using master data to reduce costs and increase agility
      • Define what data products, analytical products, decision services needed to reduce cost
    • Creating a data platform and changing your data architecture to support both

Implementation Roadmap

  • Managing expectations – the promise of building data and analytical products using rapid data integration and machine learning
  • Identifying high-value business cases and quick wins
  • Defining the data projects needed to implement your data strategy
  • Classifying data projects by business objective to align with business strategy
  • Identifying accountable business executives to sponsor your strategy
  • Defining business and IT personnel needed
  • Defining a roadmap to incrementally bring your data strategy to life
  • Implementing data governance as part of your data strategy
  • Defining how to measure success
  • Communicating and evangelizing business value


Mike Ferguson


Mike Ferguson is the Managing Director of Intelligent Business Strategies Limited. As an independent IT industry analyst and consultant, he specializes in BI/Analytics and data management. With over 40 years of IT experience, Mike has consulted for dozens of companies on BI/analytics, data strategy, technology selection, data architecture and data management.

Mike is also conference chairman of Big Data LDN, the fastest-growing data and analytics conference in Europe and a member of the EDM Council CDMC Executive Advisory Board. He has spoken at events all over the world and written numerous articles.

Formerly he was a principal and co-founder of Codd and Date Europe Limited – the inventors of the Relational Model, a Chief Architect at Teradata on the Teradata DBMS.

He teaches popular master classes in Data Warehouse Modernization, Big Data Architecture & Technology, How to Govern Data Across a Distributed Data Landscape, Practical Guidelines for Implementing a Data Mesh (Data Catalog, Data Fabric, Data Products, Data Marketplace), Real-Time Analytics, Embedded Analytics, Intelligent Apps & AI Automation, Migrating your Data Warehouse to the Cloud, Modern Data Architecture and Data Virtualisation & the Logical Data Warehouse.


26 Nov - 26 Nov '24


The fee for this course is EUR 725 (+VAT) per person.

We offer the following discounts.

  • 10% discount for groups of 2 or more students from the same company registering at the same time.
  • 20% discount for groups of 4 or more students from the same company registering at the same time.

Note: Groups that register at a discounted rate must retain the minimum group size or the discount will be revoked. Discounts cannot be combined.

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