Strategic Information Technology - Level 2

Strategic Information Technology – Level 2

Course schedule

Classroom Training:
DateVenueDurationPrice
8 - 12 Jun 2026London5 days£4,995
17 - 21 Aug 2026London5 days£4,995
2 - 6 Nov 2026London5 days£4,995

Please note: prices shown above are exclusive of VAT (20%).

If you don’t see your preferred course date, please contact us.

Course Overview

Delegates build advanced capability in leading IT strategy and transformation. The course covers digital ecosystems, emerging technologies, and cybersecurity integration. Participants learn to evaluate technological investments for strategic impact. The programme equips IT leaders to drive innovation and enterprise growth.

Who Should Attend

IT and systems professionals managing information systems to enhance organisational strategy and decision-making. Past delegates have included:

  • IT Managers
  • Systems Analysts
  • Technology Strategists
  • Database Administrators
  • Digital Officers

Course Outcomes

  • Develop strategic frameworks for digital innovation and transformation.
  • Manage IT investments, vendor relations, and enterprise architecture.
  • Lead digital projects ensuring compliance, quality, and change management.
  • Incorporate emerging technologies into long-term business planning.
  • Build high-performing IT teams to deliver strategic value.

Course Topics

Industrial Data Integration

  • Leverage analytics in manufacturing and industrial engineering settings.
  • Integrate IoT and machine data for predictive operations.
  • Develop real-time analytics for asset utilisation and uptime monitoring.
  • Apply data standards to streamline industrial decision-making.

Predictive Maintenance Analytics

  • Use analytics models to predict equipment failure and maintenance needs.
  • Implement machine learning algorithms for predictive insights.
  • Design dashboards to visualise performance indicators and trends.
  • Optimise operational schedules through data-based forecasting.

Foundations of Data Analytics

  • Understand the core principles, tools, and methodologies in analytics.
  • Explore data lifecycle stages from collection to insight generation.
  • Apply descriptive, diagnostic, and predictive analytics techniques.
  • Develop problem-solving approaches using statistical reasoning.

Data Visualisation and Communication

  • Transform data into meaningful and actionable visual insights.
  • Use dashboards and storytelling to communicate analytical outcomes.
  • Apply visual design principles to enhance understanding and engagement.
  • Leverage software tools like Power BI and Tableau for visual analytics.

Predictive Analytics and Forecasting

  • Develop predictive models using regression and time-series techniques.
  • Apply machine learning algorithms for accurate forecasting.
  • Interpret predictive results to support business decisions.
  • Integrate predictive analytics into enterprise planning systems.

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