Managing Data as an Asset Program

This program equips business and IT executives with the strategic frameworks to govern, scale, and leverage enterprise data assets for sustainable competitive advantage.

Rather than focusing solely on technical deployment (addressed in the Deploying Data Technologies Program), this program delivers a blueprint for scaling data initiatives, helping leaders navigate the shift from initial pilot projects (proof-of-concept) to robust, enterprise-wide production.

This bespoke program (described below) bridges the gap between high-level business goals and technical capability, addressing critical leadership priorities including data governance, organizational design, modern talent sourcing, cybersecurity, compliance, and legacy system integration. Participants will learn to:

Manage IT/data resources strategically, addressing governance, value, organizational structure, and the integrated roles of the CIO-CTO-CDO-CAO
Build and manage the data/analytics organization, including reporting structure, skills, sourcing, and governance
Align data and analytics initiatives with business areas, addressing technology, skills, organizational structure, and governance
Choose a specialization in managing AI, blockchain, RPA, or textual analytics initiatives for competitive advantage
Evaluate and adopt emerging data and analytics technologies — data lakes/lakehouses, data mesh, NoSQL/NewSQL, and real-time streaming architectures

Select at least 4 courses from the following:

Courses 1 – 3 are required
All courses are available face-to-face and synchronously online
Courses marked with an * are also available asynchronously via the GIIM Cloud/Web

1. Managing IT Resources*

This course takes a comprehensive information and resource perspective of business strategy by addressing the strategic, tactical, and operational roles and responsibilities across the business for managing data as a strategic business asset.

While the alignment of business and IT is the primary focus, emphasis is placed on the current/emerging issues/opportunities in creating and coordinating the significant initiatives necessary to ensure IT’s contribution to the success of the organization; in essence as IT is shaping global markets and impacting the enterprise, how must IT reshape itself. This is done by examining important considerations such as governance, demonstrating value, IT processes, IT organizational structure, HR & sourcing, managing emerging technologies, the integrated roles of the CIO-CTO-CDO-CAO, and IT-business strategy. By concentrating on ITs strategic responsibilities, this course puts the candidate in the role of an IT leader as they build a business strategy that is enabled/driven by IT. It is the first course in the Certificate as it lays the groundwork for understanding how IT must evolve to remain relevant in a world where profound changes in business, economics, environment, and technology have become the norm.

2. Building & Managing the Data/Analytics Organization *

This course addresses the organizational elements of the Data and Business Analytics (including cognitive computing and robotics process automation) functions by focusing on the management, structural/reporting, and human resource/skills considerations of data and business analytics. Topics such as determining where the group(s) should report, how they are assessed/measured, the necessary skills and how to source them, key data/analytics/cognitive computing processes, data governance, how to lead data-driven innovation in products and services, IT and non-IT roles, and customer and competitor alignment, all driven by the demand to improve the quality and speed of business decisions, minimize the risks/challenges for implementing them, and how to leverage data as a strategic asset. By concentrating on IT’s data, analytics, and cognitive computing responsibilities, in essence this course puts the candidate in the role of the CAO/CDO (Chief Analytics Officer/Chief Data Officer) as they define the vision, strategies, missions, and build the management processes and organization/skills necessary to deploy these data driven initiatives. The course focuses on the important organizational structure in terms of separate or combined organizations, and placement within the overall enterprise and IT organizational structures. This course is geared for managers and consultants engaged in building and growing this organization, including CIOs and non-IT executives to help prepare the enterprise to leverage their investment in Big Data/BA. It combines the optional Building & Managing the Analytics Organization and Building & Managing the Data Organization courses (A & B) below.

3. Aligning Data & Analytics with the Business Areas *

While data is growing exponentially, every organization is discussing strategies that consider data as a strategic business asset. This course focuses on how to get the entire business effectively engaged to take full advantage of data, business analytics, and cognitive computing initiatives. Business leaders, suppliers, and customers have greater expectations than ever before as they demand that data and analytics are always available from anywhere, while maintaining high levels of security and privacy in compliance with all applicable regulations.

Empowering every employee across the business with data & analytics as a service is often a complex challenge, particularly in the face of rapidly evolving landscape as ALL data must be considered whether from social media, web traffic logs, machine data from sensors, data from 3rd parties, in addition to the traditional data collected from systems of record applications. Understanding data policy and all of the issues of governance, ethics, security, and privacy is fundamental.

By concentrating on the current and emerging approaches for aligning IT and business data/analytics initiatives, in essence this course puts the candidate in the role of the CAO/CDO (Chief Analytics Officer/Chief Data Officer) as they ensure all areas of the business are prepared to effectively and efficiently leverage data as a strategic asset. The course focuses on the following 4 areas/groups/sections:

Current & Emerging Technologies/techniques & their Strategic Uses
Skills, Roles, Sourcing, and other HR Considerations
Organizational Structure & Reporting Considerations
Governance (Strategic, Tactical, Operational) Considerations

Select At Least One (1) From The Following:

I. Managing AI Initiatives *

Artificial Intelligence (AI) has existed for decades, but its capabilities, risks, and industry‑wide impact are accelerating faster than any prior technology wave. AI is no longer a technical experiment; it is a strategic leadership mandate. This course equips both IT and non‑IT executives to design an enterprise AI strategy, govern AI initiatives, structure the organization to leverage AI, and deploy AI solutions that generate measurable business value while protecting the enterprise. Special emphasis is placed on the emerging responsibilities of the Chief AI Officer (CAIO).

Participants will learn how AI differs fundamentally from traditional software, including its strategic lifecycle, data‑driven architecture, probabilistic behavior, risk profile, governance demands, and organizational implications. The curriculum spans the full set of leadership considerations required to manage AI initiatives, including strategy, architecture, ethics, security, workforce readiness, change management, regulatory compliance, organizational design, reporting structures, and cross‑functional execution.

A core theme of the course is the evolving relationship between humans and intelligent systems. Rather than treating AI as a job eliminator, we examine how AI augments human capability, reshapes roles, and enables new forms of collective intelligence—where people and machines collaborate to solve problems previously considered unsolvable

By the end of the course, participants will be able to:

Build an enterprise AI strategy aligned with business goals, risk appetite, and organizational maturity
Distinguish between classic software and AI systems in strategy creation, planning, development, governance, and operations
Understand the major categories of AI initiatives (industry‑specific front office, back office, machine learning, predictive, generative, and agentic AI)
Evaluate AI opportunities and constraints across functions, processes, and data ecosystems
Lead responsible AI adoption, including workforce enablement, organizational and sourcing decisions, change management, and ethical considerations
Oversee successful deployment, scaling, and continuous improvement of AI solutions across the enterprise

Graduates will leave with a practical, actionable framework for leading AI initiatives, equipping their organizations to innovate confidently and safely, compete effectively, and harness AI as a strategic asset.

II. Managing Blockchain Initiatives *

Candidates completing this Certificate would also be eligible to receive a GBA Certification.

While having over a 10-year history, Blockchain is still actively evolving to where it is now emerging as an important technology across every industry. With all of the buzzwords flying around, it can still be difficult to separate Blockchain hype from business reality. The purpose of this course is to prepare IT and non-IT managers for creating effective Blockchain strategies and plans that leverage Blockchain for competitive advantage. The focus of this course will be on learning the essentials of Blockchain, preparing Management Professionals to lead industry current and future business application initiatives, and deriving Blockchain deployment strategies, business cases, and plans, as well as considerations for organizational structure, sourcing, security, legal, and governance processes.

Through an engaging mix of understanding the current and emerging Blockchain technologies, business insights, industry examples, and their impact on the business, the learning journey will bring into sharp focus the reality of contemporary Blockchain and how it can be harnessed to support representative cross industry as well as industry specific (e.g. Finance, Retail, Healthcare) applications.

Focusing on essential Blockchain and related technologies, such as smart contracts, oracles, identity, consensus and tokenization, this course will help candidates understand the implications of these new technologies for strategic business initiatives, as well as the economic and societal issues they address. The course will also examine how Blockchain will complement and strengthen the workforce, how roles may change in an organization ecosystem including considerations for governance, sourcing, security, and organizational considerations, and the overarching potential that Block chain can have on every industry.

Additionally, the course will emphasize how the power of the network and distributed computers can solve business problems that not long ago were impossible.

Upon completion of this course IT and non-IT candidates will be prepared to deliver an organizational Blockchain strategy that addresses specific technology management and organizational aspects for ensuring successful deployment of Blockchain.

III. Managing Robotics Process Automation Initiatives

RPA is a foundational technology reshaping business processes across the enterprise. This course prepares IT professionals, business analysts, BI developers, data architects, and system integrators with the tools and practices needed for successful RPA deployment.

Candidates learn to distinguish Robotic Process Automation (which automates rules-based tasks with structured data and deterministic outcomes) from Cognitive Automation (which uses inference-based algorithms, machine learning, and deep learning to process unstructured data like natural language and produce probabilistic outcomes). RPA “takes the robot out of the human,” automating repetitive tasks so people can focus on judgment-driven work. Candidates leave prepared to build and launch an RPA implementation plan for your organization.

Select to see interview on RPA

IV. Managing Textual Analytics: Hearing the Voice of the Customer

The purpose of this course is to equip IT and non-IT managers with the insights required to achieve and sustain business value through mining/leveraging textual data/information. While it has always been important to listen to your customer, the way you listen to your customer today is very different than it was even a year ago. Knowing your customer and listening to them is essential to succeed in today’s digital world.

There are MANY places to hear the voice of your customers/clients, including:

what people are saying in your call center
feedback that has been directly solicited
the Internet. The Internet is filled with sites where people discuss the merits of the companies and their products
email

This course focuses on leveraging textual analytics by hearing and listening to what your customer is saying to you. The course will also address the important governance, roles/responsibilities, skills, sourcing, and organizational considerations necessary to derive a textual analytics business strategy.

V. Managing Emerging Data & Analytics Technologies *

Data is now the primary driver of organizational intelligence, automation, and competitive differentiation. This course prepares executives to understand, evaluate, and lead the adoption of current and emerging data and analytics technologies—spanning modern data platforms, AI/ML ecosystems, cloud-native architectures, and real‑time decisioning environments.

Although this is the most technical course in the certificate series, the emphasis remains on management-level decision-making: how leaders assess data technologies, architect scalable solutions, govern data responsibly, and translate analytics capabilities into measurable business value.

Participants will learn the distinctions between traditional systems of record built on ACID‑compliant relational databases and today’s distributed, schema‑flexible NoSQL and NewSQL platforms. The course explores cloud-scale data layers, data mesh and data fabric architectures, master data management, data curation at enterprise scale, and the modernization of data warehouses into real‑time, streaming-enabled analytical environments.

Executives will examine how emerging technologies—AI/ML, generative AI, IoT telemetry, edge analytics, crowdsourced data, open data ecosystems, and third‑party enrichment services—reshape how organizations collect, integrate, secure, and leverage data. The course positions participants in the role of a modern CAO/CDO, responsible for building data-driven organizations that can operationalize analytics at scale.

What Participants Will Learn

How to evaluate and select emerging data and analytics technologies using structured, business‑aligned criteria.
How to differentiate between relational, NoSQL, NewSQL, graph, and vector databases—and when each is appropriate.
How to design and modernize data architectures, including data lakes, lakehouses, data mesh, and real‑time streaming pipelines.
How to cleanse, curate, and shape data from an expanding universe of internal, external, and crowdsourced sources.
How to integrate third‑party and open data (e.g., geospatial, demographic, behavioral) to enhance analytics and AI models.
How to assess cloud-native data services, legacy modernization strategies, and hybrid/multi-cloud data governance.
How to evaluate and adopt emerging analytics capabilities such as generative AI, cognitive computing, anomaly detection, and automated decisioning.
How to manage data privacy, security, lineage, and regulatory compliance in increasingly complex data ecosystems.
How to build organizational structures, governance models, and talent strategies that support enterprise-wide analytics maturity.

Topics Covered Include

Modern data architectures: data lakes, lakehouses, data mesh, data fabric
ACID vs. BASE, relational vs. NoSQL/NewSQL, graph and vector databases
Cloud-native data platforms and legacy data warehouse modernization
Real-time analytics, event streaming, and operational intelligence
Data governance, privacy, security, lineage, and regulatory frameworks
AI/ML, generative AI, cognitive computing, and automated analytics
IoT, edge analytics, and sensor-driven data ecosystems
Crowdsourced and third‑party data integration
Data quality, curation, and enterprise-scale data management
The evolving role of the CAO/CDO in data-driven transformation

Optional Programs & Courses to Choose From

A. Building & Managing the Analytics Organization

In essence it takes a similar perspective as course B below, but instead of focusing on the role of the CDO (Chief Data Officer), it focuses on the role of the CAO (Chief Analytics Officer).

This course addresses what the Analytics and Cognitive Computing functions should look like by focusing on the management, organizational, and human resource considerations for leveraging analytics. It addresses the emerging job roles of data governance, data stewards, data curators, data scientist, master data architects, data security & privacy, data engineers & architects, and data scientists, as well as centers of excellence/ competency. Managing data as an asset requires significant transformation at many companies. There are cultural issues that must be dealt with, and learning how to manage transformation is a critical skill. Topics such as where the group should report, how they are assessed, the necessary skills and how to source them, key data/analytics processes, integration strategies, data governance, data-driven innovation in products and services, data security/privacy and standards, IT and non-IT roles, customer and competitor drivers, and understanding how the preceding can be used to improve the quality and speed of business decisions and processes, and the risks/challenges for implementing them to leverage data as a strategic asset are fundamental. By concentrating on ITs data and analytics responsibilities, in essence this course puts the candidate in the role of the CAO (Chief Analytics Officer) as they build the management processes and organization/skills necessary to deploy these data driven strategies.

B. Building & Managing the Data Organization

In essence it takes a similar perspective as course A above, but instead of focusing on the role of the CAO, it focuses on the role of the CDO (Chief Data Officer).

This course addresses the organizational elements of the Data and Business Analytics functions by focusing on the management, structural/reporting, and human resource/skills considerations of data and business analytics. Topics such as determining where the group(s) should report, how they are assessed/measured, the necessary skills and how to source them, key data/analytics processes, data governance, how to lead data-driven innovation in products and services, IT and non-IT roles, and customer and competitor alignment, all driven by the demand to improve the quality and speed of business decisions, minimize the risks/challenges for implementing them, and how to leverage data as a strategic asset. By concentrating on IT’s data and analytics responsibilities, in essence this course puts the candidate in the role of the CAO/CDO (Chief Analytics Officer/Chief Data Officer) as they define the vision, strategies, missions, and build the management processes and organization/skills necessary to deploy these data driven initiatives. The course focuses on the important organizational structure in terms of separate or combined organizations, and placement within the overall enterprise and IT organizational structures. This course is geared for managers and consultants engaged in building and growing this organization, including CIOs and non-IT executives to help prepare the enterprise to leverage their investment in Big Data/BA.

C. Building the Requisite Organization Structure for Data & Analytics

This course introduces specific methods of organization structure analysis and design, and integrates previous learning in IT strategy, IT organization maturity, the CAO/CDO [Chief Analytics Officer/Chief Data Officer] role, governance, and HR considerations. The course emphasizes methods and considerations for organizing a new IT analytics unit and/or for strengthening an existing analytics unit.

Managing data as an asset requires significant transformation at many companies. Issues such as where the IT organization should report, how the CAO/CDO role should be positioned and their relationship to the CIO and non-IT organizations, what roles and levels of capability are required to deliver and leverage high-value analytics capabilities, and how to put in place effective IT governance processes for data analytics initiatives have become critical concerns. In addition to these issues, IT executives also must examine their existing IT organization structure and staffing; then plan and put in place organization changes to bring the IT organization into alignment with corporate business strategy.

IT strategy – typically framed in terms of broad goals and objectives – is the starting point for organization design. Once decided, strategic vision must be operationalized into operating units, specific roles, role relationships, accountabilities, authorities, etc. The Strategic Alignment Model and the IT Maturity Model introduced in the previous course – Leveraging IT Resources – are used in this course as a framework for discussing topics such as markers of effective organization structure, identifying and diagnosing causes of IT organization structure problems, templates for optimum IT organization structure , and managing organization change.

By concentrating on the challenges of designing and implementing an effective IT organization design, this course puts the candidate in the role of CAO/CDO[Chief Analytics Officer/Chief Data Officer] as they build a new analytics capability and/or improve their existing capabilities.

There is an optional 2-day course that provides participants with a hands-on experience for applying these organizational concepts to their organization using an effective modelling tool.

D. Industry Specific Courses

While experience with the business and management considerations for implementing data management, statistics, modeling, and BI tools is recognized as fundamental, understanding how industries are being transformed is also considered essential to a successful career in Business Intelligence/Big Data. GIIM has courses in the following industries to help prepare candidates with the requisite industry expertise: Finance, Pharmaceutical, Healthcare, Manufacturing, Hospitality, Government, Telecommunications, Energy, Retail, Insurance, Transportation, etc.

As organizations accelerate their digital transformation initiatives, they are focusing their investments in leveraging emerging information technologies for competitive advantage. It has become essential to understand how to effectively and efficiently manage an organization’s data resources, to reach these objectives. There are numerous strategic, tactical, and operational choices to be made about managing data resources and it is essential to ensure that IT and non-IT executives across the organization work in harmony.

Experience has made it clear that organizations need well-conceived organizational structures, skills, processes, and decision rights to ensure that data technologies are appropriately leveraged across the organization, especially when considering the impact that emerging information technologies is having.

This course prepares executives/professionals by providing a comprehensive understanding of the fundamental decisions related to the management of data. The course will also provide an overview of current and future relevant data related technologies and their potential impact on industry and their associated stakeholders.

The course is designed to be delivered live/synchronously (face-to-face or online) with a total of twenty (20) contact hours. While the schedule is flexible, it is usually delivered in approximately ten (10) 2-hour modules/lectures/sessions.

The data topics include:

Deriving IT-business data strategies
Considerations for types of organizational structure, sourcing, governance (i.e., decision-making and decision rights), roles/responsibilities, and processes
Leverage emerging data related technologies
The business value of data
The definition, concepts, and contexts of data
Enhancing business-IT alignment