The integration of these technologies is the impetus for enterprise changes enabled and driven by IT beyond the traditional cost savings brought by business process and productivity improvement; it is the growing trend around the globe of leveraging IT for revenue generating initiatives that has made this so noteworthy. It is the overall return on information that is generating revenue! These initiatives are driving the most significant transformational changes for the next decade and beyond. 

Information will be to the 21st century what steam, electricity, and fossil fuel were to prior centuries. How we harness this potential and take advantage of these emerging, and disruptive, technologies may become the central question for management over the next several years.

We are creating 2.5 quintillion bytes of data every day (that's 2.5 followed by 18 zeros). To harness that potential, companies need A.I. to make sense of the data, and hybrid cloud computing platforms that can distribute it across organizations.

A report from MIT says, digitally mature firms are 26% more profitable than their peers. McKinsey Global Institute indicates that data-driven organizations are 23 times more likely to acquire customers, six times as likely to retain customers and become 19 times more profitable.  Overall, Data and Analytics today are the next frontier for innovation and productivity in business. But achieving a sustainable competitive advantage from Data and Analytics is a complex endeavor and demands a lot of commitment from the organization. Gartner says only 20% of the Data and Analytic solutions deliver business outcomes. A report in VentureBeat says 87% of Data and Analytics projects never make it to production.

Our annual IT management trends research over the last 20+ years has placed big data/business analytics as the number one emerging technology investment around the globe. This, in concert with the trends research also indicating a global increase in the use of IT for revenue generating initiatives, is demanding organizations to address how to leverage this important set of technologies.

The focus of these courses is to address how organizations can get value from Data and Analytics. Specifically, how can enterprises leverage the data, AI (Artificial Intelligence) and BI (Business Intelligence) for competitive advantage?  Having IT and non-IT executives working in harmony to reconcile questions like the following have become essential:

• What is our data and analytics strategy?
  
• Are our strategic, tactical, and operational governance processes effective for data and analytics across the business and IT?
  
• Are the above integrated across other new and "older" technologies?
• Are we organized to harness the value of our data?
  
• How and what data should we capture? 
  
• Where should we store the growing availability of data?
  
• What analysis is possible and worthwhile?
  
• Do we have the right IT, business, and industry skills?
  
• Who should be responsible? 
  
• What are the long term business implications for cognitive computing, AI, blockchain, and robotics process automation?
  
• What ethical and regulatory questions and considerations might arise and how to deal with them?
  
• How could/should our business model change based on the above?
  
• What are the different strategies and considerations when introducing these new technologies versus when scaling up the use of these technologies 
  

The World Economic Forum estimates that over 130 million jobs will be created globally in new professions, where demand for data scientists, software engineers and a myriad of roles requiring digital skills are growing rapidly. In addition, successful managers and leaders increasingly require a strong working knowledge of digital technologies, as well as 21st century leadership skills including the ability to be adaptable, innovative and creative.

Recognizing that these initiatives demand more than just technical skills is imperative. Bad data leads to bad decisions. This has been most recently demonstrated in the dramatically missed projections for the 2016 U.S. Presidential election. Other examples include sports teams that have used “faulty data” in selecting new players or in deciding what plays to call or in the placement of players for a play. What erroneous decisions has your organization made; you might not even be aware until it is too late??? 

Successful use of these complex tools requires expertise in more than just technologies and data; they require the convergence of technology, data, statistics, business, industry, tools/products, and the ability to work in a team (IT and non-IT). The purpose of this certificate is to prepare candidates with the leadership/management skills necessary to meet the challenges and deliver valuable results.

To be successful in leveraging data and business analytics, organizations need to understand how to move from big data to smart data, and more importantly, how to obtain demonstrable value from these important initiatives. To be successful demands more than having the technical skills provide  d by our Deploying Business Analytics Certificate . An appropriate balance of the business, management, leadership, technical, industry, and interpersonal skills, provided in this Managing Data as an Asset Certificate, are essential. This Certificate will address the integration of the information technologies that are required to have a successful big data/business analytics/knowledge management strategy across the enterprise including AI (artificial intelligence), robotics process automation (Cognitive Computing), Block Chain, IoT (internet of things), Bring-Your-Own-Infrastructure, and SMAC (Social, Mobile, Business Analytics, and Cloud). 

The impact of big data analytics touches every area of the enterprise – marketing, sales, research, finance, human resources, supply chain, customer relations, legal, etc. To be successful there is a strong requirement for an organizational leader/manager to provide a new form of information service to the entire enterprise. As a result, there is currently a debate regarding the role of, or need for, a Chief Data Officer (a CDO) or Chief Analytics Officer (CAO) – perhaps as another member of the C-suite. Or, perhaps such a role is better placed under the CIO, or elsewhere in the organization? There is no one best place in which the responsibilities for the data questions raised above should reside for every organization, however, management needs guidance regarding what to take into account in determining the best alternative for their individual situation (e.g., strategy, culture, politics, IT-business relationship).

When considering the governance of data and business analytics , organizations need to define where the responsibility and expertise resides for:

• ultimate strategic authority on informational assets
• tactical and operational management of these assets
• investment and sourcing decisions for deploying data initiatives
• achieving organizational data success/value from these initiatives
• ensuring data security/privacy compliance
• creating innovative data-driven products and services

The key is for executives to consider data as an asset – to determine how best to manage it, to exploit its potential, as we would with any other asset. How should it be acquired, stored, maintained and put to work. Recognizing the importance of IT and non-IT organizations working collaboratively is essential. 

Identifying the options that managers (in particular CEOs and CIOs) have available to address these important questions is fundamental? Business Schools around the world are manufacturing Masters Degrees in analytics as fast as possible. Senior managers will attend seminars and read reports such as those mentioned above to keep up with these important trends. Students undertaking MBAs will no doubt find a minor in this area. However, for the vast majority of IT and non-IT managers, something else is needed. In essence flexible programs addressing the technical, business, management, industry, and organizational considerations are key.

To this end the Global Institute for IT Management (GIIM) has developed two 4-course certificate programs to address these important considerations. One ( Deploying Analytics ) is similar to m any university IT analytics programs that are being offered; albeit with a stronger focus on industry and practical considerations. This (the second) Managing Data as an Asset Certificate focuses on the leadership, management, and industry skills necessary to leverage this important new technology; how to derive value from data.

No doubt the Global Institute for IT Management will be just one of many bodies offering education in data and business analytics. However GIIM brings to the table a selection of exemplary IS academics (from multiple leading universities, where Masters Degrees are also available) and practitioners from around the world with a wealth of experience in executive education, information technology, design and business analytics, as well as a strong industry focus geared for IT and non-IT executives. In addition, GIIM provides a certificate addressing the technical data/analytics responsibilities and a second (the one described here) addressing the management data/analytics responsibilities. 

Recognizing that some candidates will have a technical background while others a more business background, candidates should also consider courses from the Deploying Business Analytics Certificate, IT in Industry Certificates, IT Security Management Certificate, and IT in Marketing Certificate. Candidates should have completed the course Data Management & Warehouse Considerations (The second course in the Deploying Big Data/Business Intelligence/Knowledge Management Certificate) and The Essentials of Data Management course or have the equivalent experience prior to taking this certificate.   

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. Leveraging IT Resources: Information & Resource Management *

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 courses focus 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:

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

Select At Least One (1) From The Following:

I. Managing AI Initiatives *

While having a relatively long history, Artificial Intelligence (AI) is still actively evolving to where it is now emerging as an essential technology across every industry. The purpose of this course is to prepare IT and non-IT managers for creating effective AI strategies and plans that leverage AI and Cognitive Computing for competitive advantage.

Artificial intelligence (AI) is an academic term that has been seized upon by the media, marketing departments and commentators as shorthand, and to add narrative spice. The now-dominant AI term includes physical and software robots and tools including ‘robotic process automation’, ‘cognitive automation’ and ‘artificial intelligence’. The focus of this course will be on learning the essentials of modern AI, leading industry current and future business application initiatives, and deriving AI deployment strategies, business cases, and plans, as well as considerations for organizational structure, sourcing, and governance processes.   

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

Focusing on key AI and Cognitive Computing technologies, such as machine learning, natural language processing and deep learning, this course will help candidates understand the implications of these new technologies for business strategies, as well as the economic and society issues they address. The course will also examine how artificial intelligence and cognitive computing will complement and strengthen the workforce rather than just eliminate jobs. Additionally, the course will emphasize how the collective intelligence of people and computers can solve business problems that not long ago were considered impossible.

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

II. Managing Blockchain Initiatives *

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  

The purpose of this course is to prepare IT and non-IT managers for creating effective RPA (Robotics Process Automation) strategies and plans that leverage RPA for competitive advantage. The focus of this course will be on learning the essentials of RPA, preparing Management Professionals to lead industry current and future business application initiatives, and deriving RPA deployment strategies, business cases, and plans, as well as considerations for organizational structure, sourcing, and governance processes.

The course provides the foundation for managers/executives and management consultants aspiring to leverage these important emerging technologies or have a career in the Automation Industry. This course will provide the knowledge along with the practical skills necessary to implement Robotic Process Automation through specified guidelines and methodologies that will bring value and efficiencies to a business organization. 

Understanding how to leverage RPA to estimate and manage progress against plans for internal and external projects is an essential requirement, as are building the critical skills to formulate effective responses to risk events. Participants will develop a sharpened expertise in considerations for organizing, staffing (e.g., skills, sourcing, HR), governing, and preparing a strategy to introduce and scale RPA initiatives that integrate across the organization and emerging data technologies (e.g., AI, analytics, Cognitive Computing, Blockchain, IoT).

Appreciating how enterprises automate services using a variety of automation technologies is at the core of this courses. The array of available automation products described include scripting tools, software robots, robotic process automation, artificial intelligence, desktop automation, cognitive computing, business process management automation, and machine learning, to name a few. Understanding how these tools worked, the type of data used as input, how they processed data, and the type of results produced are fundamental.

Recognizing the difference between Robotic Process Automation (RPA) and Cognitive Automation (CA; which people commonly call artificial intelligence/AI) and the impact they can have is essential. The realm of RPA consists of tools that automate tasks that have clearly defined rules to process structured data to produce deterministic outcomes. A ‘software robot’ is configured to process tasks the way humans do, by giving it a logon ID, password, and playbook for executing processes. RPA tools are ideally suited for automating those mindless ‘swivel chair’ chores performed by humans, like taking structured data from spreadsheets and applying some rules to update an ERP system. RPA tools ‘take the robot out of the human’, meaning that the tedious parts of a person’s job could be automated, leaving the human to do more interesting work that requires judgement and social skills.

The realm of cognitive automation (CA) consists of more powerful software suites that automate or augment tasks that do not have clearly defined rules. We do not like to call such software ‘Artificial Intelligence’ because we believe the AI label aggrandizes what these tools do. With CA technologies, inference-based algorithms process data to produce probabilistic outcomes. A variety of tools are in the realm of CA, such as tools that analyze data based on supervised machine learning, unsupervised machine learning, and deep learning algorithms, backed by powerful computing and memory. The input data is often unstructured, such as natural language, either written or spoken.

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

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

Also consider courses from Business Process Management

 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 *

This course focuses on the current and emerging data and business analytics tools, approaches, and related technologies (e.g., cloud, legacy services, data security/privacy, social media/networks, internet of things, mobile applications, cognitive computing, crowd-sourcing, standards), and how they can be integrated and leveraged. This is the most technical of the certificate courses, but it is still focused on data and business analytics management considerations.

It is designed to help candidates understand the difference between traditional systems of record built on ACID databases and emerging NoSQL databases, web-scale cloud data layers, master data management, data curation/taming at scale, data modeling, real time data warehousing, data warehouse modernization, fraud & anomaly detection, internet of things implications, crowd-sourcing data (LinkedIn, Yelp, etc.), and when & how to incorporate 3rd party data (e.g., Google maps, public open data, acquired data). Candidates will also learn how to help their organization assess, select, and adopt trends in emerging data business analytics products, tools, and techniques. Other considerations include how to cleanse, curate, and shape data coming from more sources than ever before and how to build data architectures / infrastructures and services that integrate and leverage these new data sources. By concentrating on current and emerging data and analytics technologies, in essence this course puts the candidate in the role of the CAO/CDO (Chief Analytics Officer/Chief Data Officer) as they ensure their organization is prepared to effectively and efficiently enable/drive these data driven initiatives.

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 having experience with the business and management considerations for implementing data management, statistics, modeling and BI tools is recognized as being fundamental, understanding how industries are being tranformed is also considered essential in being able to have 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, Petroleum, Retail, Insurance, Transportation, etc.