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 
  

Business Intelligence versus Data Science

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
  

Data Positions and Careers

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.