BI is at a crossroads; its place as an integral part of Data Management is secure, with everyone from the public to the private sector incorporating data into their operational processes. Yet, as the reliance on data increases, the nature of the role that BI will play in future data integration is split into two diametrically opposed possibilities that can substantially alter the form of Data Management.
The traditional use of this technology requires formal BI education, a process involving professional certificates and college degrees that aids the growing number of professionals looking to pursue careers as BI analysts. There is also a movement towards the simplification of BI, one of the most distinctly emerging trends related to the data industry, as evinced by the increasing number of business professionals using data to influence their decisions. There is a plethora of evidence to indicate that both of these trends are growing, although conventional wisdom posits that the more popular one will eventually cancel out the other.
Formal BI Education
BI is in the process of evolving from a tool reserved for techies to an important resource for business professionals. Other than Data Governance, it is arguably the single most important aspect of the movement towards incorporating data in daily operations, as its many applications (mining, decision support systems, predictive analytics, etc.) are what give data its value. There are a number of organizations that still employ BI analysts to sift through different sources to obtain relevant data for specific needs. This distributed approach to BI analysis is largely behind the movement for formal education regarding this technology.
Other than procuring training for an IT department with consultants or BI vendors, the most expedient form of education for BI analysts involves professional certification. Several organizations offer this option, which includes comprehensive as well as specialized credentials typically requiring coursework and the successful completion of examinations (the list below is only a few of the many available):
- Southern Methodist University Cox
- Saint Joseph’s University
- The Data Warehouse Institute
- Boston University
- Villanova University
But, as the incorporation of data becomes more influential in organizational decisions at the tactical and operational level, greater numbers of students are choosing to earn college degrees in BI. Colleges and universities are increasing options for both graduate and undergraduate majors (and minors) in this subject to keep up with current IT demands. Degree programs allow students to learn general IT concepts that revolve around the usage of data and the applications of a host of BI tools that make such information stratified and timely. These programs are appearing at both technical schools and conventional four-year institutions:
Master’s Degree
- Saint Joseph’s University
- Boston University
- Northwestern University
- Capella University
- University of Denver
Bachelor’s Degree
Implications for Big Data
There’s no denying the impact of Big Data on the future of BI. The sheer size and variation of Big Data requires a refined set of analytic tools, especially for real-time analysis – one of the most useful BI features. These tools will need to account for both unstructured and structured data, and expand beyond relational technologies for useful integration. Such cutting edge advancements can almost certainly be handled better by formally educated BI analysts instead of laymen.
The trouble with using conventional BI tools to analyze Big Sata is the speed – or lack thereof. However, a number of BI vendors have recently developed applications specifically designed for Big Data and Hadoop, the most commonly used open source filing system. Cloudera has created an open source query engine that operates in real time and is significantly faster than traditional Hive querying; it has garnered support from a number of BI product developers. Other vendors are projected to release Data Visualization tools and applications that can cache querying results, allowing users to sift through them at their leisure. These products will make Big Data and Hadoop a lot more viable for BI analysis, although much of this technology is still being developed and best managed by analysts specifically trained in this field.
Simplification
The increasing popularity of formal education programs in BI reinforces the notion that BI analysis is widely conceived of (and may continue as) a specialized field reserved for techies. Yet, as the data movement gains ground throughout the business side of the industry, it seems possible that at some point in the near future BI analysis will simply be another routine aspect of the job for business professionals looking to maximize the use of what will be viewed as a standard resource.
There are several developments in the world of BI that are helping to demystify its capabilities and render it more functional for the average executive. The trend to simplify its tools and market solutions towards such professionals is already underway. Conventional BI accessibility – through the IT department – is not always expedient enough to keep up with the demands for data, largely because of the need for IT “middlemen” to sort through data first before significance is attached to it. Developments in BI for Big Data that improve the speed and value of such data will also influence the simplification of tools that will be able to perform many of the same functions for little data, including deep analysis of varying sources in real time. By providing information from a variety of sources that relate to a specific transaction or customer input via streaming, BI will become considerably more viable for executives looking to utilize this software on their own.
The Mobile Movement and Analytics
There are two interrelated factors that are paving the way for the simplification of BI for business users. One is the increasing usage of mobile devices, which provide access to proprietary data remotely and within the workplace. Several vendors have developed dashboards and Data Visualization techniques specifically for these devices, which will likely continue due to the lowered cost of enterprises encouraging employees to work with their own handsets – or simply issuing them instead of traditional computers. By providing tools that work with these autonomous devices, BI vendors are subtly encouraging executives to utilize these capabilities without third-party intervention.
The second factor encouraging a future in which BI is simplified and incorporated into the daily functions of those working in business is the ubiquity of analytics. Although BI offers a variety of tools to extract meaning from reams of data, its predictive analytics capability is one of its more frequently used. Analytics are everywhere, especially in mobile devices, and are playing a growing role in the management of operations, strategies, and fundamental aspects of people’s lives. The ubiquity of analytics encourages an environment in which tools such as BI are used as frequently as possible by business representatives; the fact that so many of them are available on mobile applications reinforces this trend.
In Hindsight: Looking Back to the Future
The need for formal education for BI analysts will likely continue in the coming years, although it will eventually become less necessary due to the emerging simplification of BI tools that will encourage executives to use this software more autonomously and effectively. In much the same way that technology tends to transition from being used by the elite to the general population, BI is in the process of evolving into a vital series of tools that greatly inform real-time decisions for executives, and will eventually become marketed as such.
The key to the timeframe in which this realization of BI’s full potential will occur pertains to its simplification process that not only includes visualization techniques and dashboards for mobile devices, multiple source analysis streamed in real time and the prevalence of analytics, but also its increasing use for identifying diverse entities and tracing data lineage. These final two applications are projected to expand in the coming years as more sources of data and regulations regarding discoverability become prominent issues in data management. The presence of inexpensive, reliable data discovery tools for the desktop and handset will fuel BI’s progression from a dedicated search for a particular piece of information to a readily accessible component of the daily elucidation of pertinent facts related to operational processes.
