Ideas and Technology

Big Data, Business Analytics, and Business Intelligence

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IDC stands for International Data Corporation, which is an American organization that specializes in consumer technology, information technology, and telecommunications. It was established in 1964 and iscurrently headquartered in Framingham, Massachusetts.

During the IDC Big Data and Business Analytics Conference on 18 November 2013 at the Emirates Palace Hotel, it was agreed that the UAE’s economy produces a stream of steadily monitored and analyzed data with room for continuous improvements in data mining and analytical capabilities. IDC’s estimate, based on reliable sources, is that an approximate1.8 zettabytes of data replication and creation took place in 2011 in the UAE. (A zettabyte is 10²¹ bytes, equivalent to 1.8 trillion gigabytes)

What contributes to this much flow of information and data, and what are the latest trends in business analytics in the public sector?

For the most part, social interactions, simulations, mobile devices, physical infrastructure, R&D equipment, and facilities contribute to this stream of data and are part of the latest innovations and trends in business analytics. The term used to group all this information is “Big Data.” Often, people fail to understand what “Big Data” means, and confuse it with other terms describing a type of business tool.

What is “Big Data”

The proper definition of Big Data, according to IDC, is “[a] new generation of technologies or tools, which aim to extract more value from a wide range of data via high velocity capture, analysis, and discovery, and thatis economically acceptable for businesses to use to improve themselves.”

Big Data plays a huge role in increasing business potential for businesses across every industry and for businesses of all sizes. It does not require a huge investment in an in-house system as it can be utilized via the Cloud. (For more information on Cloud Computing see our article in Issue 2, page 46.)Projections say that spending on acquiring Big Data capabilities will reach $16.9 billion in 2015.

The UAE has remained at the forefront of business analytics and is one of the biggest investors in Big Data capabilities and technologies in the Middle East. More than 40% of CIOs (Chief Information Officers) claim that they scoop investments in the field of business analytics and Big Data, whereas 58% of CIOs claim that compliance requirements, governance, reporting and regulation, and the demand for transparency contribute to forcing people to invest more into business analytics technology and Big Data. Based on this, a sizable growth of approximately 20%is predicted in business analytics tools and technologies over the next decade.

How Technology Helps Collect and Interpret Big Data

Business analytics (BA) and Business Intelligence are not interchangeable terms. Business analytics refers to the skills, technologies, and practices for continuous, iterative exploration and investigation of past business performance to gain insight into business performance and drive future planning. Business analytics focuses on developing new insights and ways of understanding business performance based on data and statistical methods. Business intelligence,in contrast, traditionally focuses on using a consistent set of metrics to both measure past performance and guide business planning, which is also based on data and statistical methods.

Through advancements in technology such as display technologies, sensors and the like, companies can collect data by monitoring the behavior of people, events, entities, and objects. They use the data collected to apply new statistical, analytical, and computational techniques to study and evaluate past trends and future possibilities. As new display technology and visualization applications are emerging, there have beendrastic improvements in how companies process and visualize the information they collect.Decisionmakers can now have instant access to accurate and timely information that enables them to make informed business decisions.Conveniently, such applications are now accessible through smart phone and tablet devices, ensuring that decisionmakers are never in the dark.

By using business analytics, an increasing number of companies are starting to realize the business advantages associated with such technological advancements. Among the numerous advantages and benefits of business analytics are the ability to enhance customer experience and increase loyalty while lowering the cost of marketing.

With advancements in analytical technology, analysts are relieved from the burden and pain involvedin performingtediousmanual data analysis in order to deliver real-time information. Since everything is computerized and electronic, the speed of transition of information is faster, facilitating better decisionmaking and quick action to ensure better business outcomes.

Types of Business Analytics

There are four types of analytics that companies can use to learn from and better engage with their customers. It’s from the second two types, Predictive and Prescriptive Analytics, that one can really get the insights needed to drive a business forward.

Descriptive Analytics:

Also known as Business Intelligence (BI), this is what you get from your web server through tools like Google Analytics, Omniture, or the like. You can quickly understand “what happened” during a given period in the past and verify whether a marketing campaign was successful based on simple parameters, such asweb page views. About 35% of companies surveyed say they do this consistently.

The purpose of descriptive analytics is to summarize past performance. It is estimated that more than 80% of business analytics, most notably social analytics, are descriptive. Business Intelligence tools are fast becoming an essential and integral management tool in most organizations.

Business intelligence can be applied to the following business purposes in order to drive business value:

• Measurement – a program that creates a hierarchy of performance and benchmarking metrics that informs business leaders about progress towards business goals.
• Analytics – a program that builds quantitative processes for a business to arrive at optimal decisions and to perform business knowledge discovery. This type of program frequently involves data mining, process mining, statistical analysis, predictive analytics, predictive modeling, business process modeling, data lineage, complex event processing, and prescriptive analytics.
• Reporting/enterprise reporting – a program that builds infrastructure for strategic reporting to serve the high-level strategic management of a business, as opposed to operational reporting. It frequently involves data visualization, executive information system, and On-Line Analytical Processing (OLAP).
• Collaboration platform – a program that allowsstakeholders inside and outside of the business to work together through data sharing and electronic data interchange.
• Knowledge management – a program to make the company data driven through strategies and practices to identify, create, represent, distribute, and enable adoption of insights and experiences that represent valid business knowledge. Knowledge management leads to learning management and regulatory compliance.

In addition to the above, business intelligence can provide a pro-active approach, such as an alert function that immediately notifies the enduser if certain conditions are met. For example, if some business metric exceeds a pre-defined threshold, the metric will be highlighted in standard reports and the business analyst may be alerted via email or another monitoring service. This end-to-end process requires data governance, which should be designed by persons inside the organization who are well-versed in the procedures and policies of the organization.

Diagnostic Analytics:

If you want to go deeper into the data you have collected from users in order to understand the “causative chain of events” leading up to a business situation, you can use business intelligence tools to gain insights.However, it is very laborious work that has limited ability to give you actionable insights, basically providing a very good understanding of only a limited piece of the problem you want to solve. Less than 10% of companies surveyed do this on occasion and less than 5% do so consistently.

Predictive Analytics:

If you can collect contextual data and correlate it with other behavior datasets, as well as expand data beyond what you can get from your web servers, you enter a whole new area where you can get real insights. Essentially, you can predict what might happen if all inputs remain constant, then manipulate various criteria and business factors to simulate potential scenarios and the outcomes associated with them. Less than 1% of companies surveyed utilize this tool, but with it they have found incredible results that have already made a significant difference in their businesses.

Prescriptive Analytics:

Once you get to the point where you can consistently analyze your data to predict future performance, you are very close to being able to understand what you should do in order to maximize good outcomes and prevent potentially bad outcomes. This is on the bleeding edge of innovation today, but it’s attainable!

Implementation

There are numerous factors that dictate the successful adoption of good business analytics practices in an organization. Among some of the key drivers of success are the level of commitment and sponsorship of such a project from senior management, the level of business need for creating a data driven business analytics/intelligence program within the organization, and the amount and quality of business data available.

Creating a data-driven organization is difficult. However, with appropriate strategic direction, executive commitment, and a well-considered execution plan, companies can leverage the promise of Big Data to become more efficient, intelligent, and profitable.

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