Which of the following is an umbrella term that combines architectures tools databases analytical tools applications and methodologies?

Business intelligence (BI) is an umbrella term that combines architectures, tools, databases, analytical tools, applications, and methodologies. It was coined first by Gartner group in the 1990’s. It is a content-free expression, so it means different things to different people. BI’s major objective is to enable interactive access (sometimes in real time) to data, to enable manipulation of data, and to give business managers and analysts the ability to conduct appropriate analyses. By analysing historical and current data, situations, and performances, decision makers get valuable insights that enable them to make more informed and better decisions. The process of BI is based on the transformation of data to information, then to decisions, and finally to actions.

A BI system has four major components: a data warehouse, with all the relevant source data; business analytics, a collection of tools and algorithms for manipulating, mining, and analysing the data in the data warehouse; business performance management (BPM) for monitoring and analysing performance; and a user interface (e.g., a dashboard) that can powerfully display the insights generated by analytics.

Business cycle times are now extremely compressed; faster, more informed, and better decision making is therefore a competitive imperative. Managers need the right information at the right time and in the right place. This is the mantra for modern approaches to BI. Organizations need to work very smart. Paying careful attention to the management of BI initiatives is a necessary aspect of doing business today.

Analytics consists of utilising all the available data to answer key questions that Business needs to answer to improve its profitability and other objectives. For instance, the Chief Marketing Officer needs to know which customer segments to target for cross and upselling, the Chief of Risk needs to know if all checks and balances are put in place not to compromise financially or information wise. The Chief Information Officer would need to have fullest control on the budgets and ROI on IT spends and ensure that the applications designed run to their potential. The Chief Executive Officer on the other hand would like to know if any new products need to be designed and developed to cater to unmet needs of customers. Most of these questions can today be answered by digging deeper into enterprise and external data, and by processing the data for generating rich insights using advanced analytics.

Analytics is typically classified as descriptive analytics, predictive analytics, and prescriptive analytics. Descriptive analytics is the use of historical data combined with simple statistical techniques meant for visualising and interacting with the historical data. This often helps understand what the current state of the enterprise is. Predictive analytics, on the other hand leverages advanced mathematical and statistical modelling to come up with forecasts of any selected variable such as quarterly sales. This is used to help plan the activities better. Prescriptive analytics leverages techniques such as optimisation in order to arrive at the best course of action given the current state and predicted future states of the system.  Decision making is thus enabled almost to near real time with the embedding of data and analytics into organisational processes.

Business Case

ABC Corp is one of the world leaders in the travel industry, providing both business-to-consumer services as well as business-to-business services. It serves travellers, travel agents, corporations, and travel suppliers through its four main companies. The current volatile global economic environment poses significant competitive challenges to the airline industry. To stay ahead of the competition, ABC Corp recognized that airline executives needed enhanced tools for managing their business decisions by eliminating the traditional, manual, time-consuming process of collecting and aggregating financial and other information needed for actionable initiatives.

This enables real-time decision support at airlines throughout the world that maximize their (and, in tum, ABC’s) return on information by driving insights, actionable intelligence, and value for customers from the growing data. ABC Corp developed an Enterprise Travel Data Warehouse (ETDW) to hold its massive reservations data. ETDW is updated in near-real time with batches that run every 15 minutes, gathering data from all of ABC’s businesses. A C Corp also uses its ETDW to create Executive Dashboards that provide near-real-time executive insights using an enterprise class BI platform appropriate technology infrastructure. The Executive Dashboards offer their client airlines’ top-level managers and decision makers a timely, automated, user friendly solution, aggregating critical performance metrics in a succinct way and providing at a glance a 360-degree view of the overall health of the airline.

At one airline, ABC Corp’s Executive Dashboards provide senior management with a daily and intra-day snapshot of key performance indicators in a single application, replacing the once-a-week, 8-hour process of generating the same report from various data sources. The use of dashboards is not limited to the external customers; ABC Corp also uses them for their assessment of internal operational performance.

Need to automate for quick action

In order to serve the near real time need to generate and consume business insights, the BI and Analytics platform should be ready with a variety of prebuilt data warehouses, data marts, and data models, canned BI reports for a variety of business stakeholders, and the ability to perhaps self serve some insights. This calls for automation of the data engineering, as well as the insights and reports generation engine. A variety of self service platforms also help in jump starting the journey to BI and Analytics. Recent advances in natural language processing and speech recognition have also enabled AI enabled BI. For instance, the business user could type in their requirement in English, whilst the BI server would recognise what reports could be pre-fetched from the array of canned reports; alternatively, it might end up generating a bespoke report if the query is unique in nature.

Conclusions

BI and Analytics enable an enterprise to embed data into every day operations and decision making. It is important to build the BI system with the right architecture, the right technologies and the right user enablement in order for a significant ROI in this field. Successful organisations embed and empower business users as part of the BI platform build and use process.