Business intelligence (BI) leverages software and services to transform data into actionable insights that inform an organisation’s strategic and tactical business decisions.
BI tools access and analyse data sets and present analytical findings in reports, summaries, dashboards, graphs, charts and maps to provide users with detailed intelligence about the state of the business.
The primary goal of BI is to help companies bring order to the massive amounts of data they collect by supporting four basic objectives:
If nothing else, BI tools quickly and efficiently collect pre-determined sets of data from enterprise systems such as Customer Relationship Management (CRMs), financial management platforms and Human Resource Management System (HRMs). In addition, Robotic Process Automation (RPA) and AI-powered bots can scrape website, spreadsheets and other documents for additional data, both structured and unstructured.
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Data storage. Data lakes and data warehouses serve as a central source for both structured and unstructured data. These tools safely and securely store large amounts of data for later use in processing and analysis. They also cleanse, integrate and organise data so that it’s high quality and easily accessed by data reporting and analysis systems and ultimately used by subject matter experts within the business.
The core of business intelligence is focused on descriptive and diagnostic analytics, which answers questions of where your company has been, where it is now, and why things are the way they are now. BI tools need to be able to draw from data storage to conduct these different types of analyses.
Data reporting. In order to be useful, data-driven insights must be easily and reliably accessed by decision-makers and other stakeholders. Instead of waiting for the IT department to create a report based on business data, self-service reporting tools allow business users to create visually engaging reports themselves.
BI and digital transformation are deeply intertwined. In fact, once could say BI is both the enabler and result of digital transformation.
The ability to analyse vast amounts of structured and unstructured data to gain insights, often in real time, is what underpins most digital transformation efforts, as the insight derived through big data analytics is used to drive digitisation and automation of workflows.
Digital transformation enabled by BI solutions presents an enormous opportunity to drive growth and profitability. Fostering a data-driven organisation emboldens the vision of faster, better-informed decisions to compete in the digital economy. Business analysis has redefined the terms ‘data’ and ‘information’. Value is derived from the ability to handle huge amounts of data. It enables business development, improved productivity and profitability based on the perfectly and visually attractive dashboards and reports.
Today’s competitive advantage is obtained through the possession of the latest information in the most desired format – anywhere and anytime. Enterprises can embrace the digital era by being able to extract insightful information that can offer them a futuristic view of their business.
This is done through the application of BI. As well as its technologies such as predictive analysis, self-service, cloud and mobile BI to name a few. To a large extent, BI is sure to smooth the digital transformation journey since it acts as a catalyst in digitising organisational activities along with detailed analysis while generating dashboards and reports to make it easier for data leaders to monitor their organisations’ digital journeys. As a whole, BI is the booster to drive the digital path, with full force and focus.
For decades, BI could only tell users ‘what is happening’ or ‘what happened', leaving the decision-making part to humans. However, with the emergence of artificial intelligence (AI), that is rapidly changing. Now, using data mining, machine learning, prescriptive analytics and other innovative technologies, organisations can use BI to uncover and share new, groundbreaking data-driven insights.
By modelling human behaviours and thought processes, AI programmes can learn and make rational decisions. AI can enable BI tools to produce clear, useful insights from the data they analyse and help companies more easily synthesise vast quantities of data into a coherent action plan.
Predictive analytics is the use of data, statistical algorithms and machine learning (or AI) techniques to identify the likelihood of future outcomes based on historical data. The use of predictive analytics is a key milestone on your analytics journey — a point of confluence where classical statistical analysis meets the new world of AI.
Using data mining techniques, predictive analytics platforms sort through massive amounts of not structured and unstructured data to identify patterns and make predictions based on past behaviour.
Organisations of all kinds are leveraging predictive analytics to drive value in a myriad of ways. For example, IT departments might leverage predictive analytics to predict storage usage. Predict analytics can also dramatically improve supply chain resilience by enhancing demand forecasting, inventory planning and last-mile delivery. Even hospitals are using predictive analytics to predict patient outcomes and help doctors make more informed treatment decisions as well as optimise resource planning.
Prescriptive analytics takes things one step further. In addition to leveraging predictive analytics to forecast what will likely happen, it also recommends a course of action.
By combining predictive analytics with another layer of AI, prescriptive tools can simulate various outcomes from worst case to best case and show the probability of each. The faster the need for digitisation evolves, the more pressing the need for effective business intelligence solutions.
The future of decision-making is built on digital platforms that make the most of BI because it reveres commitment over indecision, action over inaction, and passion over indifference.
- The writer is the chairman of BTN, an ICT provider in East Africa. ([email protected])