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Business intelligence (BI) allows organisations to analyse and visualise all their data to spot trends and make smarter, more informed decisions.

It’s all about data. Business leaders hear that every day – but just collecting and storing data isn’t enough. Business intelligence actually puts your data to work, transforming it from zeroes and ones into meaningful insights. With BI, users can ask questions and get answers, clearly and instantly, to inform smart decision-making across your organisation. 

What is BI? Business intelligence definition

BI, or business intelligence, is a set of technologies and practises used to collect, analyse, and present business data to support decision-making. BI systems use data visualisation tools to present findings in reports, interactive dashboards, and other formats that make the information easy to understand and share – no technical skills required.

Business intelligence and analytics

Together, business intelligence and analytics provide insightful information that can improve decision-making. And while they are closely related, they are not the same.

Business intelligence is descriptive and diagnostic in nature; it’s all about figuring out what happened, when, and why to help inform decisions. Business analytics  is more concerned with what will happen, uncovering patterns to predict future trends – making it prescriptive and predictive. It can recommend actions to make desired outcomes happen, such as for forecasting demand for seasonal retail products or modelling different types of financial risk.

The tools they use also differ. In addition to data visualisation tools, BI uses technology like OLAP processing, SQL, and ETL to dive into the data. In contrast, data analytics uses more advanced technologies like predictive modelling, machine learning, and data mining to spot patterns and make forward-looking predictions. These tools typically require people with technical skillset. Think data scientists, analysts, or IT teams.

BI and data analytics are both essential technologies for painting a full picture of all your data. That’s why many organisations turn to business intelligence platforms that support both types of analysis.

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The BI process: 5 steps to greater intelligence

Before business intelligence can deliver actionable information into graphs, charts, and other clear visualisations, it first has to transform raw data into meaningful insights. This is accomplished with multiple tools for integrating and storing data, modeling, querying, and visual analysis – all working together in a structured process.

STEP 1: Collect data

Data is gathered from a variety of sources – databases, applications, enterprise systems, and more. Depending on the BI solution used, this involves using connectors for ERP, CRM, MySQL, and other platforms or APIs.

STEP 2: Integrate and store data

Using extract, transform, load (ETL) or other processes, the relevant data is then cleansed, checked for quality issues, and put into a standardised format that can be read by BI and analytics systems. Finally, it is stored in a data warehouse, data mart, or data lake for fast analysis.

STEP 3: Analyse data

BI systems analyse data using techniques such as querying, OLAP processing, and data mining. Data modelling organises information so it’s easier to work with and explore, while querying tools let you ask questions and get answers, sometimes in natural language. As a result of these analysis tools, you can group and filter data, compare statistics, and more.

STEP 4: Visualise and report data findings

Final insights are visualised into interactive dashboards, charts, graphs, and reports that distill complex information into easy-to-digest bites. Self-service BI tools allow business users to dig into their data without involving IT or having to wait for new fields to be updated.

STEP 5: Make confident decisions

Finally, organisations can explore all their data and act on valuable insights in real time to reap all the rewards that business intelligence has to offer.

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