Business Intelligence (BI) is a technology-based process for analyzing data and presenting useful information that enables business executives, managers, and other end-users to make informed business decisions.
BI includes a variety of tools, applications, and methods that companies can use to collect data from internal systems and external sources, prepare it for analysis, develop and implement requirements for this data, and create reports, dashboards, and data visualizations. to make analysis results available to decision-makers and operational staff.
The term business analysis often refers to a set of tools that provide quick, easy-to-learn access to ideas about the current state of the business based on available data.
The meaning of business intelligence
In general, the job of business intelligence is to improve all parts of the business by increasing access to company data and then using that data to increase profitability. Companies using BI practices can translate the collected data with ideas about their business processes. The insights can then be used to create strategic business solutions that increase productivity, increase revenue, and accelerate growth.
- Speed up and improve decision making;
- Optimization of internal business processes;
- Improve operational efficiency;
- attract new income;
- Achieve a competitive advantage over competitors;
- Assist companies in identifying market trends; and
- Identify business problems that need to be resolved.
BI data can include historical information stored in the data warehouse, as well as new data captured as the resulting source system so that BI tools can support strategic and tactical decision-making processes.
Initially, BI tools were mainly used by data analysts and other IT professionals who performed analysis and generated reports on query results for business users. However, executives and employees are increasingly using the business intelligence platform itself, partly because of the development of self-service BI and data discovery tools and dashboards. The BI market is expected to grow steadily as these tools increasingly include artificial intelligence (AI) and machine learning (ML).
Examples of business intelligence
Reporting is central to business intelligence, and dashboards may be archetypal BI tools. The dashboard is a hosted software application that automatically captures the available data in charts and graphs which provide a real-time overview of the state of the business.
While business intelligence doesn’t tell business users what to do or what would happen if they took a particular course, BI isn’t just for reporting. In contrast, BI provides a way for users to research data to understand trends and gain insights by simplifying the effort it takes to find, aggregate, and query the data needed to make informed business decisions.
For example, a company that wants to better manage its supply chain needs BI’s ability to determine where delays occur and where the variables are in the delivery process, said Chris Hagans, vice president of operations at WCI Consulting, a consulting firm. Companies focus on BI. The company can also use its BI capabilities to find out which products experience the most delays or which modes of transportation experience the most delays.
The potential use of BI goes beyond typical business performance metrics of increased sales and reduced costs, said Cindy Hawson, vice president of research for Gartner, an IT research and consulting firm. He cites the Columbus, Ohio school system and its success in using BI tools to examine a wide variety of data points – from attendance rates to student performance – to improve student learning and graduation.
Business intelligence versus business analytics
You will find the following examples providing an overview of the current state of the company or organization: Where are the sales prospects at work? How many members were missing or gained this month? This leads to an important distinction between business intelligence and another related term, business analysis.
Business intelligence is descriptive and shows you what is happening now and what has happened in the past that brought us to this state. Business analytics, on the other hand, is an umbrella term for data analysis techniques that are predictive – that is, they can tell you what the future holds – and are prescriptive – that is, they can tell you what to do to create results. better. (Business analytics is generally considered part of a larger category of data analytics that is specifically targeted at businesses.)
The difference between the descriptive power of BI and the predictive or descriptive power of business analysis goes a little beyond the time we’re talking about. It’s also about who is business intelligence for? As explained in the Stitchdata blog, BI wants to give managers a clear picture of the current state of affairs.
While predictions and advice from business analysis require IT professional analysis and interpretation, one of BI’s goals is to make relatively non-technical end-users easy to understand and can even immerse themselves in data and create new reports.
Business intelligence strategy
In the past, IT professionals were the main users of BI applications. However, BI tools have become more intuitive and easy to use, allowing a large number of users from different areas of the company to use the tool.
Hawson of Gartner distinguishes two types of BI. The first is traditional or classical BI, where IT professionals use internal transactional data to generate reports. The second is modern BI, where business users interact with an agile and intuitive system to speed up data analysis.
Hawson explains that companies usually choose classic BI for certain types of reports, such as Government or financial reports where accuracy is paramount and questions and records are used which are standard and predictable. Organizations typically use modern BI tools when business users need to cope with rapidly changing dynamics, such as B. Marketing events where speed is measured over 100 percent correct data.
While solid business intelligence is essential for making strategic business decisions, many companies struggle to implement effective BI strategies because of poor data practices, tactical errors, and more.
Self-service business analysis
The desire to provide nearly everyone with the ability to extract useful information from business intelligence tools has led to a standalone business BI service designed to limit the need for IT intervention when generating reports. Businesses can use BI self-service tools to make internal data reports more accessible to managers and other non-technical employees.
Keys to the success of self-service BI include a business intelligence dashboard and user interface with intuitive drop-down menus and extension points that allow users to find and transform data in easy-to-understand ways. Undoubtedly, some training is required, but when the benefits of the tools are clear enough, staff are ready to join in. (If you’re buying a BI self-service solution, Martin Heller of CIO.com guides you through the decision-making process and compares the top five options.)
However, note that there are also problems with BI self-service. By directing your business users to become ad hoc data engineers, you can end up with a chaotic mix of departments that vary between departments, face data security issues, and even run large licenses or SaaS accounts without centralized control. for the tool release. Even if you advocate independent business intelligence at your company, you can’t just buy products that are sold off-market, take your people to the user interface, and hope for the best.
Business intelligence software and systems
There are many different types of tools under the business intelligence umbrella. The SelectHub software service breaks down several main categories and features:
ETL (Retrieval-Transfer-Load – a tool that imports data from one data warehouse to another)
OLAP (online analytical processing)
Of the tools, the most popular are dashboards and visualizations, according to SelectHub. They provide a quick and easy to digest summary of the data underlying BI’s value proposition.
There are many vendors and offerings in the BI space, and they can be very good executions. Some of the main cast are:
- Tableau, a self-service analytics platform, provides data visualization and can be integrated with several data sources including Microsoft Azure SQL and Excel Data Warehouses
- Splunk, a “focused analytics platform” that enables business review and data analysis
- Alteryx combines analysis from multiple sources to simplify workflows and provide a wealth of BI information
- Qlik is based on data visualization, BI and analysis and offers a comprehensive and scalable BI platform
- Domo, a cloud platform that offers business intelligence tools tailored for a variety of industries (such as financial services, healthcare, manufacturing, and education) and roles (including CEOs, sales, BI professionals, and IT staff).
- Dundas BI, which is mainly used to create dashboards and indicators, but can also create standard and custom reports
- Google Data Studio, an additional cost version of the popular offering from Google Analytics
- Einstein Analytics, Salesforce.com’s effort to improve BI with AI
- Birst – cloud-based service where multiple BI software shares common backup data.
The future of business intelligence
Gartner sees a third wave of interference on the horizon, according to Hawson, which the research firm calls “advanced analytics.” Machine learning is built into the software and guides users to query their data.
“It will be BI and analytics and it will be smart,” he said.
The combination included in this software platform makes each function stronger and more valuable to the business people who use it, says Gorman.
For example, someone would look at last year’s sales report – this is BI – but also get a forecast for next year’s sales – this is business analysis – and then add a what-if function: what if we were going to do X instead of Y? Gorman explained that software vendors are developing applications that provide these functions in a single application, rather than providing them across multiple platforms as is the case today.
“Now the system provides recommendations with a higher value. This makes decision-makers more efficient, more powerful, and more accurate, “he added.
And while BI remains valuable in its way, Hawson says organizations cannot compete unless they go beyond BI and embrace advanced analytics.
Gartner’s Magic Quadrant report predicts that companies that provide users with access to internal and external data catalogs will double the value of their analytics investment by 2020 compared to companies that don’t.
Hawson adds, “There is a need for reporting, but reporting is not enough. If you just report, you are lagging. If your reporting is not smart and agile, you fall behind. You fall behind.”