Your daily business activities generate tons of useful data that can be used to make smarter and better decisions. Business intelligence and business analytics are two distinct but related tools that can help you make sense of that data and drive success.
Here’s the difference between business intelligence and analytics, and how each can benefit your business.
What is business intelligence?
Business intelligence refers to the strategies and technology that collect, store, and analyze company data. It uses data from daily operations to help businesses optimize their practices, save money, and adapt to changes in the market or supply chain. Business intelligence allows businesses to view both present and past data that can help locate any weak points in the workflow, areas where finances could be cut, patterns in customer behavior, and market trends.
Some widely used business intelligence tools and software include:
- Reporting and querying software. These types of software are used to retrieve data with defined terms, and then organize and report it. Reporting software works to display collected data in the form of graphs, charts, or spreadsheets so businesses can review and assess progress and performance.
- Data mining tools. Data mining software is used to identify patterns or trends within a larger set of data using AI, statistics, or a database system. There are two general types of data mining: descriptive and predictive. Descriptive data—the more common approach in business intelligence processes—focuses on summarizing existing data and revealing correlations or trends. Predictive data mining, typically part of business analytics, helps users identify potential future patterns or trends, as well as issues that might arise.
- Online analytical processing (OLAP). OLAP selects and extracts data that allows users to analyze it from different perspectives, such as time, region, or product category. The OLAP system collects and categorizes data from various sources. Then, the software is able to locate correlations or places where data intersect. Similar to data mining tools, OLAP can reveal trends as well as forecast sales or help with budget planning.
As you might expect, the infrastructure of a business intelligence system requires robust data storage and management, integration, and visualization. Data management systems may include databases or data warehouses, which collect and organize from various internal and external sources. Data visualization—including tools like dashboards, charts, and reports—makes these data insights more accessible.
[Read more: How to Leverage Customer Data (And Where to Find It)]
Pros of business intelligence
- Increases productivity and efficiency. Business intelligence tools allow for faster data retrieval, storage, and organization, which minimizes the time and resources it would normally take to manually sort through. Essentially, it optimizes business processes, enabling the streamlining of operations.
- Enhances visibility through interactive platforms. Businesses will be able to view company data in an organized report, graph, or chart. Business intelligence tools can keep track of, and report on, certain KPIs, as well as reveal trends within the business, customer demographics, or current market.
- Accessible and scalable. Some business intelligence platforms can operate on mobile or smart devices, allowing users to access and manage data in real time from wherever they are. These tools also allow users to refine their data searches and shift between overviews and detailed reports, as well as predict future outcomes.
Cons of business intelligence
- Pricing may not be transparent and can vary. Each vendor will have different pricing for the software they provide, and some of them may have hidden fees or costs for data usage or premium features. It can also be costly if you are investing in several tools or systems at once.
- Business intelligence (BI) systems can be complex and time-consuming. Certain tools or systems can take up to a year or more to implement into your business. There are also quite a few applications involved in business intelligence, which can become overwhelming.
- Security may be unstable. There are always risks of data breaches or loss in a business. Another problem you may experience is exposing business data to personal devices. If you use mobile BI, employees may use personal phones or devices to access company data, which poses a slight risk.
Your data strategy is only as good as the data you provide.
What is business analytics?
Business analytics is the process of analyzing business data to make informed, efficient decisions. It uses historical data to help decision makers understand past and current performance, identify contributing factors, and determine the best path forward.
The four main types of analytics are:
- Descriptive analytics, which identifies trends and patterns in historical data—such as KPIs and their outcomes—to understand past performance.
- Diagnostic analytics, which examines data in more depth to uncover reasons behind given business outcomes. In other words, if descriptive analytics showcases the “what,” diagnostic analytics can provide the “why.”
- Predictive analytics, which uses historical data, statistical models, and machine learning to forecast future outcomes.
- Prescriptive analytics, which builds on predictive analytics by recommending specific actions based on past data and anticipated outcomes.
Businesses often use a combination of these methods to gain a comprehensive picture of their operations and make decisions accordingly.
Pros of business analytics
- Improves decision-making. The process of analyzing data enables businesses to identify potential situations they may encounter in the future, which helps them make better-informed decisions and set reasonable goals.
- Increases efficiency. With the help of automated processes and software, the process of data mining and analytics is much faster. Users are able to view visual reports, monitor progress, and streamline operations.
- Reduce costs and increase revenue. Business analytics help identify unnecessary expenses, as well as areas that may require more financial support. Businesses can also view areas to improve so they can gain customers, refine products, or make other changes.
[Read more: 6 Digital Analytics Tips From Industry Experts]
Cons of business analytics
- Low-quality data or analysis. Human error can affect the way we interpret or analyze data. In addition, there may not be enough data to collect, or the data may be complex.
- Security issues. There are potential security risks in using business analytics due to the sharing of data collections or analyses. Anyone in the business can access customer information, such as transactions or purchases.
- Improvement takes time. Business analytics work to help businesses grow and improve, but like anything that grows, it takes time to see long-term results.
When to use business intelligence versus business analytics
Business intelligence and business analytics both provide valuable, data-based insights into your business. To determine which of these to use for a given task, consider the following:
- Whether the intended goal is present- or future-focused. Though both use historical data to solve organizational challenges, business intelligence is more geared toward assessing current operations, while business analytics typically focuses on improving future performance.
- The type of data you’re working with. Business intelligence tools work best with structured data, such as numerical data and short text you’d typically find in business management software. While business analytics can be used to analyze structured data, many business analytics tools can also transform unstructured and semi-structured data into an organized, actionable format.
- The age and size of your company. Smaller or newer businesses may prioritize business analytics to predict and capitalize on future trends; larger or more established businesses are more likely to use business intelligence to understand historical and current performance. However, as AI continues to democratize access to advanced business intelligence and analytics, more small businesses may explore business intelligence tools.
Business intelligence and business analytics can (and often are) used in conjunction with each other. For example, you may leverage business intelligence processes to see how a recent initiative performed, then conduct business analytics to predict how future iterations of the campaign could drive further success.
Tips for implementing data strategies
Whether you choose to use business intelligence, business analytics, or both, here are a few things to keep in mind:
- Use the right platform. Business data typically stems from a vast range of sources—some of which may be unintentionally siloed across different teams. Look for advanced platforms that can automate the data integration process, eliminating human error and saving you valuable time.
- Maintain data quality. Your data strategy is only as good as the data you provide. Limit inaccuracies by developing and educating your team on data quality standards and protocols, as well as conducting regular data audits.
- Train your team. Before rolling out any major data strategy, ensure you can dedicate the time to educating your employees about the purpose of the strategy, how it will be carried out, and who is responsible for what. Invest in (or create your own) comprehensive training tailored to your team’s responsibilities and existing knowledge base, with plenty of opportunities for ongoing, hands-on learning.
[Read more: How Data Provenance Can Shield Your Business From Fraud]
Kayla Harrison contributed to this article.
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