Comparing Business Intelligence and Business Analytics
Business intelligence and business analytics are potent tools organizations use to make intelligent choices with their data. Both tools focus on data-driven methods, but you use them differently. Business intelligence focuses on the present and the past. It uses various techniques and tools to collect, analyze, and store data to give you insights you can put into action. The insights usually come to you in the form of reports and dashboards.
On the other end of the spectrum, business analytics looks further into the future. It uses data models, statistical analysis, and predictive forecasting to guess what trends will be popular in the future or what will happen next. So, business intelligence tells you “what happened and what is happening,” while business analytics tells you “why it happened and what might happen next.”
Related: Customer Data Integration
What Is Business Intelligence?
Business intelligence allows you to use technology to look at data and give your corporate end users, like managers or executives, helpful information they can take and analyze to make intelligent business decisions. It includes various tools, apps, and methods that allow companies to gather data from inside and outside their systems, get it ready to analyze, and build and run queries against it. Also, you can use it to make reports, dashboards, and data displays.
The outputs you get can help you understand which insights you can take away from the data. This lets them use past and present data and performance numbers to make clever and valuable business decisions.
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What Is Business Analytics?
Business analytics is a set of tools, skills, and methods businesses can use to analyze and explore past performance levels to learn more about what happened. It’s possible to use this data to guide current business planning, and it’s more about looking ahead than backward, while business intelligence is more about focusing on past data. This method uses data modeling, statistical analysis, predictive forecasting, and optimization to help businesses plan for future trends.
Business analytics digs much deeper into data to spot correlations, patterns, and trends, and it does so by harnessing computational and statistical techniques. This helps organizations predict possible problems and opportunities and make proactive, data-informed choices about their future.
Related: Data Driven Insights to Make Informed Decisions
Business Intelligence vs. Business Analytics: Key Differences
Both business intelligence and business analytics are essential tools when making decisions based on data in the business world. Even though many entities use the terms interchangeably, they have different traits and goals. Business intelligence uses dashboards and reports to help show the company’s past and present state. Business analytics goes deeper, explaining the “why” behind data trends and making predictions on what will happen moving forward.
Think of it like this: the difference between watching a movie with scenes you know will happen and looking at a picture. Companies wanting to make solid business decisions and boost their data strategies must understand these minor differences.
Business Intelligence Is Geared Toward Large Enterprises
There is an excellent reason why business intelligence and large companies have a long history. Every day, huge companies create vast amounts of data across dozens of departments. They need a set of tools to collect, process, and make this data make sense. Business intelligence has a vital infrastructure that can give these bigger companies a complete picture of their day-to-day operations. This makes it much easier to spot inefficiencies, help make decisions, and monitor KPIs.
Also, business intelligence systems demand a lot of technical skill and money to set up and maintain; they were initially much more accessible for larger companies with dedicated IT departments and deeper pockets to buy. These companies had the money available to buy the infrastructure, software licenses, and specialized staff to set it up and get it running smoothly.
However, cloud computing and scalable solutions are making this landscape shift. Smaller businesses can use business intelligence tools without destroying their bottom line. Even so, the design and features still show that it was popular in large companies in the past.
Business Analytics Focuses On the Future
Business analytics stands out regarding data-driven decisions because it primarily looks toward the future. Many data tools are designed to allow you to look at past operations, but business analytics wants to help you guess what’s coming in the future. It uses a range of advanced machine learning programs, statistical models, and predictive algorithms to try and guess which business problems, trends, and opportunities will appear in the future.
The ability to predict the future is huge in business, mainly because the market changes quickly and is more competitive. Companies can make better plans, anticipate market changes, allocate their resources, and design new services or products they think their customers will want. For example, a store could use business analytics to guess what items will be the most in-demand this season, or a bank could use it to determine which loans will default.
Business analytics is like a compass for businesses; it shows them the way to future growth and helps them avoid problems.
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Business Intelligence vs. Business Analytics: Examples
Business Intelligence (BI) and Business Analytics (BA) are both essential when it comes to data-driven strategies, but they look different and do different things, including:
What Business Intelligence Looks Like
A multinational company uses business intelligence tools to make a dashboard that shows its quarterly sales data from different regions in a visual way. This dashboard shows which areas are doing the best, trends over time, and compares sales from the current quarter to the last. It’s easy for managers to see which regions met their goals and which fell short. By looking at real-time inventory levels, they can also ensure that the amount of stock available matches the sales pattern.
What Business Analytics Looks Like
A non-profit organization focused on minimizing food insecurity uses business analytics techniques to plan for the upcoming fiscal year. The process involves employing predictive models that analyze historical resource allocation, community feedback, and economic trends. These predictive models enable the organization to predict and prioritize evolving community needs, ensuring more impactful resource allocation for the upcoming fiscal year. By making data-driven decisions, the non-profit optimizes its efforts, resulting in a more effective approach to tackling food insecurity and better serving the community.
Which Data Management Strategy Is Best for Your Business?
Any business that wants to get the most out of its data must ensure it has the right data management strategy. The best way to do something depends on the type of data being handled, the size of the business, its goals, and the infrastructure already in place. It’s essential to look at current needs, future growth prospects, and available resources to find the best fit. The Data Love Co. can help you decide which system fits your needs the best using proven tools and processes so you can harness the power of your data.
