/ How business intelligence and data analytics enhance each other
How business intelligence and data analytics enhance each other
While utilizing actionable data is at the heart of business intelligence, the field has been further enhanced by the incorporation of data analytics.
When you have the power to take large data sets and dissect them to reveal trends, correlations, and other business-critical information, you can fine-tune your BI processes to be even more effective.
However, few businesses have the in-house expertise to make full use of data analytics. That’s where BI tools come in. By packaging up data analytics functionality in an easy-to-use interface, BI tools make it possible for businesses of all sizes to harness the power of data and put it to work for them.
When used together, business intelligence and data analytics are a powerful combination.
Data analytics can provide the insights that BI tools need to be more effective, and BI tools can make data more understandable and actionable for businesses. When these two complementary disciplines work together, businesses can gain a real competitive advantage.
In this article, we will take a closer look at how business intelligence and data analytics can enhance each other and how businesses can make the most of this powerful combination.
Starting out with definitions
Business intelligence (BI) is a term that refers to the practice of using insights from data in the decision-making process within an organization.
The goal of business intelligence is to help businesses make better decisions by providing them with timely, accurate, and actionable information.
Data analytics is the process of examining data sets in order to draw conclusions about the information they contain.
Data analytics can be used to find trends, correlations, and other business-critical information.
How data analytics can help improve BI
When it comes to business intelligence, data is the lifeblood of the operation.
Businesses must have access to accurate and timely data in order to make sound decisions. Data analytics can help to improve BI functions by providing insights that would otherwise be unavailable.
For example, data analytics can be used to identify patterns and trends in customer behavior. This information can then be used to make changes to the way that BI processes are carried out, such as by changing the manner in which data is presented or by adding new features to BI tools.
But what happens when data changes?
Data analytics can help here too. By constantly monitoring data sets for changes, businesses can make sure that their BI processes are always up-to-date. This is especially important in fast-paced industries where change is the norm.
How BI tools can help make data more understandable and actionable
Data analytics is a powerful tool, but it can be difficult to make sense of all the information that it produces.
By packaging up data analytics functionality in an easy-to-use interface, BI tools make it possible for non-technical employees to understand insights from data.
Here are just a few of the ways that BI tools can make data more understandable and actionable:
1. Visualizing data in an easy-to-understand format
One of the most difficult aspects of data analytics is trying to make sense of all the information that it produces.
BI tools can help by displaying data in a visual format that is easy to comprehend, such as charts, graphs, and maps. This makes it possible to see patterns and trends that would be otherwise hidden in a sea of numbers.
2. Presenting data in a context that is relevant to the user
Another challenge with data analytics is that it can often produce vast amounts of irrelevant information.
BI tools can help by presenting data in a context that is relevant to the user. For example, a BI tool could show sales data in the context of the customer’s journey or marketing data in the context of the buyer’s journey.
3. Adding interactivity to data
BI tools can also add interactivity to data, which makes it possible to explore data sets in more depth.
For example, a BI tool could allow users to drill down into data sets to see more detailed information or to filter data sets to only see the information that is relevant to them.
4. Making data available on mobile devices
More and more people are using mobile devices to access information.
BI tools can help by making data available on different devices, including mobile devices, which makes it possible for users to access information when they are on the go.
5. Automating data-driven processes
Data analytics can be used to automate processes that are currently carried out manually. BI tools can continue that automation into reporting and sharing of data.
For example, a BI tool could be used to automatically generate reports based on data sets that are frequently updated or to send alerts when certain conditions are met.
By automating data-driven processes, BI tools can help businesses save time and resources.
6. Enabling self-service analytics
BI tools can also enable self-service analytics, which allows business users to access data and carry out analysis without having to rely on IT staff.
This is especially useful for businesses that do not have the resources to invest in a full-time data analyst.
7. Providing predictive analytics
Predictive analytics is a type of data analytics that is used to make predictions about future events based on historical data.
By using predictive analytics, businesses can make better decisions about where to invest resources and how to respond to changes in the market.
8. Enhancing security and governance
Data security and governance are important considerations for any business that collects and stores sensitive information.
BI tools can help by providing features that can help to enhance security and governance, such as data encryption and user access controls.
These benefits—and many more—create a virtuous circle that enhances the value of both business intelligence and data analytics.
When used together, they can help businesses gain a competitive edge and make better decisions about how to use their resources.
How to implement business intelligence in your organization
By sticking to the following five steps, you can ensure that your business intelligence implementation is successful.
1. Understand the needs of your organization
The first step in implementing business intelligence is to understand the needs of your organization.
You should know what type of data you need to collect, what type of insights you need to generate, and what processes you need to automate.
Only then can you select the right BI tools for your organization. These can include: