From Data to Decisions: Empowering with Business Intelligence and Data Visualization Tools

A Quick Definition Recap

Business Intelligence

Investopedia defines business intelligence as the process of analyzing business data using business intelligence (BI), a technology-driven process that gives managers and executives actionable insights to help them make more educated company decisions.

Data mining, process analysis, performance benchmarking, and descriptive analytics are all included in the wide category of business intelligence. All of the data that a company generates is parsed by BI, which then provides reports that are simple to read, performance metrics, and trends that help managers make decisions.

Data Visualization

According to IBM, data visualization involves presenting data using various graphical elements like charts, diagrams, infographics, and even animations. These visual representations effectively convey intricate data relationships and insights in a manner that is easily comprehensible.

Data visualization is used for multiple purposes. In addition to being utilized by data specialists, it is also used to manage and depict organizational structures and uncover patterns and trends. Harvard Business Review identifies four main purposes for data visualization: inspiring ideas, illustrating concepts, aiding visual exploration, and everyday data depiction.

Business Intelligence and Data Visualization

Business intelligence and data visualization often go hand in hand. While business intelligence is the data foundation, data visualization is the visual representation of such data for easy comprehension of actionable plans.

Visuals have always been the preferred method to communicate complex datasets in easy-to-understand format. With the effective usage of the two tools combined, users can quickly drill down the trends and patterns and make timely adjustments to gain a competitive advantage in the market.

Oftentimes, there are built-in data visualization tools in business intelligence software. Common types of data visualizations you can find in a business intelligence tool include:

• Bar chart
• Pie chart
• Line graph
• Box plot
• Scatter plot
• Radar or spider chart
• Dot map or density map
• Funnel charts
• Treemap

Features

One of the first things you should pay attention to is the tool’s features.

• Interactive dashboards, advanced analytics (the process of extracting data insights beyond conventional business intelligence through the use of sophisticated machine learning and visualization techniques), and real-time business data processing are functionalities to be on the lookout for.
• The tool should have no trouble supporting vast data sources and formats.
• Customization and visualization options like drag-and-drop interfaces should be available.

Budget

Every tool is an investment. When choosing the suitable tool for your organization, break down the price structure of the tool and its potential ROI.

For example, for companies that are new to business intelligence, a free version would be a great start to getting used to data analytics. For bigger organizations with large and complex datasets, however, the premium version would often be a better choice.

Ease of Use

Ease of use can be left as an afterthought when users are focusing on the features and functionalities. If you choose a tool that is feature-rich but challenging to new users, chances are you will need more time training your team. The team might take longer to embrace the new software, which slows down the time meaningful reports are generated.

Community

Analyzing data is hard. Doing it alone is even harder. Having an active community that offers tips, documents, and support to new users is invaluable.

Scalability

A great tool should be able to grow alongside a business. The BI visualization tool needs to scale - as the data grows larger and becomes more intricate, the software doesn’t slow down or crash unexpectedly.

Integration

It is essential to have strong integration capabilities in place to gain a comprehensive understanding of your business and its financial status. By integrating existing business software, such as CRM or ERP, you can achieve a more holistic view of your business performance and make informed decisions to improve its overall health.

Security

Data is the new oil. Data is also the target of almost every cyberattack. A robust security system is a must, as BI tools often host numerous sensitive business data. While applying data encryption and access controls, you need to keep in mind the industry regulations and standards that need to be complied with as well.

Power BI

Features

Integration with the Office suite from Microsoft

Updates to the dashboard in real-time

AI-driven data processing

Customizable reports

Incremental data updates

Power BI Pro offers the entire BI ecosystem as a service.

Strengths

• Compared to competitors like Tableau, Power BI offers the least expensive pricing plan.
• Extensive features and functionalities are available to solve intricate data problems.
• DAX function helps analyze datasets and creates custom visualizations.
• Suitable for big data analytics.
• Allows live data refreshing and connectivity with multiple data sources.
• Supports SQL data visualization.

Weaknesses

• Complex setup processes can be challenging, so the tool requires a steep learning curve.
• The interface is not user-friendly.
• Without coding knowledge, there are limited customization options.
• Limited collaboration features.

Google Data Studio

Features

• It connects with various platforms, including Google Analytics, Google Ads, and Facebook Ads.
• Creates reports and dashboards with customizable themes, logos, and visual aids.
• Offers diverse chart options like tables, bar graphs, maps, and scatter plots.
• Allows real-time collaboration and sharing of reports with defined access levels.

Strengths

• The tool is completely free.
• Seamless integration with Google apps
• The interface is user-friendly.
• The tool inherits Google’s granular access control and sharing options, simplifying report sharing and access management.
• Designed with a foundation of live data connections, guaranteeing data freshness without the need for complicated logic or prearranged processes.
• Google Data Studio is fully managed, relieving users’ infrastructure and installation responsibilities.

Weaknesses

• The tool is simple for reading reports but complex when it comes to creating visually appealing reports - as this needs data visualization training.
• Compared to other all-in-one BI solutions, it lacks extensive BI capabilities.
• Restricts data sources outside Google Suits.
• Not suitable for dynamic data needs since it struggles with complex visualizations.
• Privacy and security concerns.

Tableau Desktop

Features

• Real-time collaboration and sharing of data, visualizations, and dashboards.
• Connectivity to live data sources and in-memory data extraction.
• Connects to various data sources including files, databases, data warehouses, and cloud data.
• A wide range of visualization types allows easy creation of visualizations.
• Detailed and informative maps with pre-installed geographic information.
• Robust security

Strengths

• Strong performance, handles large datasets with ease.
• Mobile app available with a strong focus on mobile BI
• Active community and extensive documentation
• Affordable
• Simple upgrade process
• Easy to use

Weaknesses

• Lack of automatic scheduling, which requires manual effort to update data
• Can’t recover old data once reports are published
• Limited support for revision history
• Requires SQL knowledge for complex datasets
• No platform for developing widely shared analytic applications