After the industrial revolution worldwide in the 20th century, data analysis started playing a significant role in decision-making, and it continued in the next century as well. Nowadays, the extensive level of effort organizations are putting into data analysis ensures that data-driven decision-making is the future. In this case, data visualization is a mandatory part of data analysis. Here arises the need for efficient data visualization tools. There are many such tools in the market, e.g., Power BI, SAP Business Objects, Datapine, QlikSense, Tableau, etc.

The organizations that are, using Microsoft services regularly prefer Power BI. But that does not mean others don’t. However, if someone wants to get the maximum outcome from this huge popular tool, it is better to be used in an MS environment.

Before we assess the impact of power bi, we need to understand the requirement of Business Intelligence in an organization. Business intelligence helps the authority decide on the next best action. Data scientist or BI analyst evaluates the performance of the organization by comparing it with the competitors based on market trends.

These are a few ways that BI helps companies make smarter, data-driven decisions:

• Identify ways to leverage profit
• Analyze the behavior of the customer
• Compare the company’s data with competitors
• Assess performance
• Optimize operations
• Predict trend
• Discover issues

To accomplish all those points above, there is no alternative of data visualization. A smart and easy-to-use visualization tool makes the life of an analyst easier. Power BI has some features that make it one of the prominent BI tools in the market right now.

The Key Features of Power BI Include

1. Hybrid deployment support: It allows the BI tool to connect to different data sources and helps the automatic application of analytics to information by creating data subsets using the Quick Insights feature.

2. Power Query: It helps integrate and transform the data into the Power BI web service for enhanced Data Visualization.

3. Common data model: It makes the use of extensible database construction easy.

4. Customization feature: It changes the appearance of the Data visualization tools and can import new tools into the platform.

5. Power BI dashboard: t is embedded in other software products via APIs.

Its Advantages Include

1. Faster development capability: Power BI drag and drop feature allows the user to explore and play more with the report design by fast and easy user experience.

2. Less manpower: One can get NLP and machine learning results through clicks without writing any codes, which reduces workload.

3. Saves production cost: Power BI dashboards can easily be the alternative to a data-driven platform to some extent. Creating a data-driven platform is costly and needs the involvement of a large number of professionals where building power bi dashboards is less expensive and easier but can show you the same results.

4. Easy to interpret the outcome: All the plots and visuals in the Power BI interface are very simple and easy to interpret. Advanced analytics results can be shown in a very easy manner that even a non-technical person can understand.

5. Easy to learn: Power BI has a large community to solve problems and lots of online resources to train someone interested. It is built so that both the technical and non-technical person can learn and use it.

With the advancement of technology, the need for easy-to-use tools is increasing. Power BI is undoubtedly one of them. All the advanced features and regular updates in the tool make it one of the best BI tools in the market right now. You can take one step ahead by introducing this fantastic tool to your business undoubtedly.

Author

S M Saddam Hossain is performing as Data Scientist for more than 4 years with expertise in data analytics (R) and data visualization (Microsoft Power BI).

Also he has a decent command over Microsoft SQL to manage data held in a relational database management system (RDBMS). He also claims to be an enthusiastic learner of machine learning with Microsoft Azure Machine Learning Studio.

He has successfully completed Business Intelligence for Data Analytics (Microsoft Worldwide Learning),

Data Platform & Analytics Foundational for Data Analytics Competency (Microsoft Worldwide Learning) & Data Science with R Certification by Bangladesh Hi-Tech Park Authority, ICT Division.