Today's CEOs and executives are focused on creating a data-driven culture. Businesses now are trying their best to adopt data-driven culture to prevent them from falling behind their competitors, deliver more value to their customers, and gain more competitive advantages. Data is capable to assist businesses in gaining a better understanding of their customers' behavior, streamlining operations, and developing strategies.

In addition to those reasons, businesses are also encouraged, or even forced, to become a data-driven company after seeing how data trends are disrupting the entire markets. Adopting data-driven culture is no longer an option but 'an obligation' – if they want to make the most of their data in an era where agility and innovation are critical for business sustainability. In fact, data-driven businesses "are growing at an average of more than 30% annually," according to a Forrester report from 2018.

Then this problem arises. After obtaining data from multiple resources, how can companies make better and precise decisions with this massive amount of data they have?

Business intelligence comes as the solution for the aforementioned problem.

Business Intelligence

1. Business Data-Driven Location Analytics

According to Negash (2014), business intelligence is defined as the collection, management, and analysis of relevant data and information from structured and unstructured enterprise businesses using modern information technology. The goal of business intelligence is to help businesses improve their competitiveness by determining effective business through relevant data and information results, improving business level, and accumulating business knowledge. Microsoft also believes that business intelligence can help businesses analyze their historical and current data so they can quickly discover actionable insights for creating strategic decisions.

The desire to be more advanced in terms of technology, the need to make better use of data for operational purposes, and the increased productivity gained from the BI implementation are typically the main factors driving the adoption of business intelligence. As the need and necessity for business to utilize their data to remain competitive grows, so too will BI adoption, and more specifically cloud-based solutions that can offer the kind of scalability that smaller enterprises require to invest in BI solutions. Therefore, business intelligence tools make this possible by processing large data sets across multiple sources and presenting findings in visual formats that are easy to understand and share.

As the need for businesses to use their data to stay competitive grows, so will business intelligence adoption. Therefore, investing in business intelligence tools can help businesses processing large data sets from multiple sources and presenting findings in easy-to-understand and share visual formats. One of business intelligence tools that businesses can utilize is Microsoft Power BI.

Microsoft Power BI

Business Intelligence now has been simplified with an easy and quick BI tool for an effective data visualization – the Microsoft Power BI. Power BI is a business analytics solution that lets you visualize your data and share insights across your organization or embed them in your app or website. The solution comprises several products and services, and value and versatility comes from leveraging the individual elements, and taking advantage of how they work together.

Power BI becomes the Data Analytics tool that helps business professionals to bring together data from multiple sources to deliver a comprehensive view of the company's current condition. Power BI has a gateway that allows connection to SQL Server Databases, Analysis Services models, and many other data sources on the dashboard. It is capable to deliver predictive analysis, data visualization, R integration, and data analysis expressions. In addition, it enables businesses to create predictive models by dragging, dropping, and connecting data modules.

What Power BI Offers for Businesses

1. Data Visualization using R

Power BI offers visualization using R. R in Power Query enables businesses to gain advanced analytical depth through data visualization, reports on the dashboard, data models, and data results. It also performs advanced data cleansing and preparation tasks, such as outlier detection and missing values completion. R visuals can be shared in the reports and on the dashboard where they are interactive and more intuitive supported by The Quick Insights feature – a set of advanced analytical algorithms that enables to find insights into the compiled data in a new and congenial way.

2. Segmentation and Cohort Analysis

The segmentation and cohort analysis assists in breaking down or combining data into meaningful groups and comparing the groups to identify meaningful relationships between the data used to develop data hypothesis and further analysis. This will help businesses to cluster their data and determine the measure among each cluster. Custom visuals in Power BI will conduct further analysis and evaluation of the clusters.

3. Data Streaming

Data Streaming in Power BI allows businesses to display and analyze real-time data, obtain instant insights from time-sensitive information, and monitor social media campaigns to measure their performance. Microsoft Azure Stream Analytics and Azure Machine Learning enable businesses to gain deep insights into real-time data integration and aggregate the data.

4. Data Grouping and Binning

When several categories of data should be grouped, Power BI enables data grouping and binning which play an important role in representing data. Data grouping and binning creates more clear view, analysis, and explore data trends in visual. In addition, it also helps to refine the data figures.

5. Deep Market Understanding

Good use of Power BI enables businesses obtain sufficient data to resolve potential risks and gain a deep understanding of their market outlook. Combined with sufficient data analytics, Power BI is a powerful tool to accommodate businesses in managing their data asset more effectively.

Conslusion

To stay competitive, businesses now need analytically oriented systems that can revolutionize their ability to rediscover and use data they already have. Therefore, great business intelligence (BI) enables businesses and organizations to make great use of their data. By displaying current and historical data within the context of their business, business intelligence can assist companies in making better and strategic decisions.

Reference:
Dunlap, S. (2021). Key Drivers of Business Intelligence. Impact Networking. [BLOG]. https://www.impactmybiz.com/blog/key-drivers-of-business-intelligence/
Krishnan, V., Bharanidharan, S., & Krishnamoorthy, G. (2017). Research Data Analysis with Power BI. 11th International CALIBER-2017,Tamil Nadu.