Reflection on using Python and Microsoft Power BI for data analysis

The implication of data analytics helps in evaluating large volumes of business data which helps in optimizing business performance, maximizing profit, and executing of “strategically-guided decision-making”. I have presented my understanding of MS Power BI and Python and how this might impact the future practice in digital businesses using Gibb’s Reflective Cycle.

            Figure : Gibb's Reflective Cycle

Description:

Business Intelligence (BI) ingests business data and represents the ingested raw data in a user-friendly view like interactive dashboards, graphs, visual reports, and many more. The viewpoints on the use of Business Intelligence Software such as MS Power BI and Python for data analytics that I have gathered from my participation in the module seminar of “University of Salford” are presented in this blog spot. According to “CIO Magazine” Business Intelligence not only helps in generating visual reports from unstructured or semi-structured data but also offers digital business professionals in examining business trends and deriving business insights.  MS Power BI is a “Cloud-based” analysis service that helps in extracting rapid insights. In fact, the use of MS Power BI helps in extracting large volumes of raw data in order to visualize the data. Therefore, according to my opinion, MS Power BI brings multiple data sources together in order to generate a comprehensive view of the company’s “information assets”. Within the module seminar, we visualized the predictive power of Power BI. Through the use of MS Power Bi Software digital data analytics professionals become able to develop different prediction models. This helps business entities in making “data-driven decisions” across different aspects of the business (Cainas et al., 2021).

Python has multiple libraries that takes an essential contribution to developing different machine learning and deep learning models. 

Feelings:

Learning new things that contribute to the betterment of professional skills and attributes always creates positive feelings. In the module seminar, I have acquired a basic to an advanced level understanding of business intelligence skills that created a positive feeling. As per the view of Ameer et al., (2020), Business Intelligence Software such as MS Power BI and Python have immersive use cases in financial management as well as human resource (HR) management. From the knowledge that I have gained from the module seminar, I can say that the integration of predictive analytics (which is an important part of data analytics) in HRM helps in evaluating "employee turnover analysis", "employee work performance analysis", "training and requirements analysis", and many more. Therefore, it will not be hypothetical by saying that detailed knowledge of Business Intelligence (BI) software is a must-have for digital business professionals. 

Evaluation:

The use of Power BI helps in performing "real-time" data insights like data visualization, dashboards, and many more which run different machine learning models such as Random Forest, Logistic Regression, and many more in the background. It has been found that almost 67% of the global workforce has access to business intelligence tools. In fact, almost the adoption rate for business intelligence has reached over 26%. Therefore, according to me in order to enhance professional sustainability in this digital age an individual needs to acquire data analytics and business intelligence tools and techniques. 

Analysis:

The fundamental role of business intelligence tools is to improve business operations by making predictions based on the trend of data. The knowledge that I have acquired in MS Power BI and Python will help in translating business data into valuable insights about business processes along with business strategies. As a result, I will be able to enhance my professional sustainability in this digital age. I have gained detailed knowledge about the use of pandas, scikit-learn, PyTorch, TensorFlow, and many more. This will help in visualizing a large volume of data in order to extract meaningful insights from the data. 

Conclusion:

From the module session, I have understood that I have to strengthen my digital proficiency by learning various data visualization and business intelligence tools and techniques. 

Action Plan:

                Figure 2 : Action Plan

              (Source: Self-developed)

The actions plan that I have designed for the improvement of my digital proficiency in data analytics and business intelligence is demonstrated above.