Modern Analytical work Flow


By: Aayush Tyagi

Aayush Tyagi
Aayush Tyagi


Value of Business Intelligence comes to play when we bind the power of predictive and prescriptive analysis. Today, data is increasing at a rapid rate and business are taking decisions on the basis of statistics analysis.

Connected devices tends to generate data in unstructured or semi structured form. We all are surrounded by machines and smart devices that generate huge amount of data every minute. Henceforth, companies uses Analytics and Business intelligence to make correct decisions with the help of ML, AI and data driven techniques. Gartner reports suggests that 25 billion things will be connected via IOT by 2025. Gartner predicts that insurance, healthcare and smart house are topmost industries placed to earning the most from IOT sector. 

From the moment we wake up and get back to sleep we all are producing data, which is utilized to companies for analysis. Whether we are listening songs, changing our TV channel or even browsing websites and buying online we are producing data. Industries are using gather data as a currency because this helps them to improve their business models and investment scenario.

Business Intelligence is a systematic way of data analysis. Saeed et al. (2012) focuses on managerial approach to improve decision making. Chris et al. emphasizes on how BI is changing business scenario.  This requires data collection, data preprocessing, data cleaning and then applying statistical tools for decision-making. Companies have founded different techniques for BI and decision-making. This depends upon the kind of data set and business model companies are using. The raw data is transformed to beneficial information. John et al. define the importance of EDA in quantitative and qualitative study. Statistical tools used for evaluation are SPSS, R studios, Power BI and Tableau. 


Modern Analytical work Flow
Modern Analytical work Flow

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Business Intelligence are further classified into stages. Various stages related to BI are:

  • Data Source
  • Data Analysis
  • Decision making techniques.
  • Situation Awareness
  • Risk Management

References :

[1] Rouhani, Asgari. (2012). “Business Intelligence concept and approach” Euro Journals.

[2] John. “A guide to write dissertation on Data Analytics”. 

[3] kolhe, Patil. (2011). “BI tools and techniques”

[4] Mohan Babu. (2000). “Into the mind of IT people and Customers”.