Certificate For Module (Business Intelligence And Data Automation) - School Of Professional And Continuing Education, Hku

    9,000.00 9,000.00 9000.0 USD




    Certificate For Module (Business Intelligence And Data Automation) - School Of Professional And Continuing Education, Hku








    30 hours (PT)


    6 weeks




    Applicants Should Hold An Advanced Diploma, A Higher Diploma Or An Associate Degree Awarded By A Recognized Institution. Those With A Business, Finance, Economics, Mathematics, Science, Engineering, It Or Computer Science Background Would Have An Advantage. [Applicants With Other Equivalent Qualifications Will Be Considered On Individual Merit.]


    (1) Introduction To Business Intelligence (Bi) (6 Hours) (A) Overview Of Bi (2 Hours) (B) Principles Of Bi And Business Analytics (2 Hours) (C) Bi Powered By Business Strategies And Technologies (2 Hours) (2) Introduction To Data Preparation And Data Automation (6 Hours) (A) Fundamentals Of Big Data And Data Automation (2 Hours) (B) Data Wrangling And Processing: Data Cleansing, Data Transformation, Data Consolidation, Data Aggregation And Data Automation (2 Hours) (C) Introduction To Computational Tools For Data Preparation: Microsoft Power Query, Microsoft Power Bi, Tableau Prep Builder And Glue Databrew (1 Hour) (D) Data Privacy And Ethical Usage Of Data (1 Hour) (3) Techniques Of Data Transformation, Aggregation And Consolidation (6 Hours) (A) Data Filtering: Filtering Rows, Removing Unnecessary Columns, Eliminating Duplicates (1 Hour) (B) Data Matching And Rearranging: Matching Columns With Another Table, Transposing Table Data, Pivoting And Unpivoting Columns (2 Hours) (C) Data Extraction And Aggregation: Extracting Information From A Data Column, Aggregating Data With Group-By Operations (1 Hour) (D) Data Merging And Consolidation: Combining Files From Different Workbooks, Combining Tables On Different Worksheets, Appending Queries, Extracting Information From A Filename, Understanding The Differences Between Duplicating And Referencing A Data Set (2 Hours) (4) Data Automation And Performance Improvement (6 Hours) (A) Techniques Of Data Automation: Reviewing Empty Cells And Errors, Stepwise Automation, Handling Data Error, Use Of Parameters For Data Selection, Avoiding Hard-Coding Source File Path (1 Hour) (B) Change Of Default Automation Behaviour (1 Hour) (C) Integration With Excel Pivot Tables, Pivot Charts And Dashboards (1 Hour) (D) Importing Data From Various Sources: (I) Excel, Csv And Text File (0.5 Hour) (Ii) Data From Webpage (0.5 Hour) (Iii) Pdf File (0.5 Hour) (Iv) Database Tables (0.5 Hour) (V) Stock Prices Extraction (0.5 Hour) (E) Performance Improvement With Data Automation (0.5 Hour) (5) Business Cases Related To Bi And Practical Applications Of Data Automation (6 Hours) (A) Illustration Of Data Transformation: Sales Data Consolidation, Consolidation Of 1 Million Pos Records With Multiple Master Files, Consolidation Of 48-Month Of Sales Files (1 Hour) (B) Integration Of Transformed Data Sets With Bi Tools: Importing Transformed Data Into Financial Dashboards (1 Hour) (C) Storytelling For Managerial Dashboards (1 Hour) (D) Practical Applications Of Bi To Assist Business And Financial Decision Making (1 Hour) (E) Operational Improvement With Data Automation (0.5 Hour) (F) Corporate Value Creation Powered By Bi And Data Automation (0.5 Hour) (G) Managerial Issues And Organizational Impacts Related To Data Automation (1 Hour)