Data Science for Real-Business – Big Data Analyze Training Course Malaysia
Big data age is a long time, but there is no doubt that its influence has been felt. Can the future of marketing work be attributed to data science?
The digital marketing technology industry continues to attract me even if software vendors are saturated. Recently, I spend more time on data science, refer to recent posts in my social media platform. However, before discussing how marketing benefits from data science, I think it’s important to discuss the scope of marketing techniques.
If you follow the growth of marketing technology, it’s easy to lose in the new data ocean technology.
Marketing Data Director (Medium Salary: estimated 200K annual): We all know that marketing data grows fast and requires a huge database. For most organizations that rely on business intelligence (BI) or IT, marketing data management is a big challenge. BI and IT have their own priorities and rely on how your organization organizes marketing data management can not be their top priority.
Interestingly, this role is also a mixture of analytical / BI and marketing skills sets. An ideal candidate may be an experienced business intelligence person who spent most of his time helping the marketing team to understand the practice of modern marketing. Marketing analysts with strong data skills can also play a role.
- Successfully perform all steps in a complex Business Data Science project
- Perform Data Mining in Business
- Understand how to apply the Chi-Squared statistical test
- Apply Ordinary Least Squares method to Create Linear Regressions
- Assess R-Squared for all types of models
- Assess the Adjusted R-Squared for all types of models
- Create Dummy Variables
- Interpret coefficients of an MLR
- Read statistical software output for created models
- Use Backward Elimination, Forward Selection, and Bidirectional Elimination methods to create statistical models
- Create a Logistic Regression
- Intuitively understand a Logistic Regression
- Operate with False Positives and False Negatives and know the difference
- Read a Confusion Matrix
- Create a Robust Geodemographic Segmentation Model
- Transform independent variables for modelling purposes
- Derive new independent variables for modelling purposes
- Check for multicollinearity using VIF and the correlation matrix
- Understand the intuition of multicollinearity
- Apply the Cumulative Accuracy Profile (CAP) to assess models
- Build the CAP curve in Excel
- Derive business insights from the coefficients of a logistic regression
- Understand what model deterioration actually looks like
- Apply three levels of model maintenance to prevent model deterioration
- Install and navigate SQL Server
- Install and navigate Microsoft Visual Studio Shell
- Clean data and look for anomalies
- Use SQL Server Integration Services (SSIS) to upload data into a database
- Deal with Text Qualifier errors in RAW data
- Create Scripts in SQL
- Apply SQL to Data Science projects
- Create stored procedures in SQL
- Present Business Data Science projects to ready use
- Someone wants to master stats for business analytics
- Someone who wants to learn stats from the ground up
- Someone who wants to get hands-on experience with Business Data Science
Comprehensive introduction to your business data analysis teaches you how to apply different data analysis methods to make your data a new insight and intelligence. The ability to ask is a strong competitive advantage that leads to new sources of income, better results and productivity gains. The report recently stated that data analysis is one of the most important skills in Malaysia economy today. This course focuses on the following different analysis methods. In this lesson, you will learn why the form of analysis is important and provide examples using Excel 2013 for analysis.