Why Business Analytics for Managers Course?

Business Analytics is a process that involves data from collating to studying, using statistical models and iterative methodologies to extract insights from the data studied.

Collating ? sequencing ? processing ? studying ? extracting insights

Business Analytics aims to determine which datasets are useful and how they can be used to solve problems and increase efficiency, productivity and revenue.

The current market for Business Analytics

The usage of data for benefit analysis is almost in every industry today. It’s no longer confined to only one department. Data is tuned for the marketing department to target the pain point of the right customer and thus, streamlining the work-process operations accordingly.

Careers in Business Analytics:

1. Management Analyst/Consultant
2. Data Analyst/Scientist
3. Business Intelligence Analyst
4. Program and Marketing Managers
5. Big Data Analytics Specialist
6. Operations research Analyst
7. Market Research Analyst

Business Analytics has become an important aspect for project managers in developing strategic project plans and planning ways to spend and invest money.

Few aspects of analytics should be part of every manager’s knowledge. Even for managers who do not work directly with analytics, the techniques and strategies behind the plan should be thoroughly understood.

Who are eligible for ‘Business Analytics for Managers’ course?

1. Managers at a beginner level and working executives who are new to the analytics domain
2. Business Decision Makers
3. Senior-level managers and executives
4. CEO’s and Business Owners
5. Middle-level managers who wish to switch to a career in analytics
6. Domain specialist professional with backgrounds in planning to undertake business analytics projects

Concepts of Business Analytics for Managers

7 concepts of Business Analytics that are essential to understand for Managers are:

1. Correlation Analysis: Correlation Analysis permits us to compare two individual variables to determine if there is a relationship(correlation) between them. Analysts usually use this technique when there is a suspicion of those two variables working together in some way. Correlation analysis provides a way to evaluate the assumptions.
2. Data Mining: Data Mining deals with large datasets also referred to as Big Data. With advanced statistical analysis, analysts research large amounts of data looking for patterns and trends that are useful to a business/organization. They also check for any correlations between two variables. The agenda is to be able to create workable suggestions based on a large amount of data.
3. Experimental Design: With the experimental design sector, analytics are used to test the validity of a strategic business plan. This may include a detailed-study, product designing or a marketing plan. This involves changing an aspect of the product and comparing it to the previous version of the product. This approach determines the quality enhancement, productivity and savings-factor with the change in a product or service.
4. Factor Analysis: Factor Analysis comes into play when we need to deal with more than two variables. The methodologies followed in factor analysis helps to reduce the number of variables needed to deal with.
5. Linear Optimization: Linear Optimization helps organizations in the formation of an actionable set of steps from larger datasets. With certain mathematical models, analysts determine the best possible result based on a set of constraints. These constraining factors in business include manpower, time, money and materials. Linear optimization helps determine the suitable combination of the mentioned factors to reach the best possible outcome i.e., with an increased profit at a reduced cost.
6. Metal Analysis: At times, it is preferred and suggested to refer to earlier studies or researches regarding certain issues. Meta-Analysis deals with the research of studies previously done on an issue. Researchers examine the earlier work to find any kind of patterns and discover relationships between variables. This approach contributes to saving time and money involved with statistical analysis research
7. Regression Analysis: This approach involves a study about the comparison of benefits with one variable to another. With regression analysis, checking past data effects due to one variable on another helps businesses make precise predictions and decisions in areas like pricing accordingly.

Here are the key techniques used in data analysis. Managers in an organization should have knowledge of these to understand data analytics and also to have an idea of essentials’ representation while developing a new strategy.

Looking for a “Business Analytics for Managers” course? Check out SKILLOGIC:

SKILLOGIC is one of the world’s leading certification training providers specialized in best practice certifications in the domains of project management, IT service management, quality management and business analytics.

SKILLOGIC has strong training characteristics:

1. The industry-best trainers – SKILLOGIC has trainers that are well-equipped with knowledge as CEOs of AI-based organizations.
2. Flexible learning option: You can make your choice in the mode of learning
3. Dual certification: Get certified from IABAC- International Association for Business Analytics Certification and IBM industry
4. Flexi-pass: You will be eligible to attend the related sessions for 365 days
5. Industry best services: Well-aligned syllabus with the industry
6. Boosts career prospects: Encourages you to move forward with the practical skills you gained
7. Hands-on case studies: Real-time examples for a better understanding of the subject
8. No Coding: No programming background required and no need to learn any programming language.