5 Views· 09 October 2022
Business Analytics with Excel | Data Science Tutorial | Simplilearn
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Business Analytics with excel training has been designed to help initiate you to the world of analytics. For this we use the most commonly used analytics tool i.e. Microsoft Excel. The training will equip you with all the concepts and hard skills required to kick start your analytics career. The topics covered in this video are:
Introduction 00:00:00
Formatting and Functions 00:05:42
Lookup Functions 00:22:57
Statistical Functions 00:34:02
Who Is A Business Analyst?
A business analyst understands the business problems and identifies the solutions that will maximize the organization's value to its stakeholders. A business analyst is an individual who works closely with the technology team to improve the quality of the services being delivered. To become a business analyst you need to ensure the customer needs are correctly interpreted and translated into application. Another key factor in knowing how to become a business analyst is possessing skills like Excel, SQL, and business intelligence skills to deliver data-driven solutions.
Data Science Certification Training - R Programming: https://www.simplilearn.com/big-data-and-analytics/data-scientist-certification-sas-r-excel-training?utm_campaign=Data-Excel-W3vrMSah3rc&utm_medium=SC&utm_source=youtube
For a new-comer to the analytics field, this course provides the best required foundation. The training also delves into statistical concepts which are important to derive the best insights from available data and to present the same using executive level dashboards. Finally we introduce Power BI, which is the latest and the best tool provided by Microsoft for analytics and data visualization.
What are the course objectives?
This course will enable you to:
1. Gain a foundational understanding of business analytics
2. Install R, R-studio, and workspace setup. You will also learn about the various R packages
3. Master the R programming and understand how various statements are executed in R
4. Gain an in-depth understanding of data structure used in R and learn to import/export data in R
5. Define, understand and use the various apply functions and DPLYP functions
6. Understand and use the various graphics in R for data visualization
7. Gain a basic understanding of the various statistical concepts
8. Understand and use hypothesis testing method to drive business decisions
9. Understand and use linear, non-linear regression models, and classification techniques for data analysis
10. Learn and use the various association rules and Apriori algorithm
11. Learn and use clustering methods including K-means, DBSCAN, and hierarchical clustering
Who should take this course?
There is an increasing demand for skilled data scientists across all industries which makes this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals:
IT professionals looking for a career switch into data science and analytics
Software developers looking for a career switch into data science and analytics
Professionals working in data and business analytics
Graduates looking to build a career in analytics and data science
Anyone with a genuine interest in the data science field
Experienced professionals who would like to harness data science in their fields
Who should take this course?
There is an increasing demand for skilled data scientists across all industries which makes this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals:
1. IT professionals looking for a career switch into data science and analytics
2. Software developers looking for a career switch into data science and analytics
3. Professionals working in data and business analytics
4. Graduates looking to build a career in analytics and data science
5. Anyone with a genuine interest in the data science field
6. Experienced professionals who would like to harness data science in their fields
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