Microsoft Excel for Data Analyst

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What is this course about

 This training would be very useful to participants across various industries and functional specializations such as MIS, Finance, Marketing, Operations, Human Relations, Information Technology and Administration.

This interactive training targets specific business situations, and then demonstrates how to create spreadsheets for those problem areas. Attend these extraordinary, information-packed, powerful sessions to increase your productivity, improve the quality, accuracy & make a better report.

This course is recommended for end users seeking proficiency in the use of Microsoft Excel 2013 at advanced level or seeking to obtain Microsoft Office Specialist (MOS) certification in Microsoft Excel 2013.

What are the course deliverables ?

 Scope of Learning:

User able to manage data independently

User able to do reports (eg: Financial, Banking, Insurance, Pharmaceutical, Retail, Educational, small shops etc)

User will become data analyst

User will able to do MIS reports

Maximum organization will use the excel

It requires day to day activities to manage & analyse the data

High impact, proven training – 30000+ professionals trained globally

Experienced, expert instructors – Our Instructors come with a rich, 10+ years of industry experience.

Classroom Training programs delivered across 50+ locations globally

Content is developed in-house in GreyCampus by highly experienced industry experts

Program Highlights

 Course Objectives:

At the end of the training the participants would learn/use/acquire the following techniques/knowledge:

• Excel Advancements – some amazing features incorporated only in last 5 years
• Using Lookup & reverse Lookup techniques – easy demo of VLOOKUP, HLOOKUP, INDEX and MATCH
• Advanced Data Sorting and Filtering techniques
• Generating Pivot Tables and Charts from complex datasets, instantly
• Implementing Slicers and Sparklines to build interactive dashboards
• Exploring Data Validation techniques and creating dynamic lists
• Using ‘What-If-Analysis’ and Data representation techniques