Introduction to Data Analytics with Power Query (Get and Transform in Excel 2016)

Description

In the accounting profession, dealing with data is life. Doing it efficiently and effectively are skill differentiators. Power Query, part of Microsoft Power BI suite, is an indispensable for extracting, transforming and loading data (the “ETL” of the commonly referred to ETLR). In this session, we will explore the basics of the Power Query add-in – extracting, transforming and preparing data for analysis.

Learning Objectives

* Import and transform basic data into Excel using Power Query.
* Understand and apply the data load capabilities of loading into Excel versus loading into the “data model”, and why it matters.
* Identify the basics of extracting and transforming data

Major Topics

* Deep dive into Power Query (Excel 2016 Get & Transform) * Explore the basics of extracting and transforming data, which is the first necessary step to data analysis and reporting * Top 6 features most important to accountants (data source flexibility, appending queries, unpivot, etc.) * Exploration of real Power Query use cases, many of which accountants could implement immediately * A summary of top resources and experts to get you started on the journey of learning Power Query * Excel workbooks will be made available for all participants to use at their leisure and further explore the topics discussed

Provider
Business Learning Institute
Course Level
Advanced
Professional Area of Focus
Technology
CPE Field of Study
Information Technology
1
Who Should Attend

Any business professional responsible for managing and working with data.

Instructor(s)
Donald Tomoff
Prerequisites

Comfortable with Excel navigation and data related topics – LOOKUP, Pivot Tables, Data Tables, etc. would be helpful, but not required.

Advanced Preparation

None

Location
Online
Register Now
When
Oct 7, 2020
12:00 pm - 1:00 pm EDT
Location
Online
Total CPE Credits
1
Format
Webcast Replay

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$35.00

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$45.00

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Introduction to Data Analytics with Power Query (Get and Transform in Excel 2016)


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