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Microsoft Power BI Data Analyst-PL-300

                                                                   

REGISTRATION

  • July 19-21, 2022:(CLASS IS FULL)
  • This training is being held virtually via Cisco WebEx.
  • Each daily session will start at 9:00 AM and finish at 5:00 PM. All times are in the Central Time Zone.
  • Instructor: FastLane US

 

  • September 13-15, 2022: Registration Link
  • This training is being held virtually via Cisco WebEx.
  • Each daily session will start at 9:00 AM and finish at 5:00 PM. All times are in the Central Time Zone.
  • Instructor: FastLane US

 

  • October 18-20, 2022: Registration Link
  • This training is being held virtually via Cisco WebEx.
  • Each daily session will start at 9:00 AM and finish at 5:00 PM. All times are in the Central Time Zone.
  • Instructor: FastLane US

 

COST

$800.00/Attendee

CANCELLATION POLICY
All trainings are NONREFUNDABLE within 14 days of the training’s scheduled start date. Attendees who wish to cancel within the 14-day nonrefundable period will need to email Rami Lotay (rslotay@memphis.edu) and give a detailed explanation as to why they cannot possibly attend, as they will still be liable for payment in full.

 

WAITLIST INFORMATION

If you cannot attend the session above, please click here to join our waitlist. Once enough demand has been built, you will be contacted with dates for the next session. Please note that submitting your information on the waitlist does not automatically reserve a space for you in the training. You will have to register/pay via a separate registration portal.

 

OVERVIEW

This course will discuss the various methods and best practices that are in line with business and technical requirements for modeling, visualizing, and analyzing data with Power BI. The course will also show how to access and process data from a range of data sources including both relational and non-relational data. This course will also explore how to implement proper security standards and policies across the Power BI spectrum including datasets and groups. The course will also discuss how to manage and deploy reports and dashboards for sharing and content distribution.

OBJECTIVES

  • Utilize the entire Microsoft BI stackConnect on-premise data sources to the cloud
  • Build an enterprise Data Catalog to share queries
  • Implement scorecards, dashboards, and KPIs
  • Analyze data with PowerPivot
  • Integrate data from many different external data sources
  • Implement effective, high-performing BI solutions
  • Provide intuitive ad-hoc reporting for business users by implementing Power View

Who Should Attend (Audience Profile)

The audiences for this course are data professionals and business intelligence professionals who want to learn how to accurately perform data analysis using Power BI. This course is also targeted toward those individuals who develop reports that visualize data from the data platform technologies that exist on both in the cloud and on-premises.

Job role: Data Analyst

Preparation for the exam: PL-300

Feedback from the FedEx Attendees

  • I found it much more relevant than the DA-100 course.
  • It seems like anyone taking this class would have some knowledge of loading flat files and yet we spent time and a lab doing just that.
  • Couse covers data modeling… this was great because it allowed us to skip lower-level lessons because we had experience.
  • Data modeling and data shaping are keys to people doing analytics and this is a major focus of the training.
  • More data modeling and DAX than in the original DA-100 course.
  • Demos can be adapted to FedEx Finance or any other FedEx group’s data sets (versus Sales data that is part of the standard offering).
  • Material is very good and relevant to what I see other data analysis personnel in my org would need in order to improve their skillset.
  • Of particular interest was row-level security, dataflows/datasets, and modeling.
  • All of this enables more enterprise-level data layers and less smaller organizational.
  • Basically, let really smart people build the data model and enable others to plug into it.