MCSE Data Management and Analytics | Preparation Track (72 Hrs. )

MCSE Data Management and Analytics | Preparation Track (72 Hrs. )

$500

The main purpose of this track | Give audiences the ability to

  •  Analyze their business data using BI techniques.
  • Add BI techniques to business data.
  • Go beyond the capabilities of tables ,charts and uses Pivot Tables and Charts, the Excel Data Model and Power BI.
  • Use Microsoft R Server to create and run an analysis on a large dataset.
  • Show how to utilize it in Big Data environments, such as a Hadoop or Spark cluster, or a SQL Server database.

 

Description

MCSE Data Management and Analytics | Preparation Track (72 Hrs. ) 2

Program Added Value | After completing this program, audiences will be ready to pass MCSE Data Management and Analytics certification exams by have the following skills :

  • Create and Formatting Measures and KPIs, Create PivotCharts, Use cube functions, and Construct graphs that can summarize the information retrieved by using cube functions.
  • Build Excel Data Model, Connect to databases, transform the data into a convenient form, and load the data into Excel tables or into the Data Model.
  • Transform formatted Excel reports into usable data to perform further analysis.
  • Use the key visualizations in Power BI and describe the rationale for self-service BI.
  • Use Q&A to ask questions in natural query language, and create content packs and groups.
  • Use the Microsoft Power BI suite of tools to connect to a wide variety of data sources. These include the main industry-standard databases, Microsoft cloud-based services—Microsoft Azure SQL Database, Azure Data Lake, and Azure Machine
  • Learning—alongside Microsoft Excel® and other files, and software as a service (SaaS) providers such as Microsoft Bing®, Facebook, and MailChimp.
  • Goes behind the scenes of the visualizations, and explores the techniques and features on offer to shape and enhance your data, and create attractive reports, while helping to find hidden insights into data.
  • Explain how Microsoft R Server and Microsoft R Client work
  • Use R Client with R Server to explore big data held in different data stores
  • Visualize data by using graphs and plots
  • Transform and clean big data sets
  • Implement options for splitting analysis jobs into parallel tasks
  • Build and evaluate regression models generated from big data
  • Create, score, and deploy partitioning models generated from big data
  • Use R in the SQL Server and Hadoop environments

After completing this program, audiences will be able pass the following exams

  • Exam 70-779 : Analyzing and Visualizing Data with Microsoft Excel
  • Exam 70-778: Analyzing and Visualizing Data with Microsoft Power BI.
  • Exam 70-773:  Analyzing Big Data with Microsoft R

 

Attendees Required Resources:

Personal Laptop with at least Windows 10 & Office 2016 is required to access course LAB

 

Additional information

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