SQL Server Analysis Services Training in
Hyderabad, India

Learn about implementation of Data conversions, transformations (SSIS), Data ware house creation (SSAS) and analysing the data ware house with MDX/DAX and automation of Reports with SSRS

SSAS Training in Hyderabad @ 0091 9704077815
Power BI Guru E solutions provides best Server Analysis Services, SSAS , is an online analytical processing and data mining tool in Microsoft SQL Server. SSAS is used as a tool by organizations to analyze and make sense of information possibly spread out across multiple databases, or in disparate tables or files.

Key Features

16 hours of Instructor-led training classes
In-depth hands-on learning
Learn the fundamental concepts of Power BI
Understand the concepts such as Modelling, Visualizations, exploring data in dashboard, DAX functionality, etc
Create custom data visualizations and style reports for lucid data representation
Our mentors will guide students in implementing the technology for future projects

Description

Power BI Training

Visualization of data is key to deriving useful insights from a business perspective. While there are many tools for this purpose, Power BI has been gaining popularity for offering cutting edge tools that help transform an organisation’s data into rich visuals and offer a panoramic view of the business to users helping them gauge updates in real time. The Power BI dashboard can run on multiple devices and helps organise data into trans formative visuals.

Zeolearn Academy brings you a comprehensive Power BI training course that is a perfect introduction for you into the world of BI. You will learn the basics of Power BI such as the Power BI desktop, and how to connect to data using Power BI desktop. Our expert trainers will then familiarize you with the rich components that drive this tool such as Modelling, Visualizations, exploring data with the dashboard, working with Excel, publishing and sharing data and the DAX functionality. Enrol for the Power BI course now and master the powerful capabilities of BI. Moreover, you will get access to the reference materials after registering.

What you will learn from our workshop:

  • About BI and how it will transform data and business
  • About the Power BI desktop and managing and utilizing data with it
  • Connecting data from different sources and data modelling with Power BI desktop
  • How to custom create data visualizations and style reports for lucid data representation
  • The working of Power BI and Excel
  • How to share and collaborate with data with Power BI
  • Power BI Data Analysis Expression(DAX), and its functions

Is this course right for you?

This Power BI certification course is ideal for people who have to work with data and also developers, Business analysts, project managers and other IT professionals.

Prerequisites:

Participants are expected to have an understanding of how data works and how it can contribute to building a business to attend the Power BI training classes.

Course Content:

SSAS Course Content

Building and Modifying an OLAP Cube
• Designing a Unified Dimension Model (UDM)
• Identifying measures and their suitable granularities
• Adding new measure groups and creating custom measures
• Creating dimensions
• Implementing a Star and Snowflake Schema
• Managing Slow Changing Dimensions (SCD)
• Identifying role-play dimensions

Extending the Cube with Hierarchies

  • Creating hierarchies
    • Building natural hierarchies
    • Many-to-many hierarchies
    • Creating attribute relationships
    • Distinguishing between ragged, balanced and unbalanced hierarchies
    • Discretizing attribute values with the Clusters and Equal Areas algorithms
  • Parent-child relationships
    • Defining parent and key attributes
    • Generating level captions with the Naming Template feature
    • Removing repeated entries with the Members With Data property

Exploiting Advanced Dimension Relationships

  • Storing dimension data in fact tables
    • Building a degenerate dimension
    • Configuring fact relationships
  • Saving space with referenced dimension relationships
    • Identifying candidates for referenced relationships
    • Utilizing the Dimension Usage tab to configure referenced relationships
  • Including dimensions with many-to-many relationships
    • Implementing intermediate measure groups and dimensions
    • Reporting on many-to-many dimensions without double counting

Designing Optimal Cubes

  • Assembling cube components
    • Selecting the appropriate fact tables
    • Adding cube dimensions
    • Distinguishing between additive, semiadditive and nonadditive measures
  • Designing storage and aggregations
    • Choosing between ROLAP, MOLAP and HOLAP
    • Partitioning cubes for improved performance
    • Designing aggregations with the Aggregation Design Wizard
    • Leveraging the Usage-Based Optimization Wizard
  • Automating processing
    • Exploiting XMLA scripts and SSIS
    • Refreshing cubes with Proactive Caching

Building and Modifying an OLAP Cube
• Designing a Unified Dimension Model (UDM)
• Identifying measures and their suitable granularities
• Adding new measure groups and creating custom measures
• Creating dimensions
• Implementing a Star and Snowflake Schema
• Managing Slow Changing Dimensions (SCD)
• Identifying role-play dimensions

Performing Advanced Analysis with MDX

  • Retrieving data with MDX
    • Defining tuples, sets and calculated members
    • Querying cubes with MDX
    • Navigating hierarchies with MDX and utilizing set functions
  • Monitoring business performance with KPIs
    • Building goal, status and trend expressions
    • Using PARALLELPERIOD to compare with past time periods
  • Creating calculations with MDX
    • Adding runtime calculations to the cube
    • Comparing MDX calculations with DSV calculated columns

Securing Cube Data

  • Securing data and simplifying the user interface
    • Distinguishing between perspective feature and security
    • Creating roles for administrative privileges
    • Securing dimension data
    • Implementing cell-level security

Gaining Business Advantage with Data Mining

  • Determining the correct model
    • Identifying business tasks for data mining
    • Training and testing data mining algorithms
    • Comparing algorithms with the accuracy chart and classification matrix
    • Optimizing returns with the Profit Chart
  • Performing real-world predictions
    • Classifying with the Decision Trees, Neural Network and Naive Bayes algorithms
    • Predicting with the Time Series algorithm
  • Deploying models
    • Predicting new cases with algorithms
    • Utilizing DMX to perform batch and singleton predictions
    • Exploring results with data mining viewers

 

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