Developing SQL Data Models (#20768)
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- Learnfast is a Microsoft Silver Learning Partner. This is an authorised Microsoft Official Course (MOC).
The focus of this 3-day course is on creating managed enterprise BI solutions. It describes how to implement both multidimensional and tabular data models and how to create cubes, dimensions, measures, and measure groups. This course helps you prepare for the Exam 70-768.
Features & Benefits
- This is an authorised Microsoft Official Course (MOC).
- Attendees will learn practical skills which can be applied in the work environment.
- Even though Microsoft retired the certification exams for MCSA/E/D certifications, we will still provide you with a Microsoft Certificate of Completion of your course.
- Take full advantage of our new Hybrid Learning by attending on campus or virtually. Have all your classes ready to be downloaded and watched, anytime, anywhere. (Read More)
Outcomes & Objectives
After completing this course, learners will be able to:
- Describe the components, architecture, and nature of a BI solution
- Create a multidimensional database with Analysis Services
- Implement dimensions in a cube
- Implement measures and measure groups in a cube
- Use MDX syntax
- Customize a cube
- Implement a tabular database
- Use DAX to query a tabular model
- Use data mining for predictive analysis
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Pricing & Payment Options
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Duration
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3 Days (08:30 – 16:00) Classes are presented via our Hybrid Learning allowing learners the flexibility to attend on campus or in the comfort of their home or workplace.
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Course Prerequisites
Before attending this course, learners must have:
- Experience of querying data using Transact-SQL
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Who Should Attend
The primary audience for this course is database professionals who need to fulfill BI Developer role to create enterprise BI solutions.
Primary responsibilities will include:
- • Implementing multidimensional databases by using SQL Server Analysis Services
- • Creating tabular semantic data models for analysis by using SQL Server Analysis Services
Our
Delivery Methods
Our innovative "myWay” learning methodology is built around the students individual learning requirement, allowing each student to learn in a style that is most suitable for their skills set, knowledge and schedule.
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Instructor-Led Classes
Reach your full potential through our “myWay Instructor-Led” classes combined with interactive lessons, supporting video content, practical assignments and in field experience, done during the traditional 08:00 – 16:00 working day.
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Online Mentored Learning
Do a course at your pace via our “myWay Online Mentored Learning”, combining self-study with supported interactive online video lectures, an online course mentor, extra resources, questionnaires and more, all supported via out Online Student Portal.
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Part Time Mentored Learning
Designed for the working professional, our part time programmes provides you with the flexibility and benefit of our myWay Blended Learning with at home exercises/assignments and mentored or in-class lectures at a manageable schedule and pace.
Our Hybrid Delivery Methods
Our Hybrid Delivery Methods
myWay Hybrid Learning is a technology mediated delivery method that extends the benefit of flexibility and technology to all students. Each Hybrid delivery method is described in the section below.
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#AnywhereAnytime
Have all your classes ready to be downloaded and watched, anytime, anywhere.
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#NoStudentLeftBehind
Never miss a classs because of health, traffic, or transport issues.
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#Flexibility
A personalized class schedule, attend class on campus, virtually or both.
In Class or Virtual Class Based Learning
A technology mediated delivery method allowing campus based class or virtual class attendance, or a combination of both. Classes can be in the form of lecture based or mentored based.
Mentored Online Learning
A technology mediated, self paced online delivery method with personal mentorship.
Important Notes
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Learners to arrive at the training venue from 08:00 in preparation for 08:30 starting time
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Bookings are only confirmed upon receipt of the proof of payment or an official company purchase order.
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For full day, on campus courses, Learnfast will supply you with a computer to use for training (if applicable),& tea/coffee and a full lunch. Catering is not included for On-Site training and laptops are available for hire at an additional cost if required.
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Cancellation or rescheduling requests must be in writing and reach us via email at least 5-10 working days prior to the course commencement date. Full course fees will be retained for no shows.
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Virtual learners are required to have a stable internet connection & a working headset available for sound purposes.
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Learners who use their own laptops are fully responsible to ensure that administration rights, software installations, etc. are working sufficiently prior to training.
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Learnfast reserves the right to cancel or postpone dates if we require to do so and undertake to inform clients in writing and telephonically of these changes.
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Learnfast is not responsible for costs associated with cancellation of classes such as flight and accommodation for clients.
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Introduction to Business Intelligence
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The Microsoft business intelligence platform
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Introduction to Multidimensional Analysis
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Creating Data Sources and Data Source Views
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Creating a Cube
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Overview of Cube Security
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Configure SSAS
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Monitoring SSAS
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Configuring Dimensions
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Defining Attribute Hierarchies
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Sorting and Grouping Attributes
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Slowly Changing Dimensions
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Working with Measures
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Working with Measure Groups
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MDX fundamentals
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Adding Calculations to a Cube
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Using MDX to Query a Cube
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Introduction to Business Intelligence
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The Implementing Key Performance Indicators
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Implementing Actions
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Implementing Perspectives
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Implementing Translations
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Introduction to Tabular Data Models
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Creating a Tabular Data Model
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Using an Analysis Services Tabular Data Model in an Enterprise BI Solution
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DAX Fundamentals
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Using DAX to Create Calculated Columns and Measures in a Tabular Data Model
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Overview of Data Mining
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Creating a Custom Data Mining Solution
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Validating a Data Mining Model
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Connecting to and Consuming a Data-Mining Model
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Using the Data Mining add-in for Excel
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CampusStart DateEnd DateTypeBook Now
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15 July 202417 July 2024Full Time
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CampusStart DateEnd DateTypeBook Now
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15 July 202417 July 2024Correspondence
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19 August 202421 August 2024Correspondence
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09 September 202411 September 2024Correspondence
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14 October 202416 October 2024Correspondence
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11 November 202413 November 2024Correspondence
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CampusStart DateEnd DateTypeBook Now
-
15 July 202417 July 2024Full Time
-
19 August 202421 August 2024Full Time
-
09 September 202411 September 2024Full Time
-
14 October 202416 October 2024Full Time
-
11 November 202413 November 2024Full Time