What you'll learn:
- any students
- If you want to learn qlik view or qliksense
This Course cover some of the important topics that will be tested during Qlikview data architect certification.
About the certification exam:
This exam is based on QlikView Version 12.1, and has 60 questions to complete in 2 hours.
Passing the QlikView Data Architect Certification Exam grants you both the QlikView Data Architect (DA) and QlikView Business Analyst (BA) certifications.
Syllabus from Qlik for QlikView Data Architect
Gather and Interpret Requirements (8% of the exam)
Given a set of business objectives, determine KPIs, dimensions, or measures
Given customer requirements, determine an appropriate solution to meet the customer needs
Identify and Analyze Data Sources (18% of the exam)
Given a data set, identify quality issues
Determine the expected effects of data quality issues
Given a data set, determine how the data characteristics at the field level will affect the QlikView data model (e.g., performance, accuracy)
Interpret an entity relationship (ER) diagram
Given a data set, determine the relationships among data
Given a data set, determine how the relationships among data will affect the QlikView data model (e.g., performance, accuracy)
Create the QlikView Associative Data Model (39% of the exam)
Explain methods and considerations for connecting to different types of data sources
Describe the circumstances under which different load strategies should be used
Explain the circumstances under which QVD files and/or n-tiered data architectures should be recommended
Describe the use and properties of fact tables and dimension tables
Explain load techniques relevant to data transformation
Explain the use of QlikView functions to transform data
Explain how to resolve complex calendar scenarios
Explain the use and effects of different types of joins
Given business requirements, determine appropriate section access configuration
Given a scenario, determine how to resolve table association issues (e.g., synthetic keys/circular references, data types)
Explain the use of control statements and/or variables
Explain the purpose and functionality of the Table Viewer/System Fields
Determine the root cause for discrepancies between values in legacy reports and QlikView values
Explain the purpose and functionality of QlikView troubleshooting tools or functions
Given a script, determine the cause and/or solution for a script error
Design and Develop the QlikView Application User Interface (25% of the exam)
Determine the result of a given function or complex expression
Identify where alternate uses of expressions are appropriate
Given a scenario, determine the appropriate function or complex expression to use
Explain how to implement Actions/Triggers in the QlikView interface
Given a scenario, determine the appropriate object or chart type to use
Explain the purpose/functionality of common object properties
Given a scenario, determine the appropriate application performance tuning option to use
Given a scenario, determine the appropriate reload performance tuning option to use
Deliver the QlikView Application (10% of the exam)
Describe how to give the user information or direction for using the application
Explain the purpose and functionality of the QV Server and Publisher
Determine the circumstances under which particular client types can be used
Topics Covered in this course:
How to load data from excel file.
How to apply cross tab while loading data from excel file.
How to use of QlikView functions to transform data.
How to use common string function while loading data.
How to aggregate data using group by.
How to restrict your data by using where.
How to export your data from a internal table using Qlik scripts.
How to implement set analysis.
Upcoming modules:
Given a scenario, determine how to resolve table association issues (e.g., synthetic keys/circular references, data types)
Explain the use of control statements and/or variables
Explain the purpose and functionality of the Table Viewer/System Fields
About Set Analysis:
Set analysis offers a way of defining a set (or group) of data values that is different from the normal set defined by the current selections.
Normally, when you make a selection, aggregation functions, such as Sum, Max, Min, Avg, and Count aggregate over the selections that you have made: the current selections. Your selections automatically define the data set to aggregate over. With set analysis you can define a group that is independent of the current selections.
This can be useful if you want to show a particular value, for example, the market share of a product across all regions, irrespective of the current selections.
Set analysis is also powerful when making different sorts of comparisons, such as what are the best-selling products compared with poorly-selling products, or this year against last year.
