The Qlik Sense Data Architect exam is a rigorous, proctored exam that tests the knowledge and skills of data architects in a variety of areas, including data modeling, data architecture, data integration, and data transformation. The exam is designed to be challenging and comprehensive, covering a wide range of topics and requiring candidates to demonstrate proficiency in both theoretical and practical aspects of Qlik Sense data modeling.
To pass the exam, candidates must have a deep understanding of data modeling concepts and techniques, including the use of Qlik Sense data modeling tools, data architecture principles, and best practices for data integration and transformation. They must also be able to design and implement effective data models that meet the needs of their organization and stakeholders while ensuring the accuracy, completeness, and integrity of their data.
While the Qlik Sense Data Architect exam is challenging, it is also highly respected in the industry and can be a valuable asset for professionals looking to advance their careers in data architecture or data analytics. With careful preparation and a solid understanding of the exam content, candidates can increase their chances of success and earn this prestigious certification. In this blog, we will provide insights and tips to help you prepare for and pass the Qlik Sense Data Architect exam, including strategies for studying, practicing, and mastering the key concepts and skills required for success.
Qlik Sense Data Architecture Glossary
Here are some common terms related to Qlik Sense data architecture:
- Data model: A data model is a logical representation of the data in Qlik Sense. It describes how data tables are related to each other and how they should be structured to enable efficient data analysis.
- Dimension: A dimension is a category or grouping that can be used to slice and dice data in Qlik Sense. Examples include time, product, geography, and customer.
- Measure: A measure is a numerical value that can be aggregated or calculated to provide insight into data. Examples include sales revenue, profit margin, and customer count.
- Field: A field is a column in a data table that contains data values. Fields can be dimensions or measures.
- Data load script: The data load script is a set of instructions that Qlik Sense uses to extract data from a source system, transform it, and load it into memory for analysis.
- Data source: A data source is a system or file that contains data that can be accessed by Qlik Sense. Examples include databases, spreadsheets, and text files.
- Data connection: A data connection is a configuration that allows Qlik Sense to connect to a data source and extract data.
- Extract, Transform, Load (ETL): ETL is a process used to extract data from source systems, transform it to meet analysis requirements, and load it into a data warehouse or other target system.
- In-memory data store: Qlik Sense stores data in memory to enable fast data analysis. The in-memory data store is a high-performance data structure that allows data to be accessed and analyzed quickly.
- Data model viewer: The data model viewer is a tool in Qlik Sense that displays the relationships between tables in a data model.
- Data island: A data island is a table in Qlik Sense that is not related to any other table in the data model. Data islands can be used to store small amounts of data that are not related to the main data model.
- Synthetic key: A synthetic key is a key that is automatically generated by Qlik Sense when two or more tables have multiple fields in common. Synthetic keys can make data modeling more complex and can be avoided by creating explicit keys.
- Star schema: A star schema is a type of data model that uses a central fact table to store measures and related dimension tables to provide context for the measures.
- Snowflake schema: A snowflake schema is a type of data model that extends the star schema by normalizing dimension tables into multiple related tables.
- Slowly Changing Dimension (SCD): Slowly Changing Dimensions refer to dimensions that change slowly over time, and there are different strategies to manage these changes, from Type 0 (no changes are stored) to Type 3 (only some historical changes are stored).
What makes the Qlik Sense Data Architect exam hard?
The Qlik Sense Data Architect exam assesses a candidate’s proficiency in designing and building data models in Qlik Sense, as well as their ability to optimize data models for performance and scalability. Here are some factors that could make the exam difficult:
- Technical complexity: Qlik Sense is a powerful tool with many features and capabilities. The exam may cover advanced topics such as data modeling, scripting, data transformation, data security, and data governance, which can be challenging to master.
- Practical application: The exam may test a candidate’s ability to apply their knowledge in real-world scenarios. This requires not only a deep understanding of the Qlik Sense platform but also the ability to solve problems and make informed decisions based on business requirements.
- Time pressure: The exam may have a time limit, which can be challenging for some candidates who need more time to think through complex problems and complete tasks. Managing time effectively is a key skill in any technical exam.
- Lack of hands-on experience: Candidates who have not worked extensively with Qlik Sense may find it difficult to apply their knowledge in the exam. Practical experience with the tool is essential for success.
Overall, the Qlik Sense Data Architect exam is designed to evaluate a candidate’s technical skills and knowledge of the platform. To succeed, candidates need to be familiar with the tool, have practical experience, and be able to apply their knowledge to solve real-world problems under time pressure.
Qlik Sense Data Architect Syllabus
The Qlik Sense Data Architect Certification Examination covers the following topics:
Identify Requirements for Data Models (16%)
• Firstly, Identify the data load and refresh requirements (e.g., tiered architecture, multiple data sources, varying refresh times) and Given a scenario, identify Qlik Sense features to meet customer needs (e.g., associative data model, master items, ODAG, GeoAnalytics). Outline steps to implement security requirements
Design Data Models (28%)
• Firstly, Determine an appropriate data model design to meet customer needs
• Secondly, Decide on an appropriate data model that prioritizes reuse, scalability, and efficiency (e.g., tiered architecture, data governance. Determine how to manage complex scenarios (e.g., calendar, set analysis, flags, functions)
Domain 3: Build Data Models (34%)
• Given a scenario, use data transformation techniques with both data load editor and data manager. Manage security using section access and Use the Qlik Converter to migrate QlikView documents to Qlik Sense applications
Domain 4: Validate Data (22%)
- Validate data models against source information using Qlik Sense visualizations. Resolve data modeling issues (e.g., synthetic keys, circular references, scripting errors, debugging) and Resolve data issues (e.g., null values, data formatting)
How difficult is Qlik Sense Data Architect Exam?
To begin with, nothing comes easy, however, nothing is impossible. Therefore when it comes to the Qlik Sense Data Architect examination, all you need is the right resources and a guide to practice. With the right study material and your efforts, you are able to crack this examination. There are rumors and other assumptions that this examination might be difficult. The reason behind this is people are afraid of making efforts and work hard. But we have sorted all the things for you, let’s get started with Qlik Sense Data Architect Certification Cheat Sheet
Qlik community
Qlik Community is the online forum of people who have passed the examinations of Qlik. They share their experience with the exam and preparation. Furthermore, you can ask your doubts from the people available in that community, connect with them and take their help in clearing conceptual portions of the syllabus. You can even follow their strategy of studying if you are unable to study properly. So, do not hesitate in asking them. This can really help you as who can tell better than an experienced person.
Official Website
Make sure to visit the official site and gather all the relevant information about the exam. The official site has its guide for the exam and study material like online classes and instructor-led Qlik Sense Data Architect training courses available. You can go for those materials if you think that will be helpful to you.
Evaluate with Practice Test
When you are done with all your Qlik Sense Data Architect Certification Preparation it is always advisable to go for some mock test before you plan to sit for the actual examination. This will not only boost your confidence but will also make you aware of the weak portions in your preparation and which require some more focus and hard work. Taking real-time Qlik Sense Data Architect Practice Questions will also release you from exam fear and exam pressure. Start your learning with Qlik Sense Data Architect Exam Questions now!
