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David Schieber

This course will walk you through acquiring data to use within MicroStrategy for analysis. It covers use of the MicroStrategy object model, external data, and ways of storing that data for easier analysis.

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This course will walk you through acquiring data to use within MicroStrategy for analysis. It covers use of the MicroStrategy object model, external data, and ways of storing that data for easier analysis.

The need for data-driven decisions is ever-growing in today's tech business world. In this course, Collecting and Preparing Data for MicroStrategy, you will gain the ability to acquire data for use within MicroStrategy for analysis. First, you will learn how to work with the MicroStrategy object model. Next, you will discover the process for bringing in external unmodeled data. Finally, you will explore how to get that data in a format that supports your ability to analyze it. When you are finished with this course, you will have the skills and knowledge of MicroStrategy data acquisition needed to begin building your own reporting.

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What's inside

Syllabus

Course Overview
Working with the MicroStrategy Object Model
Importing Data into MicroStrategy Web and Desktop
Enabling Fast Analysis with Large Datasets via Intelligent Cubes
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Referencing Real-time Data with Live Connect

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Covers acquiring data for MicroStrategy analysis, which is key to data-driven decision-making in business
Helps learners gain hands-on experience with the MicroStrategy object model, enabling them to navigate and utilize it effectively
Explores external data integration, providing learners with strategies to seamlessly incorporate external data sources
Discusses data storage techniques for analysis optimization, equipping learners with practical approaches to enhance data accessibility and usability
Suitable for individuals seeking to enhance their data acquisition and analysis skills within the MicroStrategy ecosystem

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Collecting and Preparing Data for MicroStrategy with these activities:
Review data modeling concepts in MicroStrategy
Strengthen foundational knowledge of data modeling to enhance data acquisition understanding.
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  • Review MicroStrategy documentation or online resources on data modeling.
  • Create a simple data model in MicroStrategy.
  • Discuss data modeling concepts with peers or instructors.
Follow MicroStrategy documentation tutorials
Practice applying MicroStrategy data acquisition techniques in a guided environment.
Browse courses on MicroStrategy
Show steps
  • Identify MicroStrategy documentation tutorials on data acquisition.
  • Complete selected tutorials, following instructions thoroughly.
  • Practice implementing acquired techniques in MicroStrategy.
Import external data into MicroStrategy exercises
Reinforce understanding of data importation techniques through repetitive exercises.
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  • Gather sample external data files.
  • Set up MicroStrategy project and environment.
  • Import data using MicroStrategy Import Wizard or SDK.
  • Validate and verify data accuracy and integrity.
Three other activities
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Participate in MicroStrategy data acquisition study group
Engage with peers to share experiences, clarify concepts, and enhance understanding.
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  • Find or create a study group with peers.
  • Discuss data acquisition challenges and solutions.
  • Work together on data acquisition projects.
  • Provide constructive feedback to peers.
Attend a MicroStrategy data acquisition workshop
Gain in-depth knowledge and hands-on experience from industry experts.
Browse courses on Data Acquisition
Show steps
  • Identify and register for relevant MicroStrategy data acquisition workshops.
  • Attend the workshop and actively participate.
  • Apply acquired knowledge and techniques in practical projects.
Build a MicroStrategy data acquisition dashboard
Apply data acquisition skills to create a practical tool for data exploration and analysis.
Browse courses on Data Acquisition
Show steps
  • Define dashboard purpose and metrics.
  • Acquire and prepare relevant data using MicroStrategy techniques.
  • Build dashboards with visualizations and interactive features.
  • Test and refine dashboard based on user feedback.

Career center

Learners who complete Collecting and Preparing Data for MicroStrategy will develop knowledge and skills that may be useful to these careers:
Data Analyst
A Data Analyst is someone who translates raw data into meaningful information. They are responsible for collecting, cleaning, and analyzing data to identify trends and patterns. This course will help you develop the skills needed to be a successful Data Analyst, including how to work with the MicroStrategy object model, import data into MicroStrategy, and enable fast analysis with large datasets. With the skills you learn in this course, you will be able to build your own reports and make data-driven decisions.
Business Analyst
A Business Analyst is someone who helps businesses understand their data and make better decisions. They work with stakeholders to identify business needs and then develop solutions that meet those needs. This course will help you develop the skills needed to be a successful Business Analyst, including how to work with the MicroStrategy object model, import data into MicroStrategy, and enable fast analysis with large datasets. With the skills you learn in this course, you will be able to help businesses make better use of their data.
Data Scientist
A Data Scientist is someone who uses data to solve business problems. They work with data to build models that can predict future outcomes and identify trends. This course will help you develop the skills needed to be a successful Data Scientist, including how to work with the MicroStrategy object model, import data into MicroStrategy, and enable fast analysis with large datasets. With the skills you learn in this course, you will be able to build your own models and use data to solve business problems.
Data Engineer
A Data Engineer is someone who designs, builds, and maintains data pipelines. They work with data to ensure that it is clean, accurate, and consistent. This course will help you develop the skills needed to be a successful Data Engineer, including how to work with the MicroStrategy object model, import data into MicroStrategy, and enable fast analysis with large datasets. With the skills you learn in this course, you will be able to build your own data pipelines and ensure that your data is ready for analysis.
Database Administrator
A Database Administrator is someone who manages and maintains databases. They work with data to ensure that it is secure, reliable, and available. This course will help you develop the skills needed to be a successful Database Administrator, including how to work with the MicroStrategy object model, import data into MicroStrategy, and enable fast analysis with large datasets. With the skills you learn in this course, you will be able to manage your own databases and ensure that your data is safe and secure.
Software Engineer
A Software Engineer is someone who designs, develops, and maintains software applications. They work with data to build applications that meet the needs of users. This course may be useful for someone who wants to become a Software Engineer, as it will help you develop the skills needed to work with data and build software applications.
IT Manager
An IT Manager is someone who manages and oversees an organization's IT systems. They work with data to ensure that it is secure, reliable, and available. This course may be useful for someone who wants to become an IT Manager, as it will help you develop the skills needed to work with data and manage IT systems.
Project Manager
A Project Manager is someone who plans, executes, and closes projects. They work with data to track progress and ensure that projects are completed on time and within budget. This course may be useful for someone who wants to become a Project Manager, as it will help you develop the skills needed to work with data and manage projects.
Product Manager
A Product Manager is someone who manages and oversees the development of products. They work with data to understand customer needs and develop products that meet those needs. This course may be useful for someone who wants to become a Product Manager, as it will help you develop the skills needed to work with data and develop products.
Sales Manager
A Sales Manager is someone who manages and oversees a sales team. They work with data to track sales performance and identify opportunities for growth. This course may be useful for someone who wants to become a Sales Manager, as it will help you develop the skills needed to work with data and manage a sales team.
Marketing Manager
A Marketing Manager is someone who plans and executes marketing campaigns. They work with data to track campaign performance and identify opportunities for improvement. This course may be useful for someone who wants to become a Marketing Manager, as it will help you develop the skills needed to work with data and manage marketing campaigns.
Financial Analyst
A Financial Analyst is someone who analyzes financial data to make investment recommendations. They work with data to identify trends and patterns and make recommendations that can help investors make better decisions. This course may be useful for someone who wants to become a Financial Analyst, as it will help you develop the skills needed to work with data and make investment recommendations.
Operations Manager
An Operations Manager is someone who plans and executes operational plans. They work with data to track progress and ensure that operations are efficient and effective. This course may be useful for someone who wants to become an Operations Manager, as it will help you develop the skills needed to work with data and manage operations.
Human Resources Manager
A Human Resources Manager is someone who manages and oversees an organization's human resources. They work with data to track employee performance and identify opportunities for improvement. This course may be useful for someone who wants to become a Human Resources Manager, as it will help you develop the skills needed to work with data and manage human resources.

Reading list

We've selected ten books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Collecting and Preparing Data for MicroStrategy.
Provides a comprehensive foundation in data warehousing concepts, emphasizing their role in business intelligence. By understanding data warehousing principles, learners can better grasp the data acquisition and preparation techniques taught in the course.
Explores the challenges and best practices of building scalable data warehouses with big data technologies. It offers insights into data integration, storage, and processing, enhancing the course's focus on data acquisition and management.
Serves as a foundational resource for understanding dimensional modeling, a key concept in data warehousing. By mastering dimensional modeling principles, learners can enhance their data preparation techniques covered in the course.
Explores the use of cloud computing platforms for data analysis. It covers topics like data storage, processing, and visualization in the cloud, complementing the course's focus on data preparation and management.
Introduces the fundamental concepts and applications of data science in a business context. It provides insights into data mining, predictive modeling, and data visualization, expanding the knowledge gained in the course.
Serves as a practical guide to data analysis using Python. It teaches data manipulation, exploration, and visualization techniques, complementing the course's focus on data preparation and analysis.
Provides a comprehensive introduction to statistical learning methods, including data mining, inference, and prediction. It offers a deeper understanding of statistical techniques used in data analysis, complementing the course's focus on practical applications.
Delves into the Hadoop ecosystem, covering topics like data storage, processing, and analysis. It provides foundational knowledge for learners interested in exploring big data technologies beyond the scope of the course.
Offers a comprehensive overview of data mining techniques, including data preprocessing, classification, clustering, and association rule mining. It provides a deeper understanding of data analysis methods, complementing the course's focus on practical applications.
Provides a comprehensive introduction to deep learning, covering topics like neural networks, convolutional neural networks, and recurrent neural networks. It offers a deeper understanding of advanced machine learning techniques, complementing the course's focus on practical applications.

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