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Simon Allardice

We all work with data — but often don’t consider the big picture around it. In this fast-paced, practical introduction, quickly get up to speed on multiple ideas, tools and technologies around “data” in the business world today.

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We all work with data — but often don’t consider the big picture around it. In this fast-paced, practical introduction, quickly get up to speed on multiple ideas, tools and technologies around “data” in the business world today.

These days, every business role needs to understand the core ideas, tools and technologies their organizations rely on. This course, Data: Executive Briefing, is a fast-paced, practical, and pragmatic introduction to multiple ways to work with (and think about) data. First, we’ll quickly see how “data” differs from other terms like “information”, “knowledge” — or even “wisdom”. Next, we’ll get clear on the most important jargon and terminology, including “Big Data”, data silos and data warehouses, working with structured and unstructured data, and more. When you’re finished with this course, you’ll recognize the various — and sometimes unpredictable — ways that data can add value to your product, team, or organization.

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Syllabus

Data: Executive Briefing

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Offers a fast-paced and practical introduction to data-centric concepts, tools, and technologies
Delves into various facets of data, including 'Big Data,' data silos, and data warehouses
Explores the distinction between 'data' and related terms like 'information' and 'knowledge.'
Provides insights into how data can add value across different business contexts
Applies to any business role requiring an understanding of data-related concepts and tools

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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 Data: Executive Briefing with these activities:
Review basic statistics and probability concepts
Strengthen your foundation in statistics and probability to enhance your understanding of data analysis and interpretation.
Browse courses on Statistics
Show steps
  • Review lecture notes or textbooks on basic statistics and probability.
  • Complete practice problems to reinforce your understanding.
Identify potential mentors in the field of data analytics
Seek guidance and support from experienced professionals to accelerate your learning and gain valuable industry insights.
Show steps
  • Attend industry events and conferences to network with data analytics professionals.
  • Reach out to individuals on LinkedIn or other professional networking platforms.
  • Inquire about their willingness to provide mentorship or guidance.
Review 'Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today's Businesses' by Michael Minelli, Michelle Chambers, and Ambiga Dhiraj
Equip yourself with the concepts and frameworks presented in this book to strengthen your understanding of data and analytics in business.
Show steps
  • Read the book thoroughly, taking notes and highlighting key points.
  • Summarize each chapter, capturing the main ideas and their relevance to the course.
  • Identify and explain the key terms and concepts introduced in the book.
Five other activities
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Complete online exercises on data analysis and visualization
Enhance your data analysis and visualization skills through hands-on exercises, reinforcing the concepts covered in the course.
Browse courses on Data Analysis
Show steps
  • Identify and access online platforms or resources offering data analysis and visualization exercises.
  • Select exercises that align with the concepts covered in the course.
  • Complete the exercises, following the instructions and applying the techniques learned.
  • Review your results and identify areas for improvement.
Create a data dictionary for a specific business scenario
Develop a structured and comprehensive data dictionary to enhance your understanding of data organization and management.
Show steps
  • Identify and define the business scenario and its data requirements.
  • Gather and analyze data from various sources to determine data elements.
  • Create a data dictionary template and populate it with data elements and definitions.
  • Validate and finalize the data dictionary for use in the business scenario.
Compile a list of resources on data governance and best practices
Expand your knowledge of data governance and best practices by gathering resources that provide valuable insights and guidance.
Browse courses on Data Governance
Show steps
  • Conduct online research to identify articles, white papers, and industry reports on data governance.
  • Review the resources and select those that align with the course topics.
  • Organize and compile the resources into a comprehensive document or online repository.
Follow tutorials on advanced data manipulation techniques
Expand your data manipulation skills by exploring advanced techniques through guided tutorials, enhancing your proficiency in data preparation and transformation.
Browse courses on Data Manipulation
Show steps
  • Identify online tutorials or resources that focus on advanced data manipulation techniques.
  • Select tutorials that align with your learning objectives and skill level.
  • Follow the tutorials step-by-step, implementing the techniques in a hands-on environment.
  • Practice applying the techniques to your own datasets.
Develop a data-driven presentation for a business stakeholder
Showcase your ability to effectively communicate data insights to non-technical stakeholders, demonstrating your understanding of data-driven decision-making.
Browse courses on Data Presentation
Show steps
  • Identify a specific business scenario and collect relevant data.
  • Analyze the data and identify key insights and trends.
  • Create a presentation that visually represents the data and highlights the insights.
  • Practice delivering the presentation to an audience.

Career center

Learners who complete Data: Executive Briefing will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists use a variety of statistical techniques and predictive models to turn raw data into useful insights that drive better decision-making. This course will help build a foundation for using these techniques such as regression analysis, clustering, and neural networks, while contextualizing these methods in a business setting.
Business Intelligence Analyst
Business Intelligence Analysts interpret data to identify trends and patterns that can help businesses make better decisions. This course will provide a strong foundation in the core concepts of data warehousing, data mining, and data visualization, giving you the skills you need to succeed in this role.
Data Analyst
Data Analysts collect, clean, and analyze data to help businesses make informed decisions. This course will provide you with a foundation in data analysis techniques, including data mining, statistical analysis, and data visualization, helping you develop the skills you need to succeed as a Data Analyst.
Product Manager
Product Managers are responsible for the development and launch of new products and services. This course will provide you with the knowledge you need to understand the data that drives product development, helping you make better decisions about what products to build and how to market them.
Marketing Analyst
Marketing Analysts use data to understand customer behavior and develop effective marketing campaigns. This course will provide you with the skills you need to collect, analyze, and interpret data, helping you make better decisions about how to reach your target audience.
Financial Analyst
Financial Analysts use data to make recommendations about investments and financial decisions. This course will provide you with the skills you need to collect, analyze, and interpret financial data, helping you make better decisions about how to invest your money.
Operations Research Analyst
Operations Research Analysts use data to improve the efficiency and effectiveness of business operations. This course will provide you with the skills you need to collect, analyze, and interpret data, helping you make better decisions about how to streamline your operations.
Actuary
Actuaries use data to assess risk and uncertainty. This course will provide you with the skills you need to collect, analyze, and interpret data, helping you make better decisions about how to manage risk.
Market Researcher
Market Researchers use data to understand customer behavior and develop new products and services. This course will provide you with the skills you need to collect, analyze, and interpret data, helping you make better decisions about how to reach your target audience.
Statistician
Statisticians use data to solve problems and make decisions. This course will provide you with the skills you need to collect, analyze, and interpret data, helping you make better decisions about how to solve problems in your field.
Database Administrator
Database Administrators are responsible for the day-to-day operation and maintenance of databases. This course will provide you with the skills you need to install, configure, and manage database systems, helping you ensure that your organization's data is secure and accessible.
Data Engineer
Data Engineers are responsible for building and maintaining the data infrastructure that supports data-driven decision-making. This course will provide you with the skills you need to design, build, and manage data pipelines, helping you ensure that your organization has the data it needs to succeed.
Software Engineer
Software Engineers are responsible for designing, developing, and maintaining software applications. While this course does not teach software development, it will provide you with a strong foundation in the core concepts of data management, which is essential for building data-driven applications.
Information Systems Manager
Information Systems Managers are responsible for planning, implementing, and managing information systems. This course may be useful for Information Systems Managers who want to develop a stronger understanding of the data that drives their organization's decision-making.
Business Analyst
Business Analysts help organizations identify and solve business problems. This course may be useful for Business Analysts who want to develop a stronger understanding of the data that drives their organization's decision-making.

Reading list

We've selected 11 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 Data: Executive Briefing.
Provides a comprehensive guide to data mining, which is the process of extracting knowledge from data. It covers the basics of data mining, as well as advanced topics such as machine learning and data visualization.
Provides a comprehensive guide to big data analytics, which is the process of analyzing large datasets to identify patterns and trends. It covers the basics of big data analytics, as well as practical examples of how big data analytics can be used to solve real-world problems.
Provides a comprehensive introduction to data science and its applications in business. It covers the basics of data mining, data analysis, and machine learning, and provides practical examples of how these techniques can be used to solve business problems.
Provides a practical guide to deep learning for coders. It covers the basics of deep learning, as well as practical examples of how deep learning can be used to solve real-world problems.
Provides a comprehensive introduction to reinforcement learning, which type of machine learning that allows computers to learn by trial and error. It covers the basics of reinforcement learning, as well as advanced topics such as deep reinforcement learning.
Provides a practical guide to using data to improve marketing performance. It covers the key metrics that marketers need to track, and provides guidance on how to use these metrics to make better decisions.
Comprehensive guide to Hadoop, which distributed computing platform that is used for processing large datasets. It covers the basics of Hadoop, as well as advanced topics such as data security and performance tuning.
Provides a gentle introduction to machine learning, which type of artificial intelligence that allows computers to learn from data. It covers the basics of machine learning, as well as practical examples of how machine learning can be used to solve real-world problems.
Provides a hands-on introduction to data science using Python. It covers the basics of data science, as well as practical examples of how data science can be used to solve real-world problems.

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