The Data Strategy Course: Building a Data-driven Business
The Data Strategy Course: Building a Data-driven Business, available at $89.99, has an average rating of 4.58, with 78 lectures, based on 4535 reviews, and has 20284 subscribers.
You will learn about How to profit from a world of big data, analytics, and AI How to use data to improve business decisions Understand your customers and markets Provide more intelligent data-driven services Learn how to build more intelligent products Put your business in a position to be able to monetize its data Define relevant data use cases for your industry Learn how to source and collect data Understand the importance of data governance, ethics and trust Be able to turn data into insights Know how to collect, process, and store data Improve your data communication skills Build the necessary data competencies in your firm Execute your data strategy Ask clear Key Business Questions (KBQs) Be able to distinguish the fundamental types of data analysis techniques Learn how to design a KPI dashboard Gain an idea which are the most valuable skills for data scientists and data analysts Understand which data strategies fail Acquire a ‘use data for good’ perspective This course is ideal for individuals who are Data scientists or Data analysts or Business intelligence analysts or Business executives or Ambitious managers or Aspiring entrepreneurs or Financial analysts or Anyone who wants to understand how data can create value for their business It is particularly useful for Data scientists or Data analysts or Business intelligence analysts or Business executives or Ambitious managers or Aspiring entrepreneurs or Financial analysts or Anyone who wants to understand how data can create value for their business.
Enroll now: The Data Strategy Course: Building a Data-driven Business
Summary
Title: The Data Strategy Course: Building a Data-driven Business
Price: $89.99
Average Rating: 4.58
Number of Lectures: 78
Number of Published Lectures: 78
Number of Curriculum Items: 78
Number of Published Curriculum Objects: 78
Original Price: $199.99
Quality Status: approved
Status: Live
What You Will Learn
- How to profit from a world of big data, analytics, and AI
- How to use data to improve business decisions
- Understand your customers and markets
- Provide more intelligent data-driven services
- Learn how to build more intelligent products
- Put your business in a position to be able to monetize its data
- Define relevant data use cases for your industry
- Learn how to source and collect data
- Understand the importance of data governance, ethics and trust
- Be able to turn data into insights
- Know how to collect, process, and store data
- Improve your data communication skills
- Build the necessary data competencies in your firm
- Execute your data strategy
- Ask clear Key Business Questions (KBQs)
- Be able to distinguish the fundamental types of data analysis techniques
- Learn how to design a KPI dashboard
- Gain an idea which are the most valuable skills for data scientists and data analysts
- Understand which data strategies fail
- Acquire a ‘use data for good’ perspective
Who Should Attend
- Data scientists
- Data analysts
- Business intelligence analysts
- Business executives
- Ambitious managers
- Aspiring entrepreneurs
- Financial analysts
- Anyone who wants to understand how data can create value for their business
Target Audiences
- Data scientists
- Data analysts
- Business intelligence analysts
- Business executives
- Ambitious managers
- Aspiring entrepreneurs
- Financial analysts
- Anyone who wants to understand how data can create value for their business
Are you interested in learning how data can help a business thrive and prosper in 2021?
Do you want to be able to leverage the value of your business data?
If so, then this is the perfect course for you!
The hype around data science, analytics and business intelligence is at its peak. Almost all companies are aware that data can help them improve their performance in some way, shape, or form. However, the majority of business executives commit the same crucial mistake:
“Tactics without strategy is the noise before defeat’’
Sun Tzu, Chinese military strategist
Collecting and analysing data for the sake of working with numbers is far from optimal.
Data is only as valuable as the insights you will obtain from it.
So, to position your business for success in today’s data-driven world, you have to start by reflecting on several key questions.
What are the key decisions your company will make that can be improved with the right data?
How is data going to help your firm improve and automate business processes?
In what way can data make your products or services better?
To what extent is your business’s data valuable to external parties who might be willing to pay for it?
It is much better to try and answer such fundamental questions first, rather than focusing extensively on data analysis techniques and data storage infrastructure requirements before you have defined a roadmap of how data will help your business in the long run.
A smart business executive focuses on data strategy first.
In this course, we will cover several important topics that will prove to be invaluable if you are:
– a business owner,
– a business executive
– an aspiring data practitioner.
We will provide context and help you understand why data is one of the most important for any business today. We’ll talk about hundreds of ways companies have benefited from a well-structured data strategy in real life. By the end of the course you will be able to recognize data-related opportunities in your own organization.
The course starts by focusing on the main ways in which data can help a business:
– use data to improve business decisions.
– use data to understand your customers and markets
– use data to provide more intelligent products and services
– use data to improve your business processes.
– use data to generate a meaningful revenue stream
We’ll discuss how companies have benefited from data in each of these scenarios and the practical implications you need to bear in mind before embarking on your data projects.
Then, in the next section of the course, we will do one of my favorite exercises that I do when working with and consulting for my clients. I will show you how to define your data use cases. We will brainstorm the data opportunities for your business and identify possible data use cases, ensuring a clear link to your strategic business goals. We will take this process as an opportunity to review your existing strategy to ensure it is still relevant in today’s business world. We will then make sure you don’t fall into the trap of identifying too many use cases – it is not about finding as many as you can, rather than the most important ones.
Then the course continues by focusing on sourcing and collecting data. An important topic that involves several key considerations. We will distinguish between structured and unstructured data, internal and external data, and so on. By the end of this section, you will have an idea how a company should approach data collection, and understand the different sources of data that could be used besides internal data.
This is a truly comprehensive course. We’ve also included sections on:
– Data governance, ethics, and trust
– How to turn data into insights (a brief description of the various techniques that can be used to analyze data)
– How to create the appropriate technology and data infrastructure in your company
– How to build the necessary data competencies in your organization
– How to execute and revisit your data strategy
I’m very excited that you are interested in this subject because I believe that this is one of the most fascinating aspects of today’s business world. Innovation through the use of data and data analysis is something I am very passionate about. I’ll be happy if you start or advance your data analysis journey with the Data Strategy course and I hope I will see you inside the course!
Bernard Marr
Course Curriculum
Chapter 1: Welcome to the course!
Lecture 1: Welcome to the course!
Chapter 2: Deciding your strategic data needs
Lecture 1: Delineating the 5 strategic data use case areas
Chapter 3: Using data to improve your decisions
Lecture 1: Section Introduction
Lecture 2: Curated dashboards vs. self-service data exploration
Lecture 3: Challenges related to self-service data exploration
Lecture 4: Asking key business questions first (KBQs)
Lecture 5: The power of clear Key Business Questions (KBQs)
Lecture 6: How to ask the right Key Business Questions
Lecture 7: Giving people access to data
Lecture 8: Curating the most important data insights
Chapter 4: Using data to understand your customers and markets
Lecture 1: Secton intro
Lecture 2: How this butcher uses data to understand customers
Lecture 3: Netflix use case – vs Disney – this is why Disney launched Disney +
Lecture 4: Amazon use case
Lecture 5: The increasing need for real-time data to understand customers and markets
Chapter 5: Using data to provide more intelligent services
Lecture 1: Using data to provide more intelligent services
Chapter 6: Using data to make more intelligent products
Lecture 1: Using data to make more intelligent products
Chapter 7: Using data to improve your business processes
Lecture 1: Using data to improve your business processes
Chapter 8: Monetising your data
Lecture 1: Monetising your data – intro
Lecture 2: The Shotspotter case study
Chapter 9: Defining your data use cases
Lecture 1: Defining data use cases walk through (part 1)
Lecture 2: Defining data use cases walk through (part 2)
Lecture 3: Defining data use cases walk through (part 3)
Chapter 10: Sourcing and collecting the data
Lecture 1: Secton intro
Lecture 2: Structured vs unstructured data
Lecture 3: Internal vs external data
Lecture 4: Different types of data
Lecture 5: Meta data
Lecture 6: The importance of realtime data
Lecture 7: Gathering internal data
Lecture 8: Accessing external data
Lecture 9: Sources of external data
Lecture 10: When the data you want doesn't exist
Chapter 11: Data governance
Lecture 1: Section intro
Lecture 2: To own or not to own
Lecture 3: Ensuring the correct rights are in place
Lecture 4: Case study on building trust
Chapter 12: Turning data into insights
Lecture 1: Section intro
Lecture 2: Text analytics
Lecture 3: Sentiment analytics
Lecture 4: Image analytics
Lecture 5: Video analytics
Lecture 6: Voice analytics
Lecture 7: Data mining
Lecture 8: Business experiments
Lecture 9: Visual analytics
Lecture 10: Time series analysis
Lecture 11: Monte carlo simulation
Lecture 12: Linear programming
Lecture 13: Cohort analysis
Lecture 14: Factor analysis
Lecture 15: Neural network analysis
Lecture 16: Deep learning
Lecture 17: Reinforcement learning
Chapter 13: Creating the technology and data infrastructure
Lecture 1: Section intro
Lecture 2: How to collect data
Lecture 3: Database, Data warehouse, Data mart and Data lake
Lecture 4: How to store data
Lecture 5: How to process data
Lecture 6: Communicating data
Lecture 7: What is а KPI dashboard
Lecture 8: How to design a KPI Dashboard
Lecture 9: Reporting lessons from journalists
Lecture 10: Using KPI dashboard software
Lecture 11: Big data as a service
Chapter 14: Building the data competencies in your organisation
Lecture 1: Section intro
Lecture 2: Skills shortage
Lecture 3: The skills needed for a data scientist
Lecture 4: Building internal skills and competencies
Lecture 5: Outsourcing your data analysis
Lecture 6: Leadership challenges
Chapter 15: Executing and revisiting your strategy
Lecture 1: Putting the data strategy into action
Lecture 2: Why data strategies fail
Lecture 3: Creating a data culture
Lecture 4: Revisiting the data strategy
Lecture 5: A changing business environment
Lecture 6: Changing technology landscape
Chapter 16: Looking ahead
Lecture 1: Using data for good
Instructors
-
365 Careers
Creating opportunities for Data Science and Finance students -
Bernard Marr
Bestselling Author, Futurist, Strategic Advisor
Rating Distribution
- 1 stars: 25 votes
- 2 stars: 39 votes
- 3 stars: 392 votes
- 4 stars: 1587 votes
- 5 stars: 2494 votes
Frequently Asked Questions
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Can I take my courses with me wherever I go?
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