The Data Strategy Course: Building A Data-Driven Business

A Practical Guide to Intelligent Business Performance: Learn How to Position Your Business for Success Leveraging Data

What you'll 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

Requirements

No prior experience is required. We will start from the very basics

Description

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 strategistCollecting 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 streamWe’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 strategyI’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

Overview

Section 1: Welcome to the course!

Lecture 1 Welcome to the course!

Section 2: Deciding your strategic data needs

Lecture 2 Delineating the 5 strategic data use case areas

Section 3: Using data to improve your decisions

Lecture 3 Section Introduction

Lecture 4 Curated dashboards vs. self-service data exploration

Lecture 5 Challenges related to self-service data exploration

Lecture 6 Asking key business questions first (KBQs)

Lecture 7 The power of clear Key Business Questions (KBQs)

Lecture 8 How to ask the right Key Business Questions

Lecture 9 Giving people access to data

Lecture 10 Curating the most important data insights

Section 4: Using data to understand your customers and markets

Lecture 11 Secton intro

Lecture 12 How this butcher uses data to understand customers

Lecture 13 Netflix use case - vs Disney - this is why Disney launched Disney +

Lecture 14 Amazon use case

Lecture 15 The increasing need for real-time data to understand customers and markets

Section 5: Using data to provide more intelligent services

Lecture 16 Using data to provide more intelligent services

Section 6: Using data to make more intelligent products

Lecture 17 Using data to make more intelligent products

Section 7: Using data to improve your business processes

Lecture 18 Using data to improve your business processes

Section 8: Monetising your data

Lecture 19 Monetising your data - intro

Lecture 20 The Shotspotter case study

Section 9: Defining your data use cases

Lecture 21 Defining data use cases walk through (part 1)

Lecture 22 Defining data use cases walk through (part 2)

Lecture 23 Defining data use cases walk through (part 3)

Section 10: Sourcing and collecting the data

Lecture 24 Secton intro

Lecture 25 Structured vs unstructured data

Lecture 26 Internal vs external data

Lecture 27 Different types of data

Lecture 28 Meta data

Lecture 29 The importance of realtime data

Lecture 30 Gathering internal data

Lecture 31 Accessing external data

Lecture 32 Sources of external data

Lecture 33 When the data you want doesn't exist

Section 11: Data governance

Lecture 34 Section intro

Lecture 35 To own or not to own

Lecture 36 Ensuring the correct rights are in place

Lecture 37 Case study on building trust

Section 12: Turning data into insights

Lecture 38 Section intro

Lecture 39 Text analytics

Lecture 40 Sentiment analytics

Lecture 41 Image analytics

Lecture 42 Video analytics

Lecture 43 Voice analytics

Lecture 44 Data mining

Lecture 45 Business experiments

Lecture 46 Visual analytics

Lecture 47 Time series analysis

Lecture 48 Monte carlo simulation

Lecture 49 Linear programming

Lecture 50 Cohort analysis

Lecture 51 Factor analysis

Lecture 52 Neural network analysis

Lecture 53 Deep learning

Lecture 54 Reinforcement learning

Section 13: Creating the technology and data infrastructure

Lecture 55 Section intro

Lecture 56 How to collect data

Lecture 57 Database, Data warehouse, Data mart and Data lake

Lecture 58 How to store data

Lecture 59 How to process data

Lecture 60 Communicating data

Lecture 61 What is а KPI dashboard

Lecture 62 How to design a KPI Dashboard

Lecture 63 Reporting lessons from journalists

Lecture 64 Using KPI dashboard software

Lecture 65 Big data as a service

Section 14: Building the data competencies in your organisation

Lecture 66 Section intro

Lecture 67 Skills shortage

Lecture 68 The skills needed for a data scientist

Lecture 69 Building internal skills and competencies

Lecture 70 Outsourcing your data analysis

Lecture 71 Leadership challenges

Section 15: Executing and revisiting your strategy

Lecture 72 Putting the data strategy into action

Lecture 73 Why data strategies fail

Lecture 74 Creating a data culture

Lecture 75 Revisiting the data strategy

Lecture 76 A changing business environment

Lecture 77 Changing technology landscape

Section 16: Looking ahead

Lecture 78 Using data for good

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