The 4 aspects of the data and analytics framework

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來自 PwC 的課程

Data-driven Decision Making

2544 個評分

PwC

Data-driven Decision Making

2544 個評分

課程 1（共 5 門，Specialization Data Analysis and Presentation Skills: the PwC Approach）

Welcome to Data-driven Decision Making. In this course you'll get an introduction to Data Analytics and its role in business decisions. You'll learn why data is important and how it has evolved. You'll be introduced to “Big Data” and how it is used. You'll also be introduced to a framework for conducting Data Analysis and what tools and techniques are commonly used. Finally, you'll have a chance to put your knowledge to work in a simulated business setting. This course was created by PricewaterhouseCoopers LLP with an address at 300 Madison Avenue, New York, New York, 10017.

從本節課中

Introduction to Data Analytics

In this module you'll learn the basics of data analytics and how businesses use to solve problems. You'll learn the value data analytics brings to business decision-making processes. We’ll introduce you to a framework for data analysis and tools used in data analytics. Finally, we’re going to talk about careers and roles in data analytics and data science.

Why do you need a data and analytics framework?3:34

The 4 aspects of the data and analytics framework3:41

Data and analytics framework: tools and techniques12:15

與講師見面

Alex Mannella
Alumni / Former Principal

[MUSIC]

There are four aspects to our framework.

Outcomes, decisions and actions, insights, and discovery.

Beyond the emptied mind and

walk our way backwards to define the problem and analysis to redact.

And each of the four aspects we takes steps to ensure

time to value from data analytics.

During the discovery phase you need to define the problem,

develop a hypothesis and collect and explore data.

During insights, you perform the data analysis.

Next comes actions where you link insights to actionable recommendations and

an execution plan.

Finally, you review the outcomes that have transformed the business or

business unit or the industry.

We start from business outcomes to define the problem we are trying to solve.

We often look at the questions that need to be answered or

the key issues that need to be addressed.

The metrics that need to be factored.

This allows us to not only define the problem but

also state our hypothesis on how we are going to impact the outcomes.

Once we determine the outcomes to be achieved, we look at the decisions that

the executives need to make, or the actions that employees need to take.

This allows us to identify the critical dependent variables, decisions or

actions, or the output required to make the right decisions and actions.

Based on the complexity of the problem and the time available

we look at different techniques that can be used to generate those insights.

This typically starts with first understanding what has happened so

far, what the organization has done, and how they can do it in the future,

in order for us to help influence key decisions and actions.

Once we have the techniques that will generate the insights, we can look for

the right data that is available.

The data could be internal or external to the organization.

It can also be structured or unstructured.

Most offered the data available, the time available to obtain the data but

influence the techniques that we could potentially use for insight generation.

Well, this is an iterative process.

It is always better to start from the outcomes and the hypothesis as opposed to

the available data to generate the best value from data and analytics.

So let's recap the data analytics framework.

During the discovery phase you define the problem, develop a hypothesis, and

collect and explore data.

During insights you perform the data analysis.

Actions is where you link insights to actionable recommendations and

then execution plan.

Finally you review the outcomes of long term objectives and solutions.

This framework allows us to move through data analysis in an organized way and

provide us with the process to follow as we work with clients to solve a problems.

In the next video, I'm going to talk about the types of analysis you can perform and

show you the tools that you can use within the data analytics framework.

[MUSIC]

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