Digital Companies

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From the course by Duke University

Business Metrics for Data-Driven Companies

4905 ratings

Duke University

Business Metrics for Data-Driven Companies

4905 ratings

Course 1 of 5 in the Specialization Excel to MySQL: Analytic Techniques for Business

In this course, you will learn best practices for how to use data analytics to make any company more competitive and more profitable. You will be able to recognize the most critical business metrics and distinguish them from mere data. You’ll get a clear picture of the vital but different roles business analysts, business data analysts, and data scientists each play in various types of companies. And you’ll know exactly what skills are required to be hired for, and succeed at, these high-demand jobs. Finally, you will be able to use a checklist provided in the course to score any company on how effectively it is embracing big data culture. Digital companies like Amazon, Uber and Airbnb are transforming entire industries through their creative use of big data. You’ll understand why these companies are so disruptive and how they use data-analytics techniques to out-compete traditional companies.

From the lesson

Working in the Business Data Analytics Marketplace

Welcome! This week, we will meet some great people - all former students of mine - now working at super-interesting and exciting jobs as business analysts, business data analysts, or data scientists. We’ll explore what they do, how their role relates to big data, and the skills they needed to get hired! Our hope is this information will give you a better understanding of the type of data-related job you might apply for once you've completed this specialization, and a sense of the type of company you would find most appealing to work for. By the end of this week, you will be able to: differentiate among different job roles within a company that work with data; identify how each role works with data; and describe the skills required to perform each job role. You will differentiate how different types of companies relate to big data culture, and rank any company according to a 20-item checklist. You will also learn to differentiate how different types of companies relate to big data culture. Included in this week’s materials is a 20-item checklist to rank companies. This week also includes in-video polls so you can see how others are ranking their businesses.

Strategic Business Consulting - Focus on Software/IT Systems Integration3:49

Hardware and Software Companies7:52

Digital Companies5:45

Meet the Instructors

Daniel Egger
Executive in Residence and Director, Center for Quantitative Modeling
Pratt School of Engineering, Duke University
Jana Schaich Borg
Assistant Research Professor
Social Science Research Institute

The companies that we've chosen to identify as digital companies

are some of the leaders at using new business models to

disrupt traditional markets or forge entirely new markets.

These companies are driven by developing new information technology.

Both software and business analytics for their own internal use.

Mostly, products or services they sell can be offered better, faster,

cheaper, than their competitors, because of their superior grasp

of real-time data processing and machine learning.

Because they are architecting entirely new systems,

these companies need software engineers and, to a lesser extent, data scientists.

They have relatively less need for business analysts and

business data analysts.

Amazon has completely transformed multiple retail industries,

starting with books, moving on to electronics and other goods.

But recently, its biggest impact has been in the hosted storage and

processing business known as Amazon Web Services, or AWS.

More than six billion of Amazon's 69.6 billion

in revenues came from the giant server farms that it offers on a variable cost,

rent just as much as you need basis.

So global 2000 companies median business and

many of the best known start-up including both Airbnb and Google.

Amazon.com surpassed Walmart in the summer of 2015.

Becoming the largest retailer in the world by market capitalization.

We have elsewhere discussed Amazon's outstanding real time user

experience customization for revenue optimization.

Amazon also pursues a recurring revenue loyalty program model with its

Prime membership.

And competes as the low cost provider of data and

processing hosting services worldwide.

Perhaps most extraordinary is

Amazon’s early dominance of the cloud computing sector.

Amazon is rumored to have built over 500,000 customized Linux servers to date.

And its revenue from cloud computing are estimated to exceed that of its three

closest rivals in this base, IBM, Google, and Microsoft combined.

Many Internet companies offer information and services for free, and make their

money by selling targeting advertising, or better positioning within search results.

These companies use analytics both to make their services as useful and

attractive as possible, and

also to identify users toward whom to target specific advertising campaigns.

Leaders in the ad supported, free to users category, are of course first Google,

where over $50 billion of

their 69.8 billion in revenue is from targeted advertising.

Second, Facebook with $13.5 billion in 2014 revenue, primarily from advertising.

Third, LinkedIn with multiple revenue streams, but

at least 20% of its $2.9 billion in revenue from targeted advertising.

A fourth digital information company, dominating the residential real estate

rental and sales listings real estate information in metric sector is Zillow,

with $386 million in revenues, largely from advertising and placements.

Two companies that have generated tremendous attention for

their innovative sharing economy business models, and are equally impressive for

their use of data analytics, are Uber and airbnb.

Uber competes against traditional taxi companies.

Uber digitally links drivers with people needing rides, allowing each to

see reviews of the other and allowing passengers to see a map of how far away

the nearest Uber car is, and how long the soonest available will take to arrive.

As well as getting a committed fixed price from Uber for

a journey to a specified address, before they set out.

Uber also charges more when demand for cars exceeds supply,

a variable pricing method to optimize clearing of inventory of available cars.

Uber drivers own their own cars and work as independent contractors, so

Uber has minimal capital expenditure.

Uber takes a 20% commission for matching drivers and passengers.

Uber's commission revenue is expected to exceed two billion dollars in 2015,

on ten billion in gross spending by passengers.

Airbnb competes with traditional hotels.

Airbnb, which matches property owners who wish to rent out a vacant apartment or

even a room with travelers who are looking for a more personal travel experience.

Also provides mutual reviews of owners and renters.

Provides detailed mapping functionality to identify what is available in a given

region, and provides owners with predictive analytics tools to

optimize their revenue based on location, day of the week, time of the year, etc.

Airbnb collects a commission that averages 11% on room rentals.

So, about 420 million in revenues on about 4 billion in bookings in 2014.

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