INTRODUCTION FOUR ERAS IN TEN YEARS A REVOLUTION IN ANALYTICS Flashcards
What serious threat does complacency pose to businesses?
Complacency can lead to misguided satisfaction and failure to recognize competitive threats.
Examples include photographic film companies, newspapers, and movie rental companies that failed to adapt to new technologies.
Who is Jim Casey and what concept did he advocate?
Jim Casey was the founder of UPS and advocated for ‘constructive dissatisfaction.’
He believed in continuously restructuring and reinventing UPS to counter competitive threats.
What significant advantage did UPS gain from adopting analytics?
UPS gained the ability to continuously assess and improve every facet of their business.
This included the design of handheld devices for drivers and building a large data warehouse.
What is ORION and its significance for UPS?
ORION is a prescriptive analytics model that optimizes delivery routes for drivers, saving time and fuel.
It generates over $400 million in annual cost savings for UPS.
What was the primary data storage solution during the Analytics 1.0 era?
The primary data storage solution was the relational data warehouse.
It required data to be structured in rows and columns and involved a lengthy ETL process.
Fill in the blank: Analytics 1.0 was heavy on _______ analytics.
descriptive
What cultural challenges did organizations face during the Analytics 1.0 era?
The culture was reactive and slow, with analytics often being used only to support decisions rather than drive them.
Many decisions were still made based on intuition rather than data.
What is the key difference between data analysts and data scientists?
Data scientists are more involved in guiding strategic decisions and product development rather than just supporting decision-making.
They often prefer to work closely with executives and focus on creating data-driven products.
What does the term ‘self-service analytics’ refer to?
Self-service analytics refers to tools that allow users to create their own reports and visualizations without needing analytical professionals.
This trend emerged to make analytics more accessible.
What major change occurred in the analytics landscape after 2007?
The emergence of Analytics 2.0, 3.0, and 4.0, which introduced new ways of handling and analyzing data.
This shift was characterized by the rise of big data and advanced analytical technologies.
What was a significant technological development in the era of Analytics 2.0?
The creation of Hadoop, an open-source program for storing large amounts of data across distributed servers.
Hadoop allows for minimal processing and is a cost-effective way to manage big data.
True or False: The analytics created during Analytics 2.0 were typically sophisticated.
False
They were often less sophisticated, focusing on flexibility and low cost.
What is the relationship between data scientists and senior executives in modern analytics?
Data scientists often work closely with senior executives, guiding strategic decisions rather than remaining in the back office.
They seek to have a direct impact on business outcomes.
What is the ‘big data equals small math’ syndrome?
It refers to the phenomenon where big data is analyzed using relatively simple mathematical techniques.
This was noted by data scientists who observed that the analysis was not as complex as one might expect.
Fill in the blank: The analytics era prior to 2007 is referred to as _______.
Analytics 1.0
What was the focus of companies competing on analytics in the mid-2000s?
They focused on improving decision making and performance using available analytical capabilities.
Despite challenges, they were dedicated to making analytics work.
What role did the relational data warehouse play in Analytics 1.0?
It served as the primary data storage solution, requiring structured data for analysis.
This approach had its challenges, including difficulties in data management.
What was the career path of the individual mentioned in the text?
Data scientist at LinkedIn, venture capital, head of product at a startup, to the White House
The individual admitted to having an office in the basement of the White House.
How did data scientists interviewed perceive decision support?
Many found it uninteresting, with one referring to it as ‘the Dead Zone’
They preferred to focus on products and features.
What are some data products developed by LinkedIn?
- People You May Know
- Jobs You May Be Interested In
- Groups You Might Like
These products contributed to LinkedIn’s growth.
Which company acquired LinkedIn and for how much?
Microsoft for $26 billion
What is a key lesson from Analytics 2.0 practitioners?
Analytics are core to the strategies of many firms, competing on analytics more than others.
What is the motto of Facebook regarding its experimental culture?
‘Move fast and break things’
What does Analytics 3.0 represent?
A combination of big data and small data for big companies
