Currently reading: Data Science for Business

"This broad availability of data has led to increasing interest in methods for extracting useful information and knowledge from data—the realm of data science."

The ultimate goal of data science in business is to improve decision making. Here, I highlight some of the key points from the book Data Science for Business.

There are three types of concepts presented in Data Science for Business: how does data scientists fit into an organization, thinking data-analythically, and extracting knowledge from data. The book is structured around fundamental concepts of data scientists. Here are some of them:

• Determining similarity between entities. Finding similarities between for instance customers can be the basis for a predictive algorithm or for cluster analysis. It is also useful in information retreival (e.g. search) and recommendations.
• Lift: how much more prevalent a pattern is than expected by chance (i.e. what is the impact of an algorithm, all else being equal).
• Data based decision making falls into two categories: decisions made on discovery through data analysis, and repeated decisions on large scale.
• The process of extracting useful data can be treated systematically, using standards such as CRIPS-DM.
• Be careful about overfitting the data.
• Applying data mining to extract useful solutions requires thinking carefully about the context in which the data is used.

More to come as I read through the book.

Where is data mining used?

• Analyze customer behavior
• Credit scoring
• Trading
• Fraud deteection
• Workforce management
• Supply-chain management
• Direct marketing
• Online advertising
• Credit scoring
• Help-desk management
• Search ranking

Examples

• Predicting changes in demand at Walmart when a hurricane hits
• Reducing customer churn

Before deciding to use data mining and algorithms, it is important for first define what the deliverable of that analysis should be. By first asking why, it is easier to then tackle the how.

Studies show that data driven companies are more productive.

The data mining process

The analysis is applied to an entity of interest, such as a customer. The customer can be described by a number of attributes. Relevant attributes can be discovered by applying relevant theory (or model), or through an automated discovery process (model agnostic). A model agnostic approach is more likely to lead to overfitting.

The future of big data

The authors compare the development of big data to that of the web. In the beginning, companies focused on putting the basic requriements in place to have a precense on the web. Once that was in place, companies started asking what additional benefit they could get out of the Internet. In the same way, many companies have put the basic data management tools in place, and are now asking themselves how they can take advantage of this resource.Once the capability to process big data sets are in place, companies should ask themselves what new opportunities this could bring.

The book's website: http://www.data-science-for-biz.com/

Entrepreneurship is a kind of management

Part three from my read of The Lean Startup by Eric Ries.

"Lately, it seems that one is cool, innovative, and exciting and the other is dull, serious and bland." He's talking about the how the words entrepreneurship and management go together.

In another startup Eric was involved in, IMVU, they went at it determined to make as many mistakes as they could. They shipped the product as soon as they cobbled something together, they charged people for it, and iterated often - sometimes several times per day. And in 2011 IMVU had revenues of $50 million.


From this experience, Ries distilled five principles:
1. Entrepreneurs are everywhere. An entrepreneur is anyone who works with new products and services under conditions of extreme uncertainty.
2. Entrepreneurship is management. Startups require a management style geard to its context of extreme uncertainty.
3. Validated learning. In addition to making money, startups exist to learn how to build a sustainable business.
4. Build-Measure-Lean. Startups should make the cycle of building products, measuring their success and learning from the experience as fast as possible.
5. Innovation accounting. The boring stuff is also importan, measuring progress, setting up milestones, and how to prioritize our work.


As I wrote earlier, I'm also reading The One Minute Manager by Ken Blanchard and Spencer Johnson. One of the three pillars of the one minute manager is one-minute goals. These are goals no longer than 250 words that the manager and the managee agree upon as the measure of a project's success. Principle five says the same thing, that measuring and comparing performance to goals is an important part of a startup. as well as in established companies.

Continuing to read: The Lean Startup

My second entry on my read of Eric Reis' book The Lean Startup. This great quote comes up right at the beginning:

"And we really were on to something. We were building a way for college kids to create online profiles for the purpose of sharing ... with employers. Oops."

He then goes on to say "There is a mythmaking industry hard at work to sell us [that we too can achieve fame and fortune], but I have come to believe that the story is false, the product of selection bias and after-the-fact rationalization." There's a great book called Fooled by Randomness I read a while ago that gives a lot of food for thought on the source of success.


But, it's not all luck. Reis goes on to write that startup success can be engineered by following the right process.

Currently reading The One Minute Manager and the Lean Startup

I'm currently reading two classic books in the world of business. The One Minute Manager by Ken Blanchard and Spencer Johnson is a guide to becoming a good manager. The Lean Startup by Eric Ries is a book about creating startups that achieve great things without being wasteful.

The One Minute Manager outlines three techniques that managers should use; one-minute goals, one-minute praises, and one-minute reprimands.

The Lean Startup is about Ries' five principles for building a lean startup; entrepreneurs are everywhere, entrepreneurship is management, validated learning, innovation accounting, and "build-measure-learn".

The One Minute Manager is a short story about a young man who stumbles on a guy called the one minute manager in his search for good leaders. I've gotten half way so far and it's instructions are good, if not surprising. I haven't read a lot form The Lean Startup yet, but I'm looking forward to finding out what "entrepreneurship is management" means.