Big Data & Digital Marketing

Top Performers consistently apply analytics in almost every activity across their organization. They prefer Analytics over Intuition 5 times more than Low Performers.

This Survey by MIT Sloan, in collaboration with IBM, draws a clear picture on how organizations can approach big data, what the major challenges are and how a successful analytics culture can be established.

Organizations are usually found in one of these 3 stages:

1. Aspirational: just started with analytics. The main target is to improve cost efficiency. Are not very rigorous.

2. Experienced: use analytics to guide actions, target at growing revenues, some use of rigorous approaches, applications are limited for future strategies.

3. Transformed: use analytics to prescribe actions, use analytics at all levels also in day-by-day activities, use rigorous approaches.

Sometimes organizations transition from state 1 to 2 to 3.

The Survey suggests a 5-step methodology for successfully implementing analytics-driven management:

1. Focus on the biggest and highest value opportunities

2. Within each opportunity, start with questions, not data

3. Embed insights to drive actions and deliver value

4. Keep existing capabilities while adding new ones

5. Use an information agenda to plan the future

This is one of the best article I have ever read on Big Data.

Big Data is not just about having more data, or at a higher rate, or in different shapes. It is a profound shift in the way we deal with data analysis. Actually 3 shifts:

1. from "sample" to "population"

2. from "clean" to "messy"

3. from "causation" to "correlation"

Data collection is not a news (cookies exist since the beginning of the internet). Now it has expanded into our life in the "real world", and it is bringing incredible benefits to:
1. Cities
2. Healthcare
3. Environment

Nevertheless Big Data is a double-edged sword, and cuts both ways. Although the potential of Big Data to do good is great; it is just as easy to manipulate and abuse.

Big Data: hero or villain?

With SaaS, many of the challenges associated with the traditional software distribution model are eliminated right off the bat, essentially making a big data deployment much less of a hassle to deal with.

In an SaaS arrangement, a service provider:

1. hosts the software and delivers it to you over the web.

2. handles all the grueling maintenance aspects that come along with it behind the scenes. 

Microsoft's Windows Azure HDInsight is the perfect example of such an application.

Right now, big data applications are limited in comparison to other fields, but there will surely be more variety available soon.

I particularly like the first point:"Big Data is not a technology initiative, but a business one."
Here is the list of 4:

1. Ownership

2. Data

3. People

4. Technology

There is a lot of content in this (long) article published by the Harvard Magazine.

Here are my main 3 takeaways:

1. "The Big Data revolution lies in improved statistical and computational methods, not in the exponential growth of storage or even computational capacity" by Gary King

2. Big Data isn't everything: "We had petabytes of data and yet we were building models that were fundamentally flawed, because we didn't have insights about what was happening" by Nathan Eagle

3. "No matter how much data exists, researchers still need to ask the right questions to create a hypothesis, design a test, and use the data to determine whether the hypothesis is true." by Nathan Eagle

In the past, emerging technologies might have taken years to mature. Now people iterate and drive solutions in a matter of months, or weeks.

The article presents the top emerging technologies and trends that should be on your watch list. Here are my best 4 pick:

1. Big Data analytics in the cloud

2. SQL on Hadoop: Faster, better

3. More, better NoSQL

4. Deep learning

Here are 5 wonderful TED/TEDx talks about Big Data.

My favourite is the 3rd one.

1. Jennifer Golbeck

Big Data can predict your intelligence from social media behaviour. "My goal is to improve the way people interact online"

2. Alessandro Acquisti

Analytics can make our life better, but we must pay a price for that.

We trade autonomy & freedom for comfort.

3. Jer Thorp

We have the chance to build the Big Data Business in the good way, just bring the human element into the story.

4. Kelvin Slavin

Data, particularly algorithms, are changing the very landscape of our world.

5. Philip Evans

Value cannot rely just on having the data, but on leveraging them.

Technology is what is driving the business strategy, and today it is time for data-driven business.

The next hot topic of this decade is data *visualisation*, which is useful not only for making insights more understandable, but also to make it easier to generate insights.

I believe that Data Visualisation itself is an analytic tool.