Gramener is one of the 30 contestants (among 20,000) selected at Pioneering Spirit, a entrepreneurs’ reality contest.
The key to any businesses success is the ability to identify and act on fresh leads consistently over time. Using data visualization software can help solve the age old question of how to keep the flow of customers constant and growing. The solution is often found within the data the business already generates.
The problem facing small entrepreneurs and big businesses alike is taking the data generated from all its various sources (employees, vendors and customers) and harnessing it into a sales tool. Once a business has a better understanding of its current customer base and administrative structures, identifying new opportunities and trimming waste is an easy process.
According to Flowers (director of analytics for the Office of Mayor of New York City), applying predictive data analytics towards “preemptive government” in New York City has resulted in:
• A five-fold return on the time of building inspectors looking for illegal apartments
• An increase in the rate of detection for dangerous buildings that are highly likely to result in firefighter injury or death
• More than doubling the hit rate for discovering stores selling bootlegged cigarettes
• A five-fold increase in the detection of business licenses being flipped
• Fighting the prescription drug epidemic through detection of the 21 pharmacies (out of an estimated total of 2,150 in NYC) that accounted for more than 60% of total Medicaid reimbursements for Oxycodone in the city.
Perez’s(Anthony Perez, director of business strategy for the National Basketball Association franchise.) team began by using analytic models to predict which games would oversell and which would undersell. The box office then took that information and adjusted prices to maximize attendance — and profits. “This season we had the largest ticket revenue in the history of our franchise, and we played only 34 games of the 45-game season due to the lockout,” he says.
P&G uses predictive analytics for everything from projecting the growth of markets and market shares to predicting when manufacturing equipment will fail, and it uses visualization to help executives see which events are normal business variations and which require intervention. “We focus the business on what really matters,” Says Guy Peri, director of business intelligence for P&G’s Global Business Services.
Big Data has suddenly caught everyone’s attention which in turn has made it one of the hottest debated topics nowadays in the enterprise computing circle. The need to unshackle this huge treasure trove is now beginning to dawn upon every CIO and they are realizing the significance of how it can bring in business efficiency and value.
The Data conundrum is giving rise to Analytics
MIT Sloan Management Review indicates that 58% of the 4,500 respondents (business executives, managers and analysts) say that their companies gain competitive value as a result of data analytics. The more competitive organizations are experienced in analytics and go far beyond its traditional baseline use. Their leaders use analytics to guide strategic and tactical decision making.
They are adept at deploying analytics tools (software for data visualization, modeling, mining, and analysis) that promote the use of data. The article suggests that organizations supporting and practicing analytics of all this data are more competitive than companies that don’t use data analytics in their day-to-day operations.
A new poll done on behalf of SAP finds that small and midsize enterprises (SMEs) are realizing the competitive advantages of using and managing “big data” faster than their larger competitors.
Top competitive advantages gained by using big data include more efficient business operations (59%); boosting sales (54%); lowering IT costs (50%); becoming more agile (48%); and attracting and retaining customers (46%). In large part because of these advantages, 70% of those surveyed said they would expect a return on their big data investments within one year.
This post is part of the output of the Bangalore Fifth Elephant Hacknight.
What you see above are the words most often used on Twitter by Indians. (Click for a larger image). The size of the bubble indicates how often the word is used.
We were looking at whether there are specific words that people with a large number of followers use, that are distinct from people with few followers. The words on the left (also coloured red) are used mainly by people with few followers. The words on the right (also coloured green) are mainly used by people with many followers.
(At this point, it’s worth discussing the dataset. These are 1 week’s worth of geocoded tweets, mainly around India (but including Pakistan, Nepal, etc.) It’s interesting that there were just 80,000 geocoded tweets in this period – and many of them were FourSquare entries.
It’s interesting that people )with low followers often talk about “know”, “high” and ‘”traffic”. People with many followers have significantly more hashtags. Whether this is a cause or an effect of having many followers is, of course, debatable. But the correlation is quite definite.
It also appears that those with more followers are polite. The “good morning”s and “thank you”s are quite to the right. Those with more followers are more likely to say “good” than “bad”, and vice versa. Perhaps there’s something about having Twitter followers that leads to happiness – or is it the other way around?
This picture shows you the words more often used in replies (on the left, in red) when compared to new tweets (on the right, in green).
“haha” and “lol” appear rather prominently in replies. Either folks who reply are an amused bunch, or it’s the funny tweets that get more replies. A lot of replies are also to thank people. The dominance of Mumbai, Maharashtra and Delhi on the right is easiest explained by the presence of the words “@foursquare” and “mayor” – most of these tweets appear to be FourSquare related.
The above shows the words used in the morning (up to 12 noon) vs the evening. Clearly, people mention “morning” in the morning – often, but not always, in the context of “good morning”. The evenings were, at least on this week, were dominated by Euro 2012.
The visualisation used above is a document contrast diagram. Each word is drawn as a bubble, whose size represents its frequency. The horizontal position determines whether the word is closer to one aspect or another – e.g. replies on the left vs new tweets on the right. This is a very quick and easy way of understanding what characterises an aspect (e.g. which words are often used with good vs bad), as well as the context in which words are used.