Big data is the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. It has been the buzzword of the last couple years, and many businesses today want to “Get Started with Big Data”.
When I start discussing with clients what they want to do with big data, more often than not I get puzzled looks. It is important to have the preparedness to “get started with big data” by having:
- Pinpointed a line of business in the company to get started with the use cases
- Identified use cases that serves a true business needs within that line of business
- Verified that there’s indeed large amounts of meaningful data available to support the use cases
Above is the snapshot of the mindmap showing some sample use cases. You can download the original mindmap from the links at the original post.
This is an interesting analysis on adoption of smarter planet solutions by various industries. It leverages a mindmap to organize the challenges and advantages for industries in embracing the smarter systems.
Here’s the snapshot of the mindmap from the link:
You can use the interactive tool on this page and see if you’re on the right track in building your skills. Are you interested in mobile? Social? Cloud? Analytics? Choose one and discover what industry is ahead or behind in adoption. Then look at which industries are investing and finally where they assess themselves in terms of having the required skills. Your sweet spot might be to find an industry you want to work in, which is investing in one of the big four, and needs skills you can be building today.
Examples -for MOBILE - in media & entertainment, there is about a 50% adoption rate, they are increasing their investments, and they indicate that they do have moderate to major skills gaps! In social – same industry – they think they are at the adoption stage for the most part; are maintaining spend, and have indicated major gaps in skills. Very similar results come up for Cloud. For Analytics, they show a lot of adoption, decreasing spend, ye a fairly big skills gap. Wonder what that’s all about?
Discuss your findings here in comments…
Do you remember when your high school math teacher talked about means, medians, variances, regression analysis and the like? Most of us were probably hoping that we never had to deal with these terms again after passing the exam. Here are the good news: nobody will ask you to calculate a standard deviation with just a pencil and an empty sheet of paper on your desk. We have software that does that job much quicker and more accurate. The bad news: statistics and its applications will become more and more important in the future and you should be able to understand the basic concepts.
No matter if you attend a business school, study electrical engineering or physics. All of these programs will have a statistics class waiting for you. The demand for college graduates that understand the basics of statistics has increased tremendously during the past decade as industry challenges have become more complex and more data needs to be taken into consideration to make decisions. Employers expect their analysts to understand the basic relationships between influencing factors on a business (e.g. the influence of interest rates on the demand of a product) or how to interpret a given set of box- and whisker plots.
IBM’s Smarter Planet initiative for example includes a growth play labelled ‘Analytics’. Analytics is the application of descriptive and other statistical measurements to address real-world challenges. The city of Singapore, for example, used statistical methods and tools to analyze the traffic flow in the metropolitan area and developed models to predict the flow (predictive analytics) to reduce traffic jams and pollution. Statistics can also be used to prevent blackouts by analyzing the correlation between population growth and energy consumption and making predictions for future demand. This allows energy providers to adjust their long-term investment plans for new power plants.
As our world get more instrumented (we can measure practically everything), interconnected (people, systems and objects interact) and intelligent (prediction of future events), statistics will play a major role in the future in all parts of our lives. Big Data, i.e. the collection of vast amounts of data, will require enterprises to find intelligent ways to use the information for their purposes. Being able to structure and analyze this data will become a critical skill for college graduates – statistics builds the foundation for these tasks.
Do you feel that you should recap on your statistics skills? Try this lecture of Khan Academy: Introduction to Descriptive Statistics
Guest blogger: Tobias Enders