Tag: Big Data

Big Data and Analytics: How to avoid going the way of the Dinosaur!

jurassic_parkhttp://www.linkedin.com/today/post/article/20130822181033-251829763-big-data-blurring-risk-and-uncertainty

“More than 99% of all species that have ever existed are now extinct. The causes of species extinction include the predictable — predator-prey relationships, for example — to the unpredictable, such as an asteroid collision. Similarly, 90% of Fortune 500 companies since 1955 no longer exist. Businesses, like species, face perils that range from identifiable risks to true uncertainty or unknowns. Uncertainties pose unknowable and hence unmanageable threats. Risks, however, can be explicitly accepted, avoided, or transferred. Organizations that are fully exploiting big data are actively uncovering and converting uncertainty into known risk as well as addressing and exploiting competitive vulnerabilities.”

The following three big-data analytics keys are critical to supporting a proper understanding of risk versus uncertainty — and ultimately leveraging risk for competitive advantage.

1. Healthy Analytics Culture. The first key to using big data analytics to survive is empowering business owners and leaders with the ability to use data to drive decision-making. There is so much data to analyze, so using cutting edge analytics tools and employing curious and proactive analytical professionals help maintain a healthy culture.

2. Segmenting Risks. The second key is know how to identify and classify risk. When you come across a risk in your business you have to assign the right team or person to investigate the risk. To understand if it should be accepted, avoided or somehow transferred. Accepting risks means you have to monitor it and make sure its controllable. Avoided risks require changes in strategy or process, often needing people to lead a new way to do things. Transferring the risk means you need to trade-off things or hiring someone else to take the risk from you. Big Data analytics allow you to investigate, assess and segment risks.

3. Accept, Avoid or Transfer Risks. Once you have decided how to segment risk, then you need to take action. You need to set up a mitigation strategy, you need to monitor the risk and you be capable of re-segmenting the risk if it changes.

Businesses that can access their big data, that can analysis it and that use it to drive decision-making will survive. Ones that do not will go out of business, be acquired or just go the way of the dinosaurs.

13 Months in the Philippines – Lesson 2 – June 2012 – Training is My Passion

522Pasay City, Metro Manila, Philippines

I did a trial run of the Introduction to Analytics training back in December 2011 with some interns and business partners, which helped me prepare a two-day training class. I launched the two-day class with the target of fresh grads in late May 2012, and I conducted several of the classes over the course of the next six months. It was in June however that I really figured out that I was an amazing trainer and that I could enchant an audience by talking about analytics.

I have always liked being in front of an audience and being empowered to talk about things I am passionate about it. I get a huge rush of adrenaline that can last for several hours. This calling originally led me to traditional classroom teaching but after several misadventures post graduate school, I took the job with Wells Fargo to pay the bills. Fifteen years later I left Wells to do training full time. In the interim I did a lot of ad-hoc and informal training in various way at Wells although I never had trainer in the title.

Per Wikipedia, a Trainer is a person who educates employees of companies on specific topics of workplace importance. While a teacher is simply who provide schooling for pupils and students. I have found that I am exactly in the middle. And there are very, very few people who can train like a teacher. People who can provide hands on, useful content in a short time frame, but deliver it in way that has the empowering effect of taking an actual academic style class are worth their weight in gold. These are the great trainers or favorite instructors who end up becoming speaker and lectures. They have both the ability to train on skill and teach on knowledge. This is what I learned about myself last June.

From an analytics standpoint, I learned a lot about how to construct a training program. Budget, Recruitment, Venue Management, Staffing, Marketing, etc. I learned a lifetime worth of lessons in a few months. I was able to look at each of these topics and find data to compare what I was doing to other benchmarks. Am I efficient, am I cost-effective, am I marketable. Lots and lots of data to bring into my analysis of how to grow my business.

Analytics Tool > Microsoft Excel > http://office.microsoft.com/en-us/excel/

Analytics Concept > Big Data > http://en.wikipedia.org/wiki/Big_data

YouTube Resource > http://www.youtube.com/watch?v=jhjuyH4RTrM&feature=share&list=PL7EC252B253873D5D

My Analytics Story – My passion is solving problems by bringing together the best talent, cutting edge technology and tried and true methodologies. DMAIPH is all about empowering people towards better Decision-Making through the use Analytics and business Intelligence. This is what I do best. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly for a free consultation about getting more analytics into your career and your business.

Data Engineer? Data Scientist? I love all the new terms for data nerds

Here is an infograph on Data Engineers, something one of my trainees came up with at the direction of my assistant.

15_Alvin_Data_Engineer

I love it! So much information wrapped into an eye catching visual. I’m proud of you Alvin. This is really good stuff! Anyone looking for top-notch analytic talent who gets both big data (the science)  and data visualization (the art), look no further. We have them here at DMAI!

 

Managing Big Data: The 3 V’s

InfoGraph_2.08I came across this infographic earlier today and loved on of the visuals illustrating the challenges marketing managers have with Big Data. Big Data is all the data you have in your business… customer, product, social media, marketing spend, etc.  Its considered big if you have more of it then you know what to do with.

According to the data gathered, the challenges are:

  1. Variety = The diverse sources of data, the different places is stored and the various applications needed to access it. 49% of the respondents cited this as the biggest challenge. For me variety challenges can be mitigated if you have a good data warehouse approach and have a data master to keep it all inventoried.
  2. Volume = The amount of data in your business that you have to analyze to be able to make decisions.  In the underlying survey, 29% of respondents indicated the sheer amount of data they had to work with is the biggest challenge. The best way to deal with this challenge is to have cutting edge, analytics tools that allow you to mine data quickly. Tableau is my favorite!
  3. Velocity = The speed in which you receive data. It can either be too fast to properly analyze or it can be to slow to be used in your decision-making process. 26% of the respondents indicated that the speed in which they are fed actionable data is their biggest challenge. If you have a way to control the variety and a tool to analyze volumes, then velocity shouldn’t be an issue.

Contact DMAI via this blog or you can e-mail me directly at danmeyer@dmaiph,com to set up an analytics assessment to help you figure out a strategy to control for the variety, volume and velocity in which you use your business data to drive decision-making.