"Get Your Hands Dirty" ™ and Get Social Media Up and Running in 6 hours

"Tell me and I forget.  Teach me and I may remember.  Involve me and I learn."  

Benjamin Franklin

Social media can contribute to both top and bottom line in an organisation.  This workshop is specifically designed to get organisations up and running with social media in a systematic way in less than a day.

In this hands-on workshop, within 6 hours, participants will:

• Create a Company Page on Twitter;
• Create a Company Page on LinkedIn;
• Create a Company Page on Facebook;
• Create an online magazine;
• Post the first piece of content to ALL pages at the same time
• Learn how to maintain business pages fresh and interesting in less than 2 hours/week

After the workshop students and, their organisations, will go away with:

• a social media blueprint 
• a business Facebook page
• a business Twitter page
• a company LinkedIn page
• a voucher for 1-hour complimentary consultation
• a weekly to-do list to keep Social Media presence fresh
• own online magazine like Big Data for Organisational Leaders

Date and Time: 30 July 2013, 8:30 am
Venue: Brisbane Convention and Exhibition Centre
Duration:  7 hours, including morning tea and lunch
Price: $460 (GST incl.)

Requirements: Laptop (preferred) or tablet

Internet connectivity: Provided
Morning Tea: Provided
Lunch: Provided

Pirates (on the High Seas), Graffiti and Big Data

Big Data is starting to have significant and wide-reaching impact on our lives.  And, it can be found in quite unexpected places.  +Nate Silver's prediction of 2012 US Election has been making headlines on the web for the last three months.  The accuracy is surprising, using Big Data to achieve it, probably not so much.  However, following are two scenarios where Big Data’s value is not so obvious.  The first one shows how Big Data analytics has been used and the second one demonstrates the potential of Big Data for dealing with minor crime and benefitting communities.

Pirates (on the high seas)

Although we’re now in the 21 century with advanced technology and military hardware at our disposal, piracy still remains a significant problem.  Oceans Beyond Piracy, a US-based consultancy, estimated that losses from piracy reached $7Bn in 2011. 

However, in 2012 the International Maritime Bureau reported a 54% drop in piracy incidents in the first half of 2012 compared to the same period the year before.  The reason for this drop was the fact that law enforcement agencies turned to Big Data to try and prevent piracy.  The amount of data available to Government agencies is analysed in order to predict where the incidents may occur in the future.  The information is then plotted on a map using advanced mapping software by Esri and used by the relevant maritime and Government authorities.  

The results, as we can see, are simply staggering. 

… And, graffiti (in the city)

The above example brings us to another potential use of Big Data - reducing graffiti appearances in our cities.  According to a report from the Australian Institute of Criminology, graffiti costs around $1.5 billion a year in Australia, based on conservative estimates.  Graffiti can be classified in several groups with the offenders in each group possessing a number of distinct characteristics.  The most prevalent type of graffiti writer, accounting for over 50% of all people engaged with graffiti, is the tagger.  The report also lists some specific traits of graffiti writers: 

• tagging is more common among teenagers and piecing, or graffiti on murals, prevalent in the group of those 15 years old or over;
• likely to be alienated from school in some form;
• majority have strict self-imposed rules where they will graffiti;
• majority are males between 12 and 25, etc.

Thus, if we look at how to deal most effectively with graffiti, it is clear that focusing on taggers will provide the “best bang for the buck”.  They also are the easiest group to deal with in terms of predicting the location their future actions since their mobility is limited, because of age.  Thus, using data from schools, reports of graffiti incidents to police and local authorities and data from cleaning operations it is possible to build a predictive model in relation to graffiti.

Similar approach has already been applied by the Memphis Police Department in relation to various crimes with great success.  The Department is using analytics to predict incidents.  The report from their analytical solution may say “You’ve had three robberies that occurred between 10 p.m. and 1 a.m. on Monday”.  This allows patrols to be deployed in areas where they will have the biggest impact.  

In essence, this approach is similar to the one, mentioned above, and used to fight pirates on the high seas. And, in relation to graffiti it can be equally effective because of the similarities in available data and the characteristics of the crime.

Can Big Data Crack Fraud?

How many jailed criminals receive unemployment benefits? How many people are working while claiming unemployment benefits?  How many unemployment benefits recipients are driving high-end BMWs? These questions are not always very easy to answer.

Part of the problem is the increasing number of services delivered through online methods.  Registering with Medicare or Social Security and then receiving benefits can be done in a fully virtual environment.  The situation is complicated further by various jurisdictional boundaries - local, state and federal governments.  This problem is probably less pronounced in countries with two levels of government, but it still exists, nevertheless.

However, the above questions are becoming easier for authorities to answer by using Big Data. And, smaller jurisdictions, with correspondingly smaller budgets and "narrower" view of their constituents, are going to be some of the biggest beneficiaries.

An example of using Big Data to identify fraud is the work done by +LexisNexis in US.  The company compared Medicaid recipients against vehicle registrations.  The check discovered quite a number of people receiving Medicaid benefits and driving everything from Bentleys to Aston-Martins to high-end Mercedes-Benz vehicles.

According to Andy Bucholz, director of Government Fraud Solutions for +LexisNexis, a much more holistic view of citizens and their activities is very likely to solve some of the fraud-related problems.

Read the full article in +Government Technology by Wayne Hanson here.

How Big Data Is Changing the Whole Equation for Business

Businesses in a range of industruies are finding new ways to use the data available to them. Quite often business as usual gets in the way of any Big Data initiatives. After all, humans (and organisations) are inherently resistant to change.

Here are some examples of organisations using data to transform their businesses.

Human resources - Caesars Entertainment is analysing health insurance claims of its employees. Since 2009 the company has saved $4.5 million.

Product Development - Zynga, the game maker behind Farmville, captures 25 terabytes/day and uses that data for customer service, quality assurance and new feature research. For example, in FarmVille 2, animals were made more central because, surprisingly for the company, players interacted more with them than originally expected.

Operations - UPS combined GPS information and data from fuel efficiency sensonrs to reduce fuel consumption by 8.4 million gallons and cut 85 million miles off its routes.

Read the full article in +The Wall Street Journal  by Steven Rosenbush and Michael Totty here.

Big Data and Business Intuition Work Together

The question of gut vs. data is becoming more and more relevant considering the terabytes of data available in each organisation. However, there's is a happy medium according to reports from the Economist and +Harvard Business Review. The trick is how to combine the two.

According to management expert Dr. Chongqi Wu gut-based and fact-based decision making complement each other and shouldn't be seem as competing approaches. According to Dr. Wu "Data just makes executives better gamblers".

There are times, of course when one of the approaches is better than the other. For example, it's much better to rely on data in operational decisions that can be automated. On the other hand, when dealing with incomplete information, setting strategy is one example, decisions based on intuition are can be the better.

It's important to differentiate between the initial hunch, which is quite often correct, and the subsequent assumptions that have almost no intuitive value.

And, the old adage of "garbage in, garbage out" holds true in this instance, as well. We need to learn to ask the right questions of the available data.

Read the full article on +GoodData by +Cliff Cate here.

Big Data Questions for the Layman

• 90% of data was created in the last two years. Why is that? 
• How does that affect security professionals? 
• How does that affect the everyman?

According to various sources 90% of the data in the world was created in the last two years.  The main reasons are: the rising popularity of social networks, our willingness to share more and the type of information we create/consume/share.  Let’s have a look at each of these in turn.

Rising popularity of social networks

Facebook, for example, grew from 197 million to 901 million active users within the space of 3 years (source: jeffbullas.com).  Google+ figures tell a similar story, within a year its user base grew from less than 50 million to 500 million (source: farotech.com).  These are the two behemoths of social networking; however the figures from other networks, such as LinkedIn, Twitter, etc. suggest a similar story.

Willingness to share

And, this growth has made all of us much more comfortable using the networks, connecting with family and friends, posting photos, videos, songs, etc.  

In a sense, this is similar to the e-commerce trends. In the early 2000s only a small number of people were transacting over the Internet and the security, privacy and other concerns were quite high, and justified.  These days hardly anybody pays attention how the transaction occurs.  What is important is the result – a purchase made at an acceptable price with almost 100% guarantee of delivery.

Mark Zuckerberg even speculated that the amount of information we share doubles every two years.  

Type of information created/consumed/shared

Until recently creating and posting “rich media” for others to see and use required a certain amount of technical skills.  At present, with a large percentage of population (50.4% in US, according to Nielsen) carrying smartphones in their pockets/handbags, it’s never been easier to create a 3-min video of little Johnny playing with his sister. And, the size of this video on iPhone 4 would be 240Mb, while on iPhone 4S or 5 that figure would go to 540MB. 

Even with compression, let’s say when uploading to Facebook,  the data amounts are staggering compared to a spreadsheet considered “state of the art” only a few years ago (2005 seems somewhat pre-historic these days in “Internet chronology”). 

This type of data explosion is certain to affect a growing number of professions.  And information governance and security professionals, will be amongst to first that will have to adapt and deal with this new reality.  Organisations are already starting to recognise the importance of Big Data and how it can deliver competitive advantages.  As a consequence, this realisation will further accelarate the drive to start using these technologies.  

Thus, the question in the mind of many executives will become “how to do it”.  It’s certain, existing systems and infrastructure are not very well suited for Big Data purposes.  Some of the more obvious options would be:

• develop expertise in-house and introduce new infrastructure;
• outsource Big Data processing to companies specialising in this area;
• a mixture of the above;
• or a new model, e.g. utilising Platform-As-A-Service (PaaS), Software-As-A-Service (SaaS) or something currently being dreamed/prototyped in a garage somewhere in the world

Any of these scenarios imply a certain amount of change.  And, how this change is decided upon, implemented and then managed will be of concern to governance and security professionals.  Why? They will need to provide advice, help other units within their organisation and monitor the new processes afterwards.

This is a tide which is already irreversible.  Organisations can’t afford not to deal with Big Data because their external stakeholders have already embraced it.  Our lives have been enriched by new technologies and we will continue to share lots of photos and videos.  We will ask for sensors to be attached to us so that we can monitor our blood pressure, or how well we exercise or sleep.  And, because we know that, through various sensors, a trained professional can be monitoring our parents’ health, living on their own, 24 hours. 

Big Data has made big promises and now the general population is keen on those being delivered. 

6 Steps To Manage Big Data

Here are 6 tips by +Diane Berry from +Coveo and +Coveo's engineers to handle the biggest challenge of the 3 Vs of Big Data - Variety:

1. Understand Your Business Goals Beforehand
2. Don't try to Move the Data
3. Replicate and Duplicate Data? Don't Do It
4. Use Indexing Technology to Navigate a Complex Data Environment
5. Present Information Based on User Actions
6. Spin Data Into Insights

Full article on +InformationWeek by Jeff Bertolucci can be accessed here.

What's Your Big Data Worth?

Business leaders wanting to value their data are facing significant obstacles from outdated accounting practices. A positive development, however, is the fact that data has been added as an asset class during the +World Economic Forum  Summit in Dubai.

And, some Gartner clients are now asking not only how to become information-driven but also how to generate revenues from the data assets they own.

Also, according to John Lewis from Nielsen, a common mistake was "falling in love" with own data and disregarding external sources, such as industry or consumer data.

Full article on +InformationWeek by Ellis Booker can be accessed here.

What A Data-Driven Culture Buys You

A survey by the +Economist Intelligence Unit of 530 C-Level executives found a very strong correlation between company's financial performance and how it views data collection, analysis and sharing.

Companies that considered themselves ahead of peers financially also paid strong attention to the way they collected, analyzed and used data. The reverse link was also very strong.

Elissa Fink from +Tableau Software, the company that sponsored the survey, speculated that the reason for the results can be very simple "If you're on top of your data, you're probably more aware of your financial performance".

Full article on +InformationWeek by Ellis Booker can be accessed here.

9 Big Data Challenges Banks Face

Some banks have started dusting off projects that were put on hold when the financial crisis hit. However, most of these are dealing with a specific problem, such as liquidity risk reporting and not trying to transform the enterprise systems at once.

These are the major challenges as identified by executives from +SAP:

1. The Big Data myth
2. Dirty data
3. Aged data infrastructures
4. The need for real-time data
5. The need to get new products to market quickly
6. Inefficient data management
7. Seeing the value of data
8. The need to shift IT from cost to profit center
9. Fear of failure

Full article on +American Banker can be accessed here.

Big data is the key to unlocking big gains in energy productivity

Big Data will allow energy productivity gains, called for by President +Barack Obama, to be achieved more easily. And, that applies as much to the new, already efficient buildings, as to existing ones where the biggest impact would be felt if they're made more energy efficient.

At present, US and Canada, use almost double the amount of energy per capita, compared to Germany and Japan - 83,561 and 86,101 kWh respectively, vs 46,702kWh (Germany) and 45, 477kWh (Japan).

WebMeter is a device that can monitor data from up to 36 circuits in a building's circuit board. And, it's main difference is cost - 1/10 compared to other monitoring technologies.

Full article by Tyler Hamilton can be accessed here.

Big Data Pumps Life into Water Investment

A fundamental question remain unanswered in relation to water: At what costs is it economical for cities to bring additional water resources online? In other industries, e.g. oil, this question is easy to answer. Water industry, however, is treated quite differently by politicians, Wall St and other policymakers.

Large amounts of data are available in relation to water - volumes, expenditure, energy costs. These, when analyzed, would allow for creation of an universal index that can be used to evaluate attractiveness, or otherwise, of water investment.

And, this is what Water Cost Index developed by +IBM  and Waterfund is looking to achieve.

Full article can be accessed here on SustainableCitiesCollective blog.

Big Data's Big Blind Spot

(from Forbes)

Data can help envision the future, but it isn't the future. On the other hand, what makes us human most likely is the unpredictability of our behaviour. And, this cannot be handled easily by Big Data. Because our behaviours will lead to Big Swings that are not easily handled by Big Data.

Or to put another way, "Black Swans" will always be there at some point in time.

You can read the full article by Rick Segal from +gyro on Forbes here.

Unleash The Brawn Of Big Data With Small Steps

(Photo credit: Eoin McNamee, from Forbes)

A big gap exists between the possibilities of Big Data and its use in making better business decisions. Studies show that although ROI of 241% can be generated by using Big Data, only 11% of marketers use it in their decision making activities.

And, one of the reasons for this disconnect is that Big Data can be daunting. One solution is to start with baby steps and progress from there. This is what Caesar's Entertainment and Rapid Racking, a UK-based manufacturer have done.

Read the full article by +Sandra Zoratti on Forbes here.

The Retailer's Guide to Big Data

Thanks to consumers’ increasing use of mobile devices and social media, the volume and variety of data points continue to mushroom at a dizzying pace. What are the challenges and opportunities arou...

Mario's insight:

This infographics has it all - what makes Big Data big, challenges and goals in using it and how to develop a game plan.
See it on Scoop.it, via Big Data for Organisational Leaders

9 Open Source Big Data Technologies to Watch

1. Apache Hadoop - framework for data-intensive applications

2. R - statistical language

3. Cascading - software abstraction layer for Hadoop

4. Scribe - server for aggregating log data

5. ElasticSearch - open source search server

6. Apache HBase - non-relational columnar database

7. Cassandra - NoSQL data store

8. MongoDB - another NoSQL data store

9. CouchDB - yet another NoSQL data store

View the full slideshow by +Thor Olavsrud on CIO.com here.

A great presentation by +Martin Fowler from +ThoughtWorks for the non-technical user.  Covers a number of Big Data aspects, including challenges and potential solutions.

A "must see" if your organisation is starting on the Big Data path or you want to understand what Big Data can do for you.

Access the full presentation here.

IBM Taps Big Data for Security

In the last few years IBM has been putting its focus in security on Big Data.  By collecting and correlating large amounts of data from an enterprise IBM is looking to identify patterns hidden in large volumes of data.

According to Kevin Skapinetz the idea is to "squeeze every last drip of information about attacks from your data".

Focusing on Big Data also allows IBM adopt a more proactive approach to security. According to Skapinetz traditional approach to security is no longer enough. Looking actively for attackers, instead of just building bigger walls fits with the time-honoured view that "attack is the best form of defence".

Full article by +Sean Michael Kerner on +eSecurity Planet can be accessed here.

How DHL’s Big Data Boosts Performance

DHL built an in-house Big Data solution to become more competitive and address some challenges.

According to Graeme Aitkin, VP of Business Controlling at  +DHL, the company couldn't produce a standard cost of shipment or pickup and couldn't distinguish fixed and variable costs.

Now, INSIGHT, the costing system built to analyse company data produces cost and profitability for every shipment on DHL's network.

Full article by Taylor Provost on CFO.com can be accessed here.

Mindfulness in legal practice ...

Mindfulness in legal practice going mainstream (Magazine) ABA Journal http://j.mp/UDdiAG v @danlukasik @recessguy pic.twitter.

Posted by +Kevin McKeown on Twitter.

http://twitter.com/kevinmckeown/status/296675337784414209/photo/1

Three Surprising Secrets to Moving People

All leaders move people. Moving people begins when you understand them, not when they understand you.  Daniel Pink believes the ability to move people begins with attunement.



http://leadershipfreak.wordpress.com/2013/01/30/three-powerful-secrets-to-moving-people/