My 32nd B'day!

I'm 32 now. Couldn't be happier than this, spending time with my family at Pangkor & Cameron Highlands :)

Swiss Garden Spa & Golf Resort

Above: 4th Generation - Grandmother, Mother, Me&wife, Kids

Below: Strawberry Plucking in progress at Cameron Highlands

Cameron Highlands

 Birthday Boy

Happy 5th Birthday My Prince Aqeel

Aqeel is 5 years old today! How time flies...Happy Birthday my prince. Wish you all the happiness and mummy/daddy love you so much :).

SAP Forum 2013

Attended SAP Forum yesterday. It was good, SAP has done really tremendous job catching up with latest technology revolution such as mobile, social and analytic. Just wondering whether customers are ready to invest in these technologies considering their existing system is working, if it ain't broke, why fix it?

My wife B'day and Trip to Gambang

We did a two-in-one on previous weekend. Celebrating my wife b'day and fun treat for the kids at Bukit Gambang Resort. It was really fun and ended with B'day dinner at Hard Rock Cafe.Anyway, Happy Birthday my dear!

Happy Belated Birthday Princess

She's one year old and now she can't stop walking and exploring :). Happy Birthday my princess!

QUARTERLY ANALYSIS FOR BIG 4 (PLANTATION COMPANIES)

For quarter end of March 2013, following is analysis of net profit margin of Big 4 plantation companies in Malaysia. IOI again leading in net profit margin % with 17.65% followed by KLK with 10.09%, Sime Darby 6.60% and Felda 6.23%.

Data Scientist: The Sexiest Job of the 21st Century

It's not what I preach, it's taken from Harvard Business Review which I quote below Link. The article below however focusing on consumer data perspective. The other aspect should be considered as well is business data perspective. My earlier posts here and here discussed on the same issue but from business perspective. I concur with the writer that this field will be huge in 21st century. Glad I could be part of it :).

When Jonathan Goldman arrived for work in June 2006 at LinkedIn, the business networking site, the place still felt like a start-up. The company had just under 8 million accounts, and the number was growing quickly as existing members invited their friends and colleagues to join. But users weren’t seeking out connections with the people who were already on the site at the rate executives had expected. Something was apparently missing in the social experience. As one LinkedIn manager put it, “It was like arriving at a conference reception and realizing you don’t know anyone. So you just stand in the corner sipping your drink—and you probably leave early.”

Goldman, a PhD in physics from Stanford, was intrigued by the linking he did see going on and by the richness of the user profiles. It all made for messy data and unwieldy analysis, but as he began exploring people’s connections, he started to see possibilities. He began forming theories, testing hunches, and finding patterns that allowed him to predict whose networks a given profile would land in. He could imagine that new features capitalizing on the heuristics he was developing might provide value to users. But LinkedIn’s engineering team, caught up in the challenges of scaling up the site, seemed uninterested. Some colleagues were openly dismissive of Goldman’s ideas. Why would users need LinkedIn to figure out their networks for them? The site already had an address book importer that could pull in all a member’s connections.

Luckily, Reid Hoffman, LinkedIn’s cofounder and CEO at the time (now its executive chairman), had faith in the power of analytics because of his experiences at PayPal, and he had granted Goldman a high degree of autonomy. For one thing, he had given Goldman a way to circumvent the traditional product release cycle by publishing small modules in the form of ads on the site’s most popular pages.

Through one such module, Goldman started to test what would happen if you presented users with names of people they hadn’t yet connected with but seemed likely to know—for example, people who had shared their tenures at schools and workplaces. He did this by ginning up a custom ad that displayed the three best new matches for each user based on the background entered in his or her LinkedIn profile. Within days it was obvious that something remarkable was taking place. The click-through rate on those ads was the highest ever seen. Goldman continued to refine how the suggestions were generated, incorporating networking ideas such as “triangle closing”—the notion that if you know Larry and Sue, there’s a good chance that Larry and Sue know each other. Goldman and his team also got the action required to respond to a suggestion down to one click.

It didn’t take long for LinkedIn’s top managers to recognize a good idea and make it a standard feature. That’s when things really took off. “People You May Know” ads achieved a click-through rate 30% higher than the rate obtained by other prompts to visit more pages on the site. They generated millions of new page views. Thanks to this one feature, LinkedIn’s growth trajectory shifted significantly upward.

A New Breed

Goldman is a good example of a new key player in organizations: the “data scientist.” It’s a high-ranking professional with the training and curiosity to make discoveries in the world of big data. The title has been around for only a few years. (It was coined in 2008 by one of us, D.J. Patil, and Jeff Hammerbacher, then the respective leads of data and analytics efforts at LinkedIn and Facebook.) But thousands of data scientists are already working at both start-ups and well-established companies. Their sudden appearance on the business scene reflects the fact that companies are now wrestling with information that comes in varieties and volumes never encountered before. If your organization stores multiple petabytes of data, if the information most critical to your business resides in forms other than rows and columns of numbers, or if answering your biggest question would involve a “mashup” of several analytical efforts, you’ve got a big data opportunity.

Much of the current enthusiasm for big data focuses on technologies that make taming it possible, including Hadoop (the most widely used framework for distributed file system processing) and related open-source tools, cloud computing, and data visualization. While those are important breakthroughs, at least as important are the people with the skill set (and the mind-set) to put them to good use. On this front, demand has raced ahead of supply. Indeed, the shortage of data scientists is becoming a serious constraint in some sectors. Greylock Partners, an early-stage venture firm that has backed companies such as Facebook, LinkedIn, Palo Alto Networks, and Workday, is worried enough about the tight labor pool that it has built its own specialized recruiting team to channel talent to businesses in its portfolio. “Once they have data,” says Dan Portillo, who leads that team, “they really need people who can manage it and find insights in it.”

Who Are These People?

If capitalizing on big data depends on hiring scarce data scientists, then the challenge for managers is to learn how to identify that talent, attract it to an enterprise, and make it productive. None of those tasks is as straightforward as it is with other, established organizational roles. Start with the fact that there are no university programs offering degrees in data science. There is also little consensus on where the role fits in an organization, how data scientists can add the most value, and how their performance should be measured.

Election Fever

I must admit, I find political issues too emotionally charging. And politics usually lead to irrational emotional outburst which could hurt relationship. But it’s very important. It’s my right to vote but it’s my right to keep my preference close to my heart as well. I seldom discuss any political issues publicly. It’s just my personal preference. But I keep myself updated on political issues from all angles be it from government or opposition.

It’s alarming however how conservative both sides have become based on their campaigning and manifestos.  When I said conservative, I meant moving towards right wing policies. I can sense that both sides are trying to champion meritocracy policies, reward based on merit. From right wing or capitalist point of view, this is the golden rule to achieve success. However, to lure the poor, various gifts are promised such as BR1M, free education, low car prices and many more. Not one comprehensive policy to assist the poor in the long term perspective. Both government and opposition seem to response more to loud voices coming from middle and upper class of society which I can see trust meritocracy policies are the way to build this country forward. At the expense of poor? Who by the way has low or no voices at all simply because they can easily be bribed by all the wonderful promises by both government and opposition.

Led by two young and smart guys, KJ from ruling party and Rafizi from opposition, both seems preaching the same ultimate goal – merit based society. I respect both of them, they are articulate, intelligent and communicate better that can easily influence lots of people. Both have impressive CV. But they speak from their experience of success as the way to go forward. But not many people have the same gifts and talents as both of them. I too initially believed the same thing. As Rafizi said, he quit Petronas to gauge his talent outside and he was successful. I was doing the same thing, as a Petronas Scholar I was hesitant to join Petronas because I think I can do much better outside. At the moment, I’m happy where I am. But over the years, I learn one thing, success is never about money. I can never feel successful when I see a lot people closer to me struggling to make ends meet.

I’m successful as a result of merit based policies, I can admit that. Merit based policies are no angel though. Learning from Thatcher’s legacy for example, a lot of so called worker’s class still suffering until now. No wonder some were dancing upon learning Thatcher’s death. Merit based policies reward small segment of society to the point this segment controlling the fate the rest of segments of society. Richer is getting richer and poor remain stagnant and getting poorer. How can you say that’s fair? It’s proven in history over and over again.

There should be some balance as I preached in my previous post between right and left wing policies (Hint: Social Market Economy as practiced by Germany) Unfortunately, I can see none comprehensive policies or at least clear ideologies from both ruling and opposition party. This election is a fight between same ideology, the only fight they have between each other is to tackle the weaknesses among each other such as corruption, sex scandal (to the point becoming a joke now), racial issues, etc. On BN side, corruption is so wide spread that has become clear weakness to them. On PR side, reducing civil servants just to fix the deficit budget? Come on. I wish there is one party that has clear ideology to ensure the prosperity of all segments of society. Democrat type party is the closest I can wish for.

Thatcher's Legacy

She has been the most prominent conservative for their cause and completely changed the economic policy of UK during her reign. She is either the most loved or hated person in her country but revered in US. For me, she was a tough leader who were able to execute her beliefs in decisive manner. But whether her beliefs were right to begin with? I’m always in the middle of right and left wing policies. In Malaysia, I’m still confuse on our political environment  especially the economic policies of government and opposition. But I believe both are more inclined towards left wing which is more populist in general. Gradually, I can see both government and opposition becoming more liberal in the sense that individual should be more responsible and independent from government. Hard work should be rewarded but poor should not be left out as well. Thus, I believe the balance between right and left policies are more sustainable. I understand the term easier said than done. It’s pretty hard to strike the right chord when you have millions of people to govern. I do think developing country such as Malaysia requires left wing prescriptions to lift millions out of poverty. But the hardest part is to take away the candy enjoyed by these millions later on upon high income status. Before Thatcher’s reign as prime minister, UK was known  as sick man of Europe due to long economic stagnation. There was no innovation and productivity during those time as a result of long period of left wing prescriptions. The economy needed to be restructured and right wing policies perhaps were the right prescription, hence Thatcher more or less radically invoked the painful process that affected million of workers. UK economy was vibrant again after this painful process but fast forward 20 years later, the economy was ruined again as a result of long prescription of right wing policies. Freer market encourages greed and hence the near collapse of financial market in most of Western World. It’s a cycle, thus makes me think the balance of left and right wing policies must be the way to go. Her legacy is confusing to most people, perhaps history will judge her better. 

double trouble

Not sure a bigger screen helps much, as I see it, a double trouble :).