If You Can Make it Here, You Can Make it Anywhere: On What Makes a Good Business Analyst by Rajan Chandras

 Assessment, business analyst, Forrester, Industry Review, skills  If You Can Make it Here, You Can Make it Anywhere: On What Makes a Good Business Analyst by Rajan Chandras已关闭评论
12月 142008
 

In the latest post, What Makes a Good Business Analyst?, Rajan Chandras cites some soft items from Forrester’s Business Analyst Assessment Workbook:

  • Ability to think abstractly, identify patterns, and generate ideas and solutions
  • Understanding of when and how to escalate issues or needs
  • Understanding of and ability to delivery the appropriate level of detail needed for each task
  • Interest in exploring and understanding new concepts and topic areas
  • Emotionally invested in the work
  • Ability to learn by shadowing stakeholders
  • Ability to clearly articulate technology in terms stakeholders can understand
  • Understanding of the organizational culture and its impact on processes and projects (this one seems obvious, but the latter phrase is more profound than might seem at first glance)
  • Ability to drive a decision analysis and selection process
  • Ability to recognize patterns in requirements and categorize them appropriately

What’s more, there are some suggestions by Rajan Chandras himself:

  • Know the organization’s external environment: its competitive position, current state of the industry, geographical & social factors, etc.
  • Know the organization’s internal environment: its financial position, organization culture, IT maturity, etc.
  • Adapt to the needs (your language, dress etc.), but be yourself. Imperfect, yet genuine, is fine; falsity comes through easily, and will destroy your credibility in no time.

No doubt, no boss can reject such a perfect analyst. But I’m afraid these standards are suitable for every professionals. That is to say, they create a model to explain everything. It is too universal to be served as a good filter to select the most proper analysts. She or he may more marketable in any other business line.

12月 132008
 

Data Mining in Stock Market? Is it crazy? or is it just a hopeless try? Every mentor in mathematics and finance educates us that the stock market is too chaotic and sentimental to use mathematical models. Most of all gift rock scientists are concentrated in the study of interest of rates and fixed income securities. It sounds profitable to use mathematical and statistical models to predict the price of stock, but there are little successfull stories.

I know I might hold some academic doctrines, so I have interest to monitor any effort to try to forecast stock prices using data mining techniques. Some links from a popular data mining blog , Data Mining Research, are listed as follows:

12月 122008
 
During the many years I've been looking at customer data with SAS Text Miner, I've run into a few situations where I've wondered if I need danger money and here's why:

I had an interesting experience analysing some consumer security software Web search results of the 'less than savory' kind. Colorful language is common in the younger generation (18 yrs +/- ~6 yrs) Web sites, and colorful Web sites are just plain common. An innocent search can lead you to places you never intended to go. While you are likely to come across this kind of html data for text mining/text analytics at some point (like I did), I am always pleased to see that Text Miner creates its own segment for this data and I can treat it as noise and continue my analysis focusing on analyzing more useful trends.
12月 122008
 
I got an email yesterday from a government customer that asked a very good question:
It seems like Wordnet might be used to construct synonym lists [for SAS Text Miner] that could map terms "up" to more general synonyms possibly reducing noise and enhancing concept extraction. Has anyone in TM R+D ever considered using Wordnet?
Wordnet is a public-domain thesaurus/lexical database for English. It contains synsets or synonym rings that can show all related words to a given word. Since we allow the user to create synonym lists for SAS Text Miner, it seems reasonable to assume that some generic free source of a huge lists of synonyms might be beneficial. And in fact, we have looked at Wordnet before, but found that the reality does not live up to the expectation. In fact, using a generic synonym substitution usually turns out to generate worse results than doing nothing at all.

For why that is we need to look at when synonym substitution is helpful.

Continue reading "When are synonyms useful?"

Haiku from SAS R&D staff

 haiku, Matsuo Basho, misc  Haiku from SAS R&D staff已关闭评论
12月 102008
 

First prompts are silent.
Subsequent prompts loud and clear.
Now all prompts are heard.

Poem from R&D staff?
Yes. Rhyming sonnets were shakespeare-like complex;
they wrote Japanese haiku, showed as above.

The SAS R&D staff should complete some paper work in defects system before changing a code. They use informal descriptive language(HAIKUUU!) in the early stage. Chris Hemedinger, a senior software engineer at SAS, collected some haikus in his blog to show the humor side of SAS R&D staff. It’s interesting to cite one of the most famous haikus by Matsuo Bashō for comparison:

Old pond
a frog jumps
the sound of water

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12月 102008
 

Happy hearts and happy faces,
Happy play in grassy places–
-Good and Bad Children by Robert Louis Stevenson

I read this verse in W. Bennentt’s popular book, The Book of Virtues, during the bus-to-company time this morning. It’s interesting to read Stevenson’s Treasure Island, of course in Chinese edition when I was young.

Yes, it sounds “uncool”, –I went to work, with technical documents in my bag, and read a for-children book. A grown-up with childlike innocence? dare not say. I just read the book to fresh my mind and my English.

It snows little Beijing.

12月 102008
 

I just wanted to quickly introduce myself as the SAS R&D manager for SAS Text Miner. With my research-oriented background, I will be posting distinctly different types of blog entries than you will see from Manya, Barry and Mary.

I will be looking at detailed technical approaches and algorithms being researched for handling text data, i.e. the grungy details. So if you are more interested in a bird's eye view, you may want to skim over my postings. On the other hand, if you want to understand how things work, why we've decided to take the approach that we do, and what we are considering doing for the future, then tune right in. And I encourage you to make comments and suggestions. I am not tied to particular approaches, and I would love to find out "better" ways to do things that we may not even have considered.

Particular areas that I will be blogging about in the coming months include:
Continue reading "My wisdom (and lack thereof)"
12月 062008
 

Do you remember the old Faberge shampoo marketing campaign? "I told two friends about Faberge shampoo and they told two friends and so on and so on and so on ... " The one with the great visual to highlight viral marketing?

The onslaught of blogs and social media sites has initiated a huge power shift INTO the hands of customers. This can be good (if your customer is singing your praises), bad (if they are not), or more likely both.

The reality is that this represents a huge opportunity for businesses to use all available data in decision making to help you understand not only what your customers look like, but what they think. During a downturn in any economy, the customer is the last bastion, THE touch point to help you better understand what they think about your products and services.

Text mining is the technology that integrates structured and unstructured data to help you better understand your customers, enabling you to surpass the competition, save time and save money. While blogs and social media sites put power into customers’ hands, they also can empower businesses. Consider the JetBlue fiasco, which generated outrage across the Internet . The JetBlue CEO publicly apologized via YouTube! Since then, some 338,000 YouTube users have viewed the apology. They gave David Neeleman four stars for his performance. What also came out of this media was the opportunity to mine additional information – customer comments in response to the YouTube apology about the flight cancellations and peer ratings about those comments. All the makings of a “goldmine” for text and data mining for decision making. Current manual processes are inconsistent, costly and time-consuming, with information typically organized by functional area, not across the enterprise. Decisions get made in isolation. It's clear that companies must have automated processes to mine data to consistently to identify and quantify customer/product issues. Text mining is that technology. Businesses are rapidly embracing this technology. Are you one of them?
12月 042008
 
To take yesterday’s quote from a social media friend – “we live in a world of unlimited ideas”.  When it comes to analyzing text this quote would probably have to be my mantra. Analyzing text itself isn’t exactly a new idea.Government agencies have been doing this behind closed doors for a long time. What’s new is the ability to understand textual information while NOT being behind closed doors. Text mining/text analytics technology is available for commercial businesses to understand data about their customers, their competitors and much more. We use text for analysis, and combine related numeric fields. But even numbers can be saved as text strings and voice signals can be translated to text and used for better understanding of information. Imagine a bullet pushing the sound barrier. That’s what I picture when I think of The Text Frontier. We like to push boundaries – hard. And we’d like to share our experiences with you. We encourage you to join us pushing boundaries while sharing your experiences, or just watch us and comment. Whether you watch, wait or dive in with your thoughts, here’s something for you to think about:
2 + 2 = 4, but
two + 2 > 4
11月 182008
 
Treasures and memories and trash is what I found in my closet during a much needed cleaning. This was one of those deep cleans that only happens once every few years. I looked in every box, bag, and dark corner. You wouldn't believe the things I found -- treasures, memories, and trash. During one archeological dig into a plastic storage bag, I found a purse that had been long forgotten. As I am preparing it for the charity pile, I noticed a brilliant blue corner of cloth peeking out from inside the purse. I found this:

I do windows T-shirt
Do you recognize it? It is a SAS T-shirt from the early 90s. I got this shirt shortly after coming to work for SAS. (I'm guessing that it was about the time we released SAS 6.08.) Running SAS on Windows was new and exiting in the early 90s and this was a hot shirt. Finding this pristine, never-worn T-shirt started me to thinking. I can't be the only person with old SAS memorabilia stashed in a closet or drawer.

This post from Tom Hide on SAS-L assures me that I am not the only person keeping stuff. Tom has a copy of Guide to Using SAS 76. I've only seen pictures of manuals this old. See the pictures at the end of this post for a glimpse of old manuals as well as some other items from the past.



Do you have the oldest item or the most unique?


Let's have a little fun with our old stuff. What do you have? Is it old, funny, or cherished? Is it from a user group conference or from SAS? Tell us about it by writing a comment on this post. Show it to us by posting a link to a picture in your comment or by uploading pictures of your items to the sasmemories group on Flickr. If you just want to see the pictures from others, join the Flickr group at www.flickr.com/groups/sasmemories.
Continue reading "Treasures and Memories and Trash"