Tag Archives: Analyst

[repost ]Big data requires a new breed of analyst



Everyone is talking about big data. Big data is a big deal, especially in data-intensive industries such as cybersecurity, finance, health care, marketing, transportation and energy. And many of us are already familiar with the three V’s of big data – volume, velocity and variety. But the key question is: How do we extract big knowledge from big data?

The answer to this question is partly through analytics, which is a growing field within various sectors. Some people look at data analytics in terms of educating future “data scientists,” while others are exploring business analytics through educating a new kind of “business analyst.”

Skills required
Regardless of what you call them, the new breed of analytics specialists need to have a combination of skills, including statistical techniques, applied mathematical methods, advanced machine learning algorithms, data visualization, and business and communication skills.

We often can find analysts who have the technical savvy, but they lack the business and communication skills to explain to managers and executives how results from analytics can inform organizational decision making.

The new breed of analysts must also possess the experience and instinct for knowing whether the analytics results have gone awry or whether they seem to have produced some valuable results. Recent MIT conferences on big data have talked about this value of intuition and making smarter decisions.

The Partnership for Public Service and IBM’s October 2012 joint report titled From Data to Decisions II talks about the importance of tapping a mix of people with different backgrounds and strengths. The report highlights the importance of an analytics team approach that takes into account background and experience. This approach should lead to a credible set of analytics results that focus on the goals and objectives for that enterprise. Having a multidisciplinary perspective should provide great value to the analytics team.

New academic programs for analytics
Universities and colleges are offering new degrees and programs in analytics. The Master of Science in Analytics program at North Carolina State University has been a model for most of these analytics programs and has recently doubled in size due to its popularity. Other programs include:

  • The University of Maryland University College – online master’s in analytics (plans are underway to start this summer).
  • Stevens Institute of Technology – master’s in business intelligence and analytics.
  • New York University – master’s in business analytics.
  • Ohio State University – advanced analytics center, formed with IBM in November 2012.

‘Instinct’ a factor
It has already been shown that business analytics can inform decision making (see the 2011 study conducted by Bloomberg and SAS). But how can we ensure that the next generation of analysts is prepared to extract the “big knowledge” from the “big data”? Certainly, having some background in knowledge discovery techniques as part of the analytics team may provide some helpful way to look for hidden patterns and relationships in the data and text. But how do we know that these relationships are worthy of further analysis and exploration? How does “instinct” factor into the results?

It’s a Catch-22: You want analysts with technical and organizational experience, but new analysts who have the most up-to-date technical training often haven’t had enough experience to best understand the organizational setting. Thus, the team approach with a mix of background and experience will help address this concern in terms of building “instinct” into the analysis.

Other ways to instill instinct into organizational decision making through analytics are:

  • Rotate analysts’ assignments within the organization so that they can better understand its functional components.
  • Assign senior-junior analyst mentoring so that the younger analysts can learn from the experiences of others.
  • Don’t take an answer for granted – bounce the analytics results off of others in the organization to check the validity and reasonableness of the results.

Bio: Jay Liebowitz is the Orkand Endowed Chair in Management and Technology at University of Maryland University College. His newest book is Big Data and Business Analytics.


在stackoverflow.com 看到的很有趣的讨论,程序员,软件工程师,和软件开发人员的区别。


What’s the difference between programmer and software engineer?



在IBM有很清楚的区分,比如 IT Specialist ,IT Architecture,Software engineer,Software architecture,Technical solution,Technical support 等等。



n some countries and states (European countries, Canada, as per Kena’s comment, and Texas, as per Tony BenBrahim’s comment, see comments for other examples), the title “engineer” is limited to people with an engineering degree. Depending on where you found the job description, “software engineer” may mean “a person who has studied software engineering or computer science,” while “programmer” probably means “a person who knows how to write code.”


programmer = we do not have many technical employees and need someone to “program” something; for example a law firm

developer = we are a tech-savvy product or services company and need someone to work on internal or back-end tools; for example a bank or consulting company

engineer = we are a software company and need someone to work on one of our products; for example Adobe or Microsoft

There are thousands of counterexamples, but in general, I would be skeptical of any company looking to hire “programmers”, whilst I would look fondly upon a company hiring “software engineers”. “Developer” doesn’t really carry a connotation.


Officially I believe a Software Engineer is more qualified in the software development lifecycle as a whole (requirements, analysis, design, testing, team management etc etc), whereas a programmer/developer is the more Computer Science track.

Unofficially the HR people at many companies have no idea what they’re talking about and you have to go by job requirements or even the interview!


The terms are different, and they refer to differing expectations.

Usually, “Software Engineer” is a superset of “Programmer”.

Programming computers is PART of Software Engineering; but it’s by far not all of it.

While programming requires a knowledge of computer languages and algorithms and data structures, all of which are very important, software engineering also involves knowledge of projects, maintenance requirements, documentation standards, software design, etc. The things that are involved in successful software projects that are NOT actual programming.

For me, a critical distinction has always come with Software Patterns. I’ve never met someone who was “just” a programmer who had a grasp on what they are, and why they’re good. Conversely, most (albeit not all) Software Engineers that I’ve known and respected have had a good grasp on Software Patterns, and understand why they’re such a good idea.

In general, the way I tend to think of it is this: programmers program solutions. Software engineers take a problem, and (usually) use programming to solve it. The difference is that at least part of the responsibility for figuring out WHAT the solution is going to be falls on the Software Engineers.


  • Programmer: Coder. Code Monkey. Clickity-Clack, Clickity-Clack.
    Usually 0-5 years experience
  • Developer/Analyst: Gathers requirements, designs and implements applications, researches technologies, etc.
    Usually > 5 years experience
  • Engineer: Designs and implements components and frameworks for Developers and Programmers to use.
  • Architect: Designs and oversees the implementation and integration of system wide initiatives.