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  • Knowledge Base (Topics) - Aleksandr L. Blekh, Ph.D.

    Knowledge Base (Topics)

    ­

    I think that it is not too little, but it is too late. It is not too little simply because Microsoft is a for-profit company, which business model is not very much compatible with open source approach. So, nobody (well, at least, me) expects open source initiatives from Microsoft that would threaten their business model and status quo. It is too late, because Microsoft, as a company, has a long history of being very hostile toward open source ideas and movement – a strategy, which alienated a lot of open source users, developers and advocates. Now, after Microsoft realized that they can’t kill the movement and win the battle that way, they started to sound more and more friendly toward open source community and declare various corresponding initiatives. Basically, all this follows the well-known proverb/saying “if you can’t win them, join them”. So, considering the enormous damage that Microsoft introduced to relations with open source community, which can’t be undone, at least, in the near-term, I would say that their open source initiatives are too late.

    I would like to add some statistics to previous answers. Check the following projects: Ph.D. Completion by Council of Graduate Schools (http://phdcompletion.org) and The Path Forward Project (The Future of Graduate Education in the United States) by CGS/ETS (http://www.fgereport.org). For an overview, see executive summaries of the their full reports: http://bit.ly/1btNe4J and http://bit.ly/IvxLEr, correspondingly. I hope this is helpful.

    I will do my best to answer your question. For the context I will say that, having a BSEE bachelor’s degree, but experience in software development, I graduated from a similar degree program MCIS (Master of Science in Computer Information Systems). Desiring to enhance my understanding of the interrelationship between IT and business and also fascinated about research, teaching and consulting, I went on to pursue a Ph.D. in Information Systems degree, which is still in progress. My school has a MIS degree program, too, but the difference between MIS and MCIS in the curriculum is not that significant. Generally speaking, MIS, MCIS or similar degree programs are geared toward skillset on the intersection of IT and business, which means the most appropriate roles for a potential graduate are business analyst or IT analyst.

    About stagnation and growth career-wise. This very much depends on the environment you see yourself working in in the future. If you would like to work in highly-structured, corporate-type organizations, then having a MIS degree might be a valuable asset. If, on the other hand, you don’t like such kind of environment (which seems to be the case), then obtaing a MIS degree is of little value.

    I think you can approach the problem of stagnation and growth in two ways: by sharpening (honing, as you said) your skillset or by broadening your vision. From the skillset perspective, I don’t think pursuing a program such as MIS brings a lot of value. In my opinion, for this purpose, reading books mostly on software engineering topics (plus some MIS books) and doing real software development as much as possible (including open source) is the right way to go.

    Getting a MIS degree for the purpose of broadening a vision on the role of IT in business, I think is an overkill and would be a very inefficient use of your time and money. Additionally, other factors may play significant role: family obligations, kids, financial situation, if and how tuition is covered by your employer and much more. Returning to the idea of broadening vision, to me a better way to achieve this goal is to read a lot on the topics of interest (textbooks, books, magazines, blogs) and interact with people both online and offline (conferences, user groups). Additionally, there are self-paced online courses (even from top-tier universities), certificate programs and extended education courses.

    Considering your interest in IT Strategy for SMEs and Business Analytics areas and solution architecture/management roles, I would say that MIS program may provide some value (especially for corporate environment), but for the most part there are much more time-efficient and cost-effective options, which I mentioned above. These options, in my opinion, provide much more value for one’s efforts.

    I don’t know about meditation or hypnosis, but I can share these three relevant sleep wisdom facts/claims:

    1. Each hour of sleep before 11 p.m. (some say before 12 p.m.) is equal to two hours of sleep at the later time. This has been told me a while ago by a very good medical doctor (neurologist). One can probably find some data, hopefully, supporting this claim.

    2. Drinking coffee following by a brief nap is a powerful technique to providing your brain with significant rest in a short period of time. For more details, see my answer: Alexander Blekh’s answer to How should I cope with a lack of good sleep when I have a very important interview in two hours?

    3. It’s best to schedule long-term sleep intervals that match normal 90 minutes sleep cycles, that is 4.5 hours, 6 hours, 7.5 hours, etc.: Page on lifehack.org. Combining this info with other medical recommendations that advise an adult to sleep 7-8 hours daily, I arrived at 7.5 hours as an optimal number for myself. Obviously, everyone needs to approach these numbers on an individual basis and as a flexible guidelines.

    Here are some open source payment gateways:

    1. Omnipay (for PHP). Supported gateways can be found here.
    2. ActiveMerchant (for Ruby). Supported gateways and features: here.
    3. Website: CI Merchant, GitHub: repo (for PHP, but specific to CodeIgniter).

    I’m sure there are more, you just need to search longer. But these three seem to be active, stable projects, supported by solid companies (i.e., Shopify).

    Also, while not fully open source solutions, Braintree and Stripe are very popular among developers due to their rich functionality, good documentation and wide variety of multi-platform interfaces with various open source systems.

    Traditionally, principal components analysis (PCA) is used for dimensionality reduction (in a mathematical sense). However, if you care about latent constructs (factors) that your features (indicators or items, in factor analysis and latent variable modeling terminology) represent and measure, then exploratory factor analysis (EFA) and/or confirmatory factor analysis (CFA) are appropriate. For more on this, check my answer here on Cross Validated site: Page on stackexchange.com.

    Modeling a phenomena in terms of latent constructs (factors) has an additional benefit, since this approach allows further reduction in dimensionality and modeling at a higher level of  abstraction (but you still will be able to get information on  features/indicators, if this is needed).

    For open source, see List of video transcoding software.

    For cloud alternatives, see: http://aws.amazon.com/elastictra…, http://www.windowsazure.com/en-u…, http://zencoder.com/en/, http://www.encoding.com/aws.

    Here’s a nice review article as an icing on the cake for you: Does Amazon’s Cloud Transcoding Service Make Sense for You?.

    Consider the following startup programs (transcoding might not be included, ask):

    It seems that The CLOUDS Lab: Flagship Projects is the most popular cloud simulation software available. It is open source and it has advanced features. Other tools (both open source and proprietary) are available, some of them might have advantages in specific aspects. This can be seen in CS research community discussions (i.e., Page on researchgate.net), comparative analysis research papers (i.e., Page on ijarcsse.com and Page on thesij.com) and presentations on the topic (Survey on cloud simulator).

    I would argue that the approach “We are <…> for <…>. Just better.” suggested by Ivan Rasic should be taken with great caution, if at all. I understand the idea behind this approach. It has some merit. But, despite this and its popularity, I have reservations about it, nevertheless, due to:

    1) Potential lack of domain/industry knowledge.  A lot of people might not know “pretty notorious” names of products or  startups. For example, I heard a lot of “we are Kayak for <insert  market here>” statements, but, despite hearing the name a lot, for a  long time I had no idea what Kayak actually does; simply because it was  out of my domains of interest.

    2) Potential impression of lack of innovation.  It might make people (including VCs) think that your startup is just a  slightly modified version of that “pretty notorious” startup, thus,  lacks serious innovation element, and, therefore, not interesting as a product for consumers/customers and investment for VCs.

    The list below is not comprehensive by any means, but should be a good start. I approach learning data visualization (and any other data-driven domain) along the following dimensions:

    For theory, read books:

    For trends, news, resources, opinions, etc., read blogs/sites:

    For mastering skills, practice data visualization, using tools:

    From the MATLAB page: “MATLAB® is a high-level language and interactive environment for numerical computation, visualization, and programming”. Obviously, MATLAB as a language is focused on mathematical models and methods, hence the name. MATLAB is similar to Wolfram’s Mathematica, while having some differences.

    MATLAB is a specialized language for scientific and technical computing, while C++ and Python are general purpose programming languages. As in general between closed source and open source solutions, there is an advantage of having more freedom in using the general purpose languages, sometimes at the price of lacking development in some very specialized areas. However, both C++ and Python currently have a wide variety of actively developed and supported third-party libraries, usually open source, for scientific and technical computing.

    Finally, MATLAB is not free. Commercial and academic licenses are pretty expensive. Also, it is important to take into account environment in your potential career paths and/or industry domains. If specialized software, like MATLAB or Mathematica, is widely used there, you might want to consider learning it.

    While I’m not fond of your self-classification (which is relative, by the way), I will try to answer your question, as EVs and alternative energy are some of my areas of interest.

    I’m not aware of pricing specifications of a Tesla Supercharger station and I don’t think Tesla will be distributing the stations outside of their network (I assume here that you didn’t imply building a Tesla Supercharger station, based on their open patents). However, there exists an alternative way.

    Consider the following charging station: Terra multistandard DC charging station 53 CJG, designed and produced by ABB: ABB Electric Vehicle Charging Infrastructure. In addition to major charging standards, such as Combo DC (CCS) and CHAdeMO, it supports AC charging, which I believe Tesla uses (you might need an outlet adapter, though). Caveat? If you’re located in US, it is not currently available in this country (but I assume it will be, eventually). However, if you happen to live in Europe (or other location, where ABB distributes their products), this caveat doesn’t apply.

    Price-wise, I’d estimate costs, based on publicly available information for Terra 53 CJG’s smaller sister and extrapolate the numbers, considering a single unit order. Here’s the information: ABB introducing new DC fast-charger in Europe for €9,988. For more accurate and up-to-date numbers, I’d just call North American division of ABB. Hope this helps.

    Disclaimer: I’m not an ABB representative, not connected with ABB in any way and have no vested interest by referring to this company (they just seem to a leading company in this industry, but other companies, I’m not aware of, might also be active and advanced players in the market).

    Wow, close to 200 people, waiting to know the answer to this question and no answers so far… Well, I guess, I will jump in and be the first, as like all those people, I’m also a little bit curious about the topic.

    In order to answer this question reasonably well, I’ve decided to perform a brief research, pulling information from large enough number of different sources. My selection followed convenience random sampling, so it’s not perfect, but I think that it is good enough in terms of representativeness for such an informal and small study.

    First, a couple of disclaimers: 1) “Annual salary and bonuses differ broadly in this field depending on the size of the VC firm and specialization” (the citation is from [1]); 2) the following numbers are largely focused on VC, not PE segment; 3) sometimes terminology is fuzzy (depending on a firm, analyst and associate have somewhat different areas of responsibilities and, thus, different compensation structure and numbers).

    Having said that, let’s get to the numbers, as follows (numbers reflect the US market, I expect other markets to be different, based on location). Typical compensation structure for VC analysts and associates, as far as I know, includes salary, bonuses, sometimes profit sharing and, less often, a carry from deals/investments.

    ————————-————————-————————-—–
    Source => Compensation (Salary + Bonus => Median/Avg)
    ————————-————————-————————-—–
    Investopedia [1]          =>   $86,000 – $250,000  => $170,000
    SimplyHired [2]         => N/A                                   => $111,000
    Forbes/WSO [3]         => $116,000 – $197,000    => $157,000
    Glassdoor [4]               => N/A                                  =>  $95,000
    PayScale [5]                 =>   $59,000 – $174,000    =>  $96,000
    WSO Direct [6]            =>   $80,000 – $250,000  => $153,000
    PhD Career Guide [7] =>  $85,000 – $200,000   => $143,000
    ————————-————————-————————-—–
    Average across sources                                      => $132,000
    ————————-————————-————————-—–

    References

    [1] Become A Venture Capital Associate
    [2] Venture Capital Analyst Salaries
    [3] How Much Do Wall Streeters Really Earn?
    [4] Salary: Venture Capital Analyst
    [5] Associate – Venture Capital Firm Salary
    [6] Venture Capital Salary, Average Venture Capitalist Compensation
    [7] Venture Capital

    Basically, any CRM software contains (or, at least, should contain) campaign management functionality to a varied degree of comprehensiveness. Talking about open source software, the first name that comes to my mind is SugarCRM, a commercial open source CRM software. My understanding is that campaign management features are not included in SugarCRM Community Edition, but present in all commercial editions (click on Editions Comparison Chart button on the bottom of this page: CRM Software Packages and Pricing). Having said that, there are multiple extensions (add-on packages/modules) that provide campaign management functionality: SugarForge: Software Map. Many of them can be used with the Community Edition as well (see details by clicking on the Expand link in each extension’s description).

    If you’re interested in open source CRM software, other than SugarCRM, there are quite a few, but this article provides a good starting point: Five open source tools to help you manage your customers.

    Another relevant interesting and promising open source software is pimcore (Multi-Channel Experience and Engagement Management Platform), which combines multiple functionality domains, including Open Source Marketing Campaign Management.

    Additionally, there exist niche open source CRM software, which includes campaign management functionality. An example of such software is Open source constituent relationship management for non-profits, NGOs and advocacy organizations. If you have meant this by your question, have a look at CiviCRM.

    Finally, in regard to the UNICA software, which is now an IBM product, called IBM Campaign (Formerly Unica Campaign – IBM Campaign), all I can say is: 1) it is a proprietary product, which is not open source software; 2) it is probably very expensive, and likely includes purchase or subscription charges as well as support charges; 3) the only reasons IMHO it would make sense to consider such product are prior heavy investments in relevant IBM software, such as IBM Analytics, and a need for integration with it (however, it might be done via APIs).

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