Big Data & Analytics Orientation Recording - Digital Vidya

Big Data & Analytics Orientation Recording

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There are 20 comments


  • 8 months ago

    santhosh   /   Reply

    I missed the Live session,so I have a question here.you said that it wont be easy to get in for freshers in R unless they do a project or so can we get some support from you to do projects on R?

  • 8 months ago

    Kapil   /   Reply

    Yes. Just Knowledge is not sufficient. I would suggest that you do multiple projects. In our Course, we will give you 2-3 projects with different datasets. You will have to complete at least one project as part of your course curriculum.

  • 8 months ago

    Akhilesh Kumar   /   Reply

    I would like to go for R-python data analyst programm

  • 8 months ago

    Akhilesh Kumar   /   Reply

    I am having approximately 6 years in banking operations looking for data analyst programm please suggest me which module would be best for me.

    • 4 months ago

      Shweta Gupta   /   Reply

      Hi Akhilesh,

      We seem to have missed you question earlier, sorry about that. A large number of Banks and Insurance companies are heavily invested in SAS. Starting with SAS may be a great option with your domain knowledge. I have also compiled some interesting facts on the different data anlaytics tracks, that may help you with your decision.
      http://www.digitalvidya.com/blog/data-technology-landscape-evolution-of-data-sciences/

      All the best with your learning !!

  • 5 months ago

    M.Santhosh Kumar   /   Reply

    As i am a fresher will i get a job in this..

  • 5 months ago

    Uday   /   Reply

    I am currently working in data analytics in an mnc. What we do here is we analyze consumer reviews and make reports to the customer regarding product positives and negatives. Can i see my future in data analytics with the experience i have

    • 4 months ago

      Shweta Gupta   /   Reply

      Hi Uday, Absolutely, you have already started to see how data needs to be analyzed. I would encourage that you build the right skills and equip yourself with the methods and tools to improve your data anlaytics capability (for instance how can sentimental analysis b applied and used here).

      We have compiled some interesting facts on the different data anlaytics tracks, that may help you explore for yourself on where do you want to skill yourself,
      http://www.digitalvidya.com/blog/data-technology-landscape-evolution-of-data-sciences/

  • 2 months ago

    Nilesh   /   Reply

    Hi,
    Myself Nilesh working with an event management company where there is a lot of unorganized data which creates a problem in the final execution so I found out it as a problem and was keen on learning analytical technique course from Digital Vidya as also I am a non programmer and also needed information if I do this course in what other sectors can I get job after completing this course.

  • 2 months ago

    Shweta Gupta   /   Reply

    Hi Nilesh,

    Data is a very important aspect of “Data Science” and it is the fact that the various functional areas who own the real data, in roles of operations/sales/marketing/finance/logistics, must have the power of data analytics.

    You are seeing for yourself that wanting to run operations and execution efficiently in your event management company, you are struggling to put together your data. I would like to draw your attention to the 2017 European Data Science Salary Survey, where 70% respondents have chosen Excel as their tool of choice for solving data analytics business problems.

    We have created a curriculum to specifically fulfill this need, where people would leverage the power of Microsoft Excel, and Business Intelligence tool, PowerBI. This is one of our most popular courses with people from all walks of industries and functions.

    This applies to any industry, you will be able to position yourself in all kind of domains.

  • 1 month ago

    Yogeswaran   /   Reply

    I am having 8 years of Project Management/consulting in Pharma domain with M.Pharmacy degree holder.Whether I will be preferred for healthcare analytics role and the scope in the current market

  • 1 month ago

    Shweta Gupta   /   Reply

    Hi Yogeswaran, The domain knowledge of industry is definitely a very strong component for an analyst. I would ask you to look at two options:

    a) SAS is a pretty popular software used by the large healthcare/pharma industries. Do have a look at the client list on their site
    https://www.sas.com/en_us/customers.html#filterlist=industry3150
    Also use the job portals to see the job requirements, as that continues to change based on the current demand.

    b) Python as the choice of language for data science, as this is definitely going to be very forward-looking in terms of adoption across different sectors.
    Also, read up this article:
    https://www.oreilly.com/ideas/how-data-science-is-transforming-health-care

    Hope this information helps you.

  • 2 weeks ago

    Rajesh Premani   /   Reply

    * I’m a non coding professional at the moment, but would like to get into Python for Big Data and Predictive Analysis (catering to the Media Industry) immediately after I’m done with the Excel course. Please guide me on the road-map for getting into Python (eventually), being a non programmer. FYI and records, I have already enrolled for the Excel course that is due to commence 0n 23rd of Dec 2017. Many thanks!

    • 1 week ago

      Shweta Gupta   /   Reply

      Hi Rajesh,

      I have a very simple set of steps listed here for a complete non-programmer to start with Python programming.
      http://www.digitalvidya.com/blog/use-jupyter-notebook-using-python/

      See if you can follow this article (and take help of a friend from Python background, if needed). Once you have a comfort level, then you can start to solve more problems and ready to sign-up to learn Data Analytics using Python.

  • 2 weeks ago

    Trupti   /   Reply

    I have Manual product functional testing experience of 15 years. Looking for a change in career. Data Analyst can be one option. How to proceed with this. what do you suggest.

    • 1 week ago

      Shweta Gupta   /   Reply

      Hi Trupti,

      I know that 15 years of manual testing may have moved you away from programming. Critical question to you is – Are willing and ready to put in all the effort to now pick up programming?

      I have a very simple set of steps listed here for a complete non-programmer to start with Python programming.
      http://www.digitalvidya.com/blog/use-jupyter-notebook-using-python/

      See if you can follow this article (and take help of a friend from Python background, if needed). Once you have a comfort level, then you can start to solve more problems and ready to sign-up to learn Data Analytics using Python.

      SAS is another option where you may take to programming a little slower.

  • 2 weeks ago

    Sanchit Srivastava   /   Reply

    Hi, I am a graduate in b. Com,currently I am working as a team member in BPO for MNC, I want to boost my career as a Data analyst,so that I can find more and better career opportunities for my self.. Please prefer me a career option I can have in this….

    • 1 week ago

      Shweta Gupta   /   Reply

      Hi Sanchit,

      I would advise you to do the course of ‘Analytic Techniques and PowerBI’, this will get yo the skills to find roles as data analyst or BI (Business Intelligence) with advanced Excel.

  • 5 days ago

    anurag   /   Reply

    hi
    can you suggest which data analytics tool be helpful to learn to work in energy sector.

  • 3 days ago

    Shweta Gupta   /   Reply

    Hi Anurag, I will draw your attention to these articles so that you can understand the work for data analytics in the energy sector.
    1 – Read on ‘Inside the data science toolkit’ – You will typically find Big Data technologies and Python programming becoming big
    https://www.cio.com/article/3052934/big-data/how-data-science-is-changing-the-energy-industry.html
    2 – AutoGrid like players use Big Data storage to collect all data from the IoT devices (Internet of Things) and then crunch data using the Data Science machine learning algorithms.
    http://fortune.com/2016/05/24/big-money-in-energy-big-data/

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