Data Mining Lecture – – Data Analytics life cycle (Eng-Hindi)



hello ma'am of the history of my explained data analytics lifecycle so first of all a data analytics can use of that so data mining precision jump in Big Data – Aniki various sources visit your data layers that means big data like X file audio file video file so here big determine quiz problems of the issues okay to go issues to song chronically a make cycle fall over me so here is the data analytics lifecycle data analytics lifecycle my first of all start console there to start procedure is of discovering a discovery that means data Casilla we're like sources and what are the tools that are used for finding the sources raw data console on my raw material to e sorry discovery if or no picks next one is data preparation ok data preparation anything appear the performer extraction loading and transformation dopey data make choice like raw data to e huskar who skip preparation yogi by using of various tools like SQL and hydro and etc tools to be used on a most famous tool a SQL so data preparation Jonnie a memory passuk particular data are there now is the model planning so modeling actually can modern learning is the juubi data I am Pamela Harriman who's q4 performed I have made like at the methods apply Kearney and so Joe Bianco research are you who's related modern planning again so what are cunning men first of all though Jakob Joe data or the busca proper you Sokka and the model will be planned so a gauge of modern running ok a busca actually implementation mallanna and to scale your modern building here is like an order building make yoga cage OB data of APIs and E say joy up user who's a small test applied on a test cases and actual modern building will be done ganging up up go Joe Bonamassa Bonneville bunch ok so next one is communicate the results of gay joke actually burn sugar who's Cooper results Yannick a test applied on a validation supplying ocupada oka kike will be kissing be data the implementation other project requires a super test cases apply gauges and validations for converted to validations perform case and get communicate results now last one is the operationalize now everything is ready to operationalizing half a after project to deliver connect in between of the audience jana key approaches audience can beat me a project learn and father co launch gardener so now operationalize me up to audience say like you will get the results or other push PR the problem here the opposite same cycle perform only again discovery data preparation model planning water printing communicate results and operationalize so a circle actually charge bielarecki so now they can get data analytics canakya cycle next sub secure alls anything joe users of the Yuppie respect holders of the two key roles is carry any key concept persons is my actually count birthday or kiss key importance year cycle make the other so let us see the key roles of the data analytics as omne analytics partner medica hysteresis cycle perform major the output cycle to successfully complete curve negative jus key roles Yankee Joe persons is my involve okay both total six key roles in you have in you way user first row follies users TCP project go successfully complete clinically octopus end users only for end users is there is a project I use contain put a penalty or Pospisil potentially the give after project car Monacelli and what are the changes required next one is projects on sponsor obviously TCP project poker of course sponsor say the funding is required who funding Janicki like financial or financial support model support job yoga booga project sponsor and project manager project manager any ECB project to handle technically a multi who's team a project manager of the the project manager handle Auriga kik-kik newirth kidney time a complete turner and the what will be the quality of the project expected next one is business intelligence analyst obviously up.wake intelligence support on hae Yannick is the record data discovered Kerrville or his therapist queue per output techniques applied early to scale it with octopus a business intelligence analyst changing to unique important part next one is data engineer obviously key pure project main technical person is also necessary technical person discovers data database knowledge obviously mining knowledge or duping technical knowledge requirement Scalia passing Delta engineer monitoring a next one is database administrators up Juba data of Koga boo data business to Roga whose database to handle category octopus a expert on Australian database curve just computed database administrator of a database admin administrator of course support caraga database environment my RK project mr. si con carne or analyst mr. silica so this is also important person next one is data scientist data scientist Janicki overall project maker in bigger problem already PCBs are the problem and to ik over all expert on natural it is computed data scientists even with the expert and business intelligence case sorry problems to solve karna and so scaling up who is person necessary a so yet is six key persons gingka data analytics project main owners early and they are necessary for the project to become successful so yes our data analytic data analytics explanation thank you so much for watching my video don't forget to subscribe valeriy domain

12 Comments

  1. Magicumbr said:

    it will be good if camera isn't shack

    May 22, 2019
    Reply
  2. Ritu Bhatt said:

    Sir BUSINESS INTELLIGENCE pe video banao

    May 22, 2019
    Reply
  3. Farwa Naqvi said:

    Please give some examples of models? As if I see it from DWH perspective then model development is totally a different thing.

    May 22, 2019
    Reply
  4. sravya sridhar said:

    It'll very helpful if subtitles are added 🙂

    May 22, 2019
    Reply
  5. rushab zade said:

    Please make a video on hypothesis testing

    May 22, 2019
    Reply
  6. yash gupta said:

    Appreciate your efforts would been more happy if u would had provided a bit more of description of each stage now u being just lyk college professor who say the see thing using different words

    May 22, 2019
    Reply
  7. The Anonymous said:

    Thanks Sir

    May 22, 2019
    Reply
  8. RISHIKESH POTE said:

    hello Abdul sir it was a great explanation about data analytics life cycle Can you provide me a link of a power point presentation about this topic.
    Thank You…!

    May 22, 2019
    Reply
  9. Shantanu Khanna said:

    i had done msc.maths. which course should I pursue to become data analyst?

    May 22, 2019
    Reply
  10. Abhishek Beck said:

    lachand

    May 22, 2019
    Reply
  11. Tarnnum Mesaniya said:

    Easy I Like it

    May 22, 2019
    Reply
  12. khyati kansagara said:

    Easy explanation…

    May 22, 2019
    Reply

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