What is a Data Warehouse?

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  • čas přidán 21. 07. 2024
  • Learn more about Data Warehouses → ibm.biz/data-warehouse-guide
    Learn more about Data Marts → ibm.biz/data-mart-guide
    Blog Post: Cloud Data Lake vs. Data Warehouse vs. Data Mart → ibm.biz/data-lake-vs-warehouse...
    Watch "Data Warehouse Q&A in 1 minute" video → • Video
    ► Check out IBM Cloud Pak for Data → ibm.biz/prod-ibm-cloud-pak-for...
    ► Check out IBM DB2 Warehouse on Cloud → ibm.biz/ibm-db2-warehouse-on-c...
    What’s is a data warehouse, and how does it compare to a data mart and data lake? Is a data warehouse solution only for large enterprises?
    In this lightboard video, Luv Aggarwal with IBM Cloud, answers these questions and many more as he breaks down what a data warehouse is and the benefits it can provide for an enterprise.
    Get started on IBM Cloud at no cost → ibm.biz/create-ibm-free-tier-acct
    Subscribe to the IBM Cloud channel to be notified when a new video drops → ibm.biz/subscribe-now
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Komentáře • 25

  • @keyboardrambo
    @keyboardrambo Před 3 lety +60

    Can we just take a moment to appreciate the guy's ability to write right to left in English? That is amazing!

  • @vidyaanvekar
    @vidyaanvekar Před 2 lety +5

    Just loved the way you explained. Totally amazing.

  • @adamjgb
    @adamjgb Před rokem +3

    Great job making a complex topic easy to understand.

  • @chillbro2275
    @chillbro2275 Před 2 lety +5

    Finally understand what a data warehouse is! Thank you.

  • @parsarahimi71
    @parsarahimi71 Před 3 lety +20

    Solid explanation ... A minor suggestion though ... how about describing the acronyms (e.g. ETL, ERP, ...) a bit so the context could be better understood ...

  • @jamespoda5621
    @jamespoda5621 Před 2 lety +1

    8 minutes i learnt a lot cheers IBM

  • @djordjepetrovic2365
    @djordjepetrovic2365 Před 2 lety +2

    Great video, thank you very much sir!

  • @francishubertovasquez2139
    @francishubertovasquez2139 Před měsícem

    In the g type tech environment things were oriented to be predictable, but in the space and microthings environment, things can be unpredictable sometimes that's why adaptable or adjustable approach are needed. Because those areas necessitates high computing capacity meaning a combination of predictable and non predictable adaptable systems are needed. Theres space warehouse materials storage facilities as an example of plug in plug out applicable systems to the problem to solve per se meaning not only computing mechanisms should be improved but also the equipments and materials to meet the focus on hand.

  • @ChanceMinus
    @ChanceMinus Před 3 lety

    Great job! Thank you.

  • @arvinmisunderstood
    @arvinmisunderstood Před 3 lety

    Excellent video!

  • @francishubertovasquez2139
    @francishubertovasquez2139 Před měsícem

    My idea is like this, as computation branches in capability, so are the supporting structures in modern warehouses including it's materials and equipments and every inventory and specifications of items stored there improve catering to various products, those ware houses can be potential semi manufacturing areas convertibles in the near future due to variety of inventory materials stored because of famililiarization to products varieties, needing only some additional equipments and structural area changes as warehouses to semi manufacturing to be structural models for computer encoded manufacturing area structure designs in a 3d like computer structure design.

  • @francishubertovasquez2139
    @francishubertovasquez2139 Před měsícem

    You're complete with data structure congrats. Can that meet the evolving products demands and common customer orders and big ticket items orders, are those data's able to interact with each other when it comes necessity of previously worked information product type wise with the new market demand products, specifications, trends and augmentations of products ingredients to beat the competition, how those data's able to relate to latest developments and self diagnose the lacking things needed and for augmentations tech wise or product designs to make it big worldwide in a progressive computerized environment of focused applications.

  • @jamesbenedict6480
    @jamesbenedict6480 Před rokem +4

    Hi, you mentioned about data being sourced, cleaned and transformed to load the data into the Data Warehouse. Where do you recommend the data cleansing need to take place? Is it in a separate Staging area? Or within the Data Warehouse itself? Where? Thanks!

    • @Eric-fx8is
      @Eric-fx8is Před rokem +2

      As large amount of datasets are usually being stored in DW, the Data lake or we say ODS(original data store) is more suitable and powerful for dumping raw, structured and unstructured data in and for cleasing and integration.🌹 FYI.

  • @nickynick1014
    @nickynick1014 Před 3 měsíci

    Well done.

  • @abhishekghosh5550
    @abhishekghosh5550 Před 2 lety

    Thanks Luv!

  • @boniamd4844
    @boniamd4844 Před 3 lety +4

    pls do DWH vs MDM comparison next :)

    • @IBMTechnology
      @IBMTechnology  Před 3 lety +1

      Thank you for the suggestion, we will look into this! Stay tuned!

  • @francishubertovasquez2139
    @francishubertovasquez2139 Před měsícem

    Warehousing, company owned fixed to company rules, multi use warehouse capable of catering to multiple companies such as in holding companies as I analyzed only can that be structure adjustable as modern warehouse type like for example an NBA games stadium whose floor is adjustable to other sports or shows such as concerts, with products storage in modern warehouse type can the wirings plugs and other attachements in there be products items customized with it's systems inputs models product specific tailored for such such as adaptable tailored products operating systems, meaning if AI connected, AI's adjust to products brought in per se not the other way around.

  • @asadanees781
    @asadanees781 Před 2 lety

    Great

  • @jamesm.3967
    @jamesm.3967 Před 5 měsíci

    Enterprises..😅 aka businesses.

  • @vamsiakula653
    @vamsiakula653 Před 3 lety

    My 1st comment