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383 topics · page 27 of 39

  1. 261

    Data Imputation

    Data Imputation is majorly used in Data Science domain. ‘Imputation means, fill missing data.’ Data Imputation normally comes into play so business rules can…

  2. 262

    Data Disambiguation

    ‘Disambiguation means to make something clear and understandable.’ We all know the word i.e., Ambiguous which means something which is unclear especially whe…

  3. 263

    Data Fusion

    Data Fusion, another term overlapping with many other already in-place terms. ‘Data Fusion is about pulling same nature of data from multiple source systems…

  4. 264

    Integration Hub

    Integration Hub is normally confused with datastores like Data Warehouse, Data Lake, Data Lakehouse etc., which is not correction. Integration Hub is a singl…

  5. 265

    NLP

    In this era, social media has surpassed every medium to generate data. Social media is not only about writing messages, it also about sending audio or video…

  6. 266

    Data Strategy vs Data Management

    Initially, I planned to write two separate topics on Data Strategy and Data Management but as both are huge areas and the aim of this book is not to train pe…

  7. 267

    Hype Cycle forData Management

    Hype Cycle of Data Management is confused with Data Management which is not correct as one is about solution and other about enterprise. Hype Cycle of Data M…

  8. 268

    Modern Data Stack

    To make it easy, first must understand Traditional Data Stake (TDS). Now, what is TDS lolz 😊. TDS is your On-premises solution which can include any kind of…

  9. 269

    Why to define Success isimportant for Data Solution

    What does "success" mean, and why is it so important to have a clear idea of it when dealing with data solutions? Success is like reaching a goal or doing so…

  10. 270

    PVP Approach

    Yes, you are right, you might not have heard about this approach. It is something new which Myself is working on. Let’s decode it….. Productionizable Viable…

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Learn from I Am Datapedia!

Every topic of the book, readable below, with a search box to find the one you need — 383 of them with a self-check at the end.

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The source: I Am Datapedia! — Series of ‘I Am Data!’ — co-authored with Bill Inmon & Marco Wobben. By Mustafa Qizilbash.