Knowledge Hub
Learn free, at your own pace.
Self-paced learning from the trainer’s own published work, with topic self-checks — alongside, not instead of, our expert-led trainings.
Topics
383 topics · page 26 of 39
251
MPP(Massive Parallel Process)
We all have heard about MPP (Massive Parallel Processing). In the current era, consumption and serving layer without MPP capability cannot survive. MPP is mo…
252
Canned Data
Canned Data is something which is readily available at one click. A dataset prepared based on business requirements i.e., if required in pre-aggregated forma…
253
Canned Reports vs Adhoc Reports
Canned Reports Just like Canned Data, Canned Reports has the same approach where static designed reports are built for non-tech savvy stakeholders, who just…
254
Multidimensional eXpression(MDX)
Before we understand MDX, we must first reassemble our memories with respect to OLTP and OLAP. We know what these are, both are explained as separate topics…
255
Data Drift
Data Drift concept is used in Data Science practice, and it is one of the most expected behaviors in every data modelling. One must have automated ways to ke…
256
Concept Drift
Concept Drift is used in Data Science practice, and it is mostly unexpected behavior in data. One must have automated ways to keep tracking and identifying C…
257
Scope Creep
Scope Creep is a known term among Project Management but is worth discussing it among data folk as scope creep can also impact data architecture and data mod…
258
Data Discrepancies
Data Discrepancies are confused with Data Errors which is not true. Data Errors are searched, identified, and fixed based on Data Discrepancies. ‘Dictionary:…
259
Data Skew Issue
Data Skew Issue is one of the main hidden culprits for query performance 😊. It is normally referred to as Skewed data distribution which is used in Data Sci…
260
Data Coupling
Coupling is a parameter dependency approach used cross software or cross systems. This approach is used when there are more than one software or system is in…

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