Understanding the Division of Labor between Analytics Applications and DBMS
Fabian Pascal 9/29/2017 Post a comment
Those who ignore data fundamentals will always risk costly mistakes and inhibit their own progress towards analytics goals. Here's why.
Don't Conflate or Confuse Database Consistency with Truth
Fabian Pascal 9/1/2017 2 comments
In the database context both truth and consistency are critical, but they should not be confused or conflated. DBMSs guarantee database consistency with the conceptual model of the real world they represent. On the other hand, a DBMS cannot and should not be expected to ensure truth.
Structure, Integrity, Manipulation: How to Compare Data Models
Fabian Pascal 8/1/2017 2 comments
Is that new data trend actually something that you really need, or you could risk being left behind? Or is it just a buzz word or a fad?
Data Meaning: Analytics vs. Data Mining
Fabian Pascal 6/30/2017 4 comments
Can you reconstruct the meaning for a database when you have no documentation? Here's a deep dive.
Redundancy, Consistency, and Integrity: Derivable Data
Fabian Pascal 6/1/2017 16 comments
Analysts should not take database consistency for granted. Here's why.
The Necessity of Foreign Keys
Fabian Pascal 5/3/2017 9 comments
A proper understanding of data fundamentals requires the understanding of the importance of keys and primary keys. This time we take a look at another important type of key -- foreign keys.
Why You Always Need Primary Keys
Fabian Pascal 4/5/2017 8 comments
Database pros should heed this warning: if you ignore that primary keys are mandatory, you can wreak havoc with inferences made from databases, including in analytics.
The Trouble with Data Warehouse Analytics
Fabian Pascal 3/2/2017 11 comments
Data warehouses are essentially databases biased for particular data applications and against others. They are rooted in poor database foundation knowledge and logical-physical confusion.
Outsmarting the DBMS: Analysts Should Beware
Fabian Pascal 1/31/2017 1 comment
Analysts should avoid relying on techniques that undermine the soundness of database design.
Data Sublanguages, Programming, and Data Integrity
Fabian Pascal 12/23/2016 11 comments
The emphasis on coding in place of education obscures and disregards the core practical objective of database management to minimize programming.
Prediction, Explanation and the November Surprise
Fabian Pascal 12/5/2016 7 comments
Those delving into data science have to learn the important difference between prediction and explanation, as we discovered in post-election discussions and finger-pointing.
The Costly Illusion of Denormalization for Performance
Fabian Pascal 10/24/2016 4 comments
Don't be fooled by the promises that denormalization in data management will provide performance gains at no cost. The real cost will be at the expense of analytics.
Brother, Spare Me the Paradigm
Fabian Pascal 9/26/2016 5 comments
Today's new data management paradigm seems more like a return to how things were done decades ago.
Data, Information, Knowledge Discovery, and Knowledge Representation
Fabian Pascal 8/26/2016 Post a comment
Databases in general and relational databases in particular are intended to be most useful for knowledge representation in the context of validation -- when a theory has been formulated -- and the logical model representing it in the database can be used to validate it and further analyzed to derive additional implications of a theory.
Data Science, Coding, the Automation Paradox, and the Silicon Valley State
Fabian Pascal 7/29/2016 22 comments
One of the failings of education stems from the lack of separation of academia from the private sector, with a revolving door between the two and university resources resulting in curricula that are entrepreneurial and vocational.
NoSQL, Big Data Analytics, and the Loss of Knowledge and Reason
Fabian Pascal 7/7/2016 4 comments
The data science behind big data analytics lacks a core attribute of real science, forethought.
Why Data Scientists Must Understand Normalization
Fabian Pascal 5/25/2016 13 comments
Data quality and avoiding inconsistencies is directly tied to normalization of data in a database.
Data Fundamentals for Analysts: Nested Facts and the (1st) Normal Form
Fabian Pascal 4/26/2016 4 comments
Fabian Pascal outlines key steps in database normalization.
Data Fundamentals for Analysts, Not Worth Repeating: Duplicates
Fabian Pascal 3/25/2016 2 comments
Fabian Pascal's followers have been raising questions about keys in databases. Many data professionals do not seem to understand why duplicates should be prohibited. This should worry analysts.
Data Fundamentals for Analysts: The Fourth V
Fabian Pascal 3/7/2016 3 comments
There is hardly anything more important in analytics than correct and correctly interpreted results, so think of "veracity" as the fourth V in big data.
It’s Not Tables, It's the Relationships
Fabian Pascal 1/27/2016 8 comments
The relational data model (RDM) was devised for essential modeling and that’s what is essential about it, not tables.
Data Fundamentals for Analysts: Documents and Databases
Fabian Pascal 12/17/2015 3 comments
Advocates of products that purport to avoid the time and effort necessary upfront usually do not say that without investing such time and effort one cannot ask the same questions of and produce results equivalent to those from relational databases.
Database Fundamentals For Analysts: Science, Data Science and Database Science
Fabian Pascal 11/27/2015 53 comments
Fabian Pascal explores the question of whether the relational model represents science.
Database Fundamentals for Analysts: Mathematics and Meaning
Fabian Pascal 10/21/2015 15 comments
Fabian explores why a logically correct result is not necessarily a meaningful result.
Database Fundamentals for Analysts: Tables -- So what?
Fabian Pascal 9/22/2015 7 comments
If database tables are designed to represent a set of facts about a single class of attribute-sharing entities each and to preserve the mathematical properties of relations, databases are easier to understand, and query results are guaranteed to be provably correct and easier to interpret.
Database Fundamentals: Relational Theory and Database Practice
Fabian Pascal 8/13/2015 3 comments
In his third installation of Database Fundamentals, Fabian explains why the relational data model isn't just theory but is adapted for the practical needs of database management.
Database Fundamentals: The First Half of Database Science for Analysts
Fabian Pascal 7/9/2015 9 comments
In gaining an understanding of relational database systems, a key step is learning what relations really are.
Database Fundamentals for Analysts
Fabian Pascal 6/18/2015 14 comments
It's time for analysts to learn more about the databases that feed their analytics tools.
Table Constraints and Data Science
Fabian Pascal 5/26/2015 3 comments
Something's too often missing from job requirements for data scientists: relational theory.
Class Business Rules and Table Constraints
Fabian Pascal 4/15/2015 2 comments
Fabian offers his guidelines for understanding business rules and table constraints.
Domains, R-tables, and SQL
Fabian Pascal 3/5/2015 7 comments
Analysts must know database tables’ interpretation -- the business rules underlying them -- which is rarely documented.
Understand Class Business Rules
Fabian Pascal 2/16/2015 14 comments
Before you dive into analytics, you need to understand what the properties in a database really represent.
Understand Property Rules & Domains
Fabian Pascal 1/5/2015 6 comments
Guessing the meaning by visual table inspection is a risky proposition, likely to lead astray. It helps if the analyst knows the types of rules to expect.
Analytics & SQL Tables
Fabian Pascal 12/3/2014 3 comments
To ensure sensible analysis and properly interpreted results, the conscientious analyst may have to do some digging that requires basic database knowledge
Relational Fidelity & Analytics Integrity
Fabian Pascal 11/7/2014 5 comments
There are ways to build the real-world meaning of data into the corporate database.
Tools Too Good to Be True
Fabian Pascal 10/6/2014 12 comments
Promised do-it-all data tools need to reflect a better understanding of how databases operate.
Data Analysts: Know Your Business Rules
Fabian Pascal 8/26/2014 18 comments
Analysts need to know the business rules on the basis of which a database was designed, to make sure data operations make sense and can properly interpret results.
Big Data & Analytics: Table Interpretations
Fabian Pascal 7/30/2014 4 comments
For analytical purposes, you must understand how to interpret database tables.
Big Data, Normalization & Analytics: Meaning & Constraints
Fabian Pascal 6/30/2014 4 comments
A deeper exploration of the fifth normal form reveals that context is critical for database analytics.
Big Data, Normalization & Analytics
Fabian Pascal 5/30/2014 10 comments
Database dependencies can cause false associations and introduce inaccuracy into big data analytics.
Missing Data, Databases & Analytics
Fabian Pascal 4/28/2014 49 comments
NULL values in SQL databases may mean that the data is missing, or it may mean that the data is inapplicable. Not knowing the difference can derail your analytics operations.
Analytics = Manipulation of Data Structure
Fabian Pascal 3/31/2014 21 comments
The term "unstructured data" is deceptive and misleading. Every analytics operation hinges on some form of data structure.
Anatomy of a Data Management Project: Distribution Independence
Fabian Pascal 2/26/2014 22 comments
Claims of "distributed" computing must be regarded with suspicion; setting up a properly distributed environment is no easy feat.
Causality, Uncertainty & Actionability in Analytics
Fabian Pascal 1/24/2014 16 comments
If you want your projects funded, you need to make concrete recommendations while accounting for the possibility of being wrong.
Anatomy of a Data Management Project
Fabian Pascal 12/20/2013 24 comments
Here's an example that shows what happens when you engage in database practice without a good grasp of data fundamentals.
Structuring the World With 'Unstructured Data'?
Fabian Pascal 11/21/2013 24 comments
Call me a skeptic, but I don't buy the hype of systems aimed at managing and extracting information from so-called "unstructured data."
Big-Data Über Alles
Fabian Pascal 10/18/2013 43 comments
Is the "big-data revolution" the result of a cultural shift -- or is it really about one organization imitating the next?
Understanding Data Independence
Fabian Pascal 9/18/2013 8 comments
Databases and database management systems (DBMS) resolve the problem of data independence.
Real Data Science: General Theories of Data
Fabian Pascal 8/22/2013 12 comments
It's ironic that as data science hype is going through the roof, the IT industry is increasingly distancing itself from relational theory.
Pass the Salt Along With That 'Data Science'
Fabian Pascal 7/19/2013 24 comments
The assignation of “data science” and claims made in its name requires some healthy skepticism.
ANALYTICS IN ACTION
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- by James M. Connolly