(Part 2) Best data modeling & design books according to redditors
We found 378 Reddit comments discussing the best data modeling & design books. We ranked the 78 resulting products by number of redditors who mentioned them. Here are the products ranked 21-40. You can also go back to the previous section.
The "bible" is "The Grammar of Graphics" by Leland Wilkinson. (link to amazon). The "gg" of ggplot2 stands for grammar of graphics.
Then we go into other books, resources that help with actually showing visualizations:
Then we can look at the "Table of Elements of Data Visualization":
Then, we can look at some blogs to help you see what works and doesn't work:
Finally, some blog posts about other people in data visualization that you can learn from:
>virtually anyone who isn't an engineer (or "math guy" as I've heard them pejoratively called) isn't going to understand why the graph/chart/graphic must be produced at a certain proportion.
FWIW, most engineers are clueless on this as well. Infographics is a specialized field, and it's not taught in the engineering curriculum.
A simple solution, if you want to learn more - read Edward Tufte's and Stephen Few's books.
[edit] For starters, I recommend
Few, Stephen, [Show Me The Numbers](http://www.amazon.com/gp/product/0970601999?ie=UTF8&tag=andmyaxe-20&linkCode=as2&camp=1789&creative=390957&creativeASIN=0970601999 "Warning: Associate tag thingy") (Analytics Press, 2004)
I'm assuming you are interested in designing schemas for relational databases, and not writing relational databases.
I really like CJ Date's SQL and Relational Theory and Database Design and Relational Theory. Use The Index, Luke is a nice site, too, with generally less formal information than Date's books, but more practical info about day-to-day problems.
If you'd like to dig under the covers, I'd start with Principles of Transaction Processing. Philip Bernstein knows what he is talking about, and is active in database research. Gray and Reuter's Transaction Processing is a classic, but is less approachable.
If one is serious about understanding databases, one should read Database in Depth: Relational Theory for Practitioners by C.J. Date. It is eye-opening.
I am currently working in a data warehousing and business intelligence role at a bank. Aside from the basics of ETL, SQL and OLAP, I would recommend having at least a basic understanding of financial accounting. I have also found it useful to read The Data Warehousing Toolkit as well as some other Kimball books.
For entry-level work, there are two recommendations of related skill that have served me quite well to get my foot in the door and show added value: Excel and reporting.
Every institution needs reports developed and it amazes me how rare it is to find well-built reports that clearly communicate their intended information. Being able to follow a few simple guidelines for effective layout and design go a long way. Edward Tufte wrote the definitive work regarding this, but I use Stephen Few's work for more up-to-date examples.
Excel has proven itself very useful for quick ad-hoc analysis and manipulations. Also, it is a mainstay application for most financial services companies and being fluent in functions, pivot charts and VBA is quite useful.
I just grabbed a book from the library that seems perfect for you. "Data Wrangling with Python" by Kazil and Jarmul.
https://smile.amazon.com/Data-Wrangling-Python-Tools-Easier/dp/1491948817/ref=sr_1_1?ie=UTF8&qid=1506215522&sr=8-1&keywords=data+wrangling+with+python
Description:
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How do you take your data analysis skills beyond Excel to the next level? By learning just enough Python to get stuff done. This hands-on guide shows non-programmers like you how to process information that’s initially too messy or difficult to access. You don't need to know a thing about the Python programming language to get started.
Through various step-by-step exercises, you’ll learn how to acquire, clean, analyze, and present data efficiently. You’ll also discover how to automate your data process, schedule file- editing and clean-up tasks, process larger datasets, and create compelling stories with data you obtain.
Quickly learn basic Python syntax, data types, and language concepts
Work with both machine-readable and human-consumable data
Scrape websites and APIs to find a bounty of useful information
Clean and format data to eliminate duplicates and errors in your datasets
Learn when to standardize data and when to test and script data cleanup
Explore and analyze your datasets with new Python libraries and techniques
Use Python solutions to automate your entire data-wrangling process
If you want to be good at sql, you have to think in sets. Also you need to pic a platform to learn on because even tho SQL is a standard, the sql will look different on different platforms.
these books balance each other out. Start with Date first. Celko can get you into trouble in places.
edit: i just realized that the author wanted to learn sql, not how start out designing databases. Whoops. Syntax can be learned anywhere. The previous books will discuss how to build properly built databases. However poorly built databases will stress you SQL-fu
I recommend the book "Web Database Applications with PHP and MySQL"
http://www.amazon.com/Web-Database-Applications-PHP-MySQL/dp/0596005431/ref=sr_1_1?ie=UTF8&qid=1292288900&sr=8-1
At the very least, this book will give you a better understanding of back-end development, which every front-end developer should be striving to learn, IMO.
Amazon says there are 58 used copies starting at $4.50 so the cost is non-existent. It'll cost you time and effort.
For DAX, SQL BI is a great resource (especially free articles).
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This book helped me learn powerpivot/DAX when I was first starting out:
https://www.amazon.com/Power-Pivot-BI-Excel-2010-2016-ebook/dp/B019BNG4YW
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I can't really speak for courses since I've never taken one. I mainly scour BI blogs, forums and buy books, but these guys seem to know what they are talking about:
https://pragmaticworks.com/Training/On-Demand-Training/Introduction-to-SSAS-Tabular
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The first step for me is always defining the use case. You can't really know the best way to model data without knowing how it's going to be used.
A book you might find useful is Data Modeling Made Simple, by Steve Hoberman. I was fortunate enough to work at a place that just paid Steve to come in and give a week long seminar on data modeling, which definitely helped me brush up on the principles I learned in school.
relevant
Currently using this:
http://www.amazon.com/Getting-Know-ArcGIS-Desktop-ArcEditor/dp/158948083X
(the pdf version is easily found online)
Esri offer a free 60 day trial, so that's cool.
For your particular application I would look at OpenStreetMaps. Otherwise...
David Hay's
Len Silverston's
Michael Blaha's [Patterns of Data Modeling][7]. This one has some interesting temporal, graph, and tree models.
Martin Fowler's [Analysis Patterns][8]. This one skims some of the other patterns, but gives accounting a solid treatment.
They are all well-rated, and I have read all but one, and they are all very good. Several of them are available on [safaribooksonline][9].
Also, OASIS's [Universal Business Language][10], schemas
[1]: http://www.amazon.com/Enterprise-Model-Patterns-Describing-Version/dp/1935504053/ref=sr_1_1?s=books&ie=UTF8&qid=1346950468&sr=1-1&keywords=enterprise%20model%20patterns
[2]: http://www.amazon.com/Data-Model-Patterns-David-Hay/dp/0932633749/ref=pd_sim_b_2?ie=UTF8&refRID=1PQPGE4E6T2RPR2XTN80
[3]: http://www.amazon.com/Data-Model-Patterns-Metadata-Management/dp/0120887983/ref=pd_sim_b_3?ie=UTF8&refRID=1PQPGE4E6T2RPR2XTN80
[4]: http://www.amazon.com/Data-Model-Resource-Book-Vol/dp/0471380237/ref=pd_sim_b_3?ie=UTF8&refRID=08T9TEZJNZM2EMKZV3AB
[5]: http://www.amazon.com/Data-Model-Resource-Book-Vol/dp/0471353485/ref=pd_sim_b_3?ie=UTF8&refRID=1D5TDG7479G7TQMBPNWF
[6]: http://www.amazon.com/Data-Model-Resource-Book-Vol/dp/0470178450/ref=pd_sim_b_4?ie=UTF8&refRID=08T9TEZJNZM2EMKZV3AB
[7]: http://www.amazon.com/Patterns-Modeling-Emerging-Directions-Applications/dp/1439819890/ref=sr_1_1?s=books&ie=UTF8&qid=1346950554&sr=1-1&keywords=patterns%20of%20data%20modeling
[8]: http://www.amazon.com/Analysis-Patterns-Reusable-Object-Models/dp/0201895420/ref=sr_1_1?s=books&ie=UTF8&qid=1346961699&sr=1-1&keywords=analysis+patterns
[9]: http://my.safaribooksonline.com/search?q=data%20model
[10]: http://en.wikipedia.org/wiki/Universal_Business_Language
I'm a Qlikview developer, so PM me if you have any specific questions. Also, Qlik JUST came out with a new product "Sense" last week. I've yet to dig into it but it seems like it's a very quick way to build ad-hoc reports with a nice drag-and-drop interface. This might be an easier start than Qlikview. http://www.qlik.com/us/explore/products/sense/desktop
Here's a comparison between Qlikview and QlikSense
http://community.qlik.com/blogs/qlikviewdesignblog/2014/07/29/view-or-sense
I highly recommend this book, and there are also lots of resources in the Qlikview Community forums
http://www.amazon.com/QlikView-11-Developers-Barry-Harmsen/dp/1849686068
Here are some other resources I've saved
http://tools.qlikblog.at/SetAnalysisWizard/QlikView-SetAnalysis_Wizard_and_Generator.aspx?sa=
http://community.qlik.com/community/resource-library
http://community.qlik.com/blogs/qlikviewdesignblog/2013/03/22/the-qlikosphere-external-resources--part-i
http://www.citagus.com/citagus/blog/different-ways-to-load-data-in-to-qlikview/
http://www.quickintelligence.co.uk/nine-essential-qlikview-development-tools/
/u/chammit gave you the best answer. I'd like to expand on it so that you have a few ways to look at 'linking' tables.
I've worked on distributed order management systems and a bunch of other stuff. The basic relationship you need to understand is the many-to-many relationship. To use your example, a product has a set of attributes. One type of product is a screwdriver. A specific screwdriver may be in one and only one inventory location.
Screwdrivers can be in one or more inventory locations. In one sense, this sounds like one-to-many, but it doesn't scale. If we only had one product and could guarantee that we'd never have more than one product, the inventory location would just be another column on the product table. But this is not realistic.
Products may exist in one or more inventory locations.
An Inventory location may stock one or more products.
These two statements declare the many-to-many relationship. Many-to-many relationships are always resolved through a 'link' table that maps the PK from one table in the relationship to the PK in the other table. Each product in the product table might have one record in the link table for each store.
Which leads to this question: how many screwdrivers are in the Canadian store? Which leads to this: where should the model store the value for how many screwdrivers are in a store? That value belongs in the link table. So do pricing, the effective dates for sales, replenishment thresholds (time to reorder number), etc.
Here are some synonyms that I've run across in specific situations. This will help you understand what people are talking about. Just remember that all these tables resolve a many-to-many relationship, with one potential exception.
Here's the possible exception: Crosswalk table. This is used to maintain the mappings of one system's names for things to another system's different names for the same things. It's used in integration APIs, ETL for data warehouse and integrations feeds. It's more often the case that this table only has one mapping record for each term, to no many-to-many relationship exists, even though it could.
Other synonyms: bridge table, associative table.
Note that if you look at an invoice detail table, it is resolving the many-to-many relationships between several entities; product, customer, store, date. The same can be said for any detail table in a master-detail model, any child in a parent-child model. The phrase, 'master-detail', I believe is common in GUI design, while 'parent-child' is common in backend development. They mean the same thing from the point of view of the table structure.
Your modeling skills are off to a good start. This is because you asked the right question: "How many screwdrivers are at the Canadian store?" I attempted to share how I would break down your question to arrive at a modeling solution.
Edit: My recommended book: https://www.amazon.com/Data-Model-Patterns-David-Hay/dp/0932633749
Honestly, if you have minimal programming experience to begin with, you really should start with learning the basics. Pick a simple project (a few of my first included a tool to manage my Movies, a deck editor for Magic: The Gathering, and simple website, etc). Download WAMP/MAMP if you don't already have it and pick up a good resource book, and abuse php.net for learning what different things do.
I've recommended the first edition of http://www.amazon.com/Web-Database-Applications-PHP-MySQL/dp/0596005431/ref=sr_1_1?ie=UTF8&qid=1299603608&sr=8-1n before, but I don't know how the second stands up - perhaps worth a look.
Most importantly, if you don't have an understanding of HTML/CSS/Javascript - you won't understand all the different components that make up a web application. Invest heavily in learning the basic markup/css and a bit of javascript and you will be miles ahead of a lot of people who call themselves "developers" simply because they can remember the names of a dozen drupal functions.
QlikView 11 for Developers was invaluable for me.
http://www.amazon.com/QlikView-11-Developers-Barry-Harmsen/dp/1849686068
Multiple Choice.
Well, I learned from a course in college, but you might check out books from the publisher O'Reilly--e.g. this. I don't really use books much, though, I mostly learn by doing, and Googling when I run into issues. w3schools is a pretty good resource for learning the basics of HTML. Personally, the most effective way for me to learn a new language or technology is by coming up with a project I'm interested in and try to implement it in the language.
All of the suggestions about finding a project to work on are dead on. But also, along side of doing a project, learn some database theory. Also, rather than the giant 1000 page database textbooks, I like the books by C.J. Date especially SQL and Relational Theory.
Project Euler is great, but I can't imagine a less efficient way to learn about "advanced algorithmic techniques". Most of the problems are concerned with brute force search, dynamic programming and "clever" ways to trim the computation trees of those two techniques on specific problems.
A better way would be to read books on general algorithms, on optimization, on AI and on machine learning. To that end, two of my favourites are
Alternatively, if you've got a specific area of interest then you might want to find a handbook for that area. For example, here's one on data structures.
As a side note, if the price tag of any of those books puts you off, take a look at Library Genesis.
What about this book?
Since relational databases are a mature technology, there is some well-established theory that is very useful to learn (in conjunction with the more practical, vendor-specific knowledge).
I'd suggest:
Database Management Systems - an undergrad-level textbook with a good balance of theory and practice, foundations and advanced material.
Readings in Database Systems - a compilation of influential academic papers from the database field.
Data Modeling Made Simple - a great little book that bridges the gap between databases and the real-world entities they store.
Oh god, yes. Use Python. Use Python. USE PYTHON. Seriously - someone on Stack Overflow once wanted help on a project like this because he wanted to use Python and the client insisted on VBA. One of the CREATORS of VBA replied, saying he'd prefer to do it in Python. Someone else said to print that out and show it to the client and that would be all he needed. :-)
https://www.amazon.com/Data-Wrangling-Python-Tools-Easier/dp/1491948817
https://www.amazon.com/Python-Data-Analysis-Wrangling-IPython/dp/1491957662/ref=pd_cp_14_1/144-1708349-4929050?_encoding=UTF8&pd_rd_i=1491957662&pd_rd_r=3012d8cc-053a-4575-abf2-94039719a3d4&pd_rd_w=ODfdR&pd_rd_wg=CpS9q&pf_rd_p=0e5324e1-c848-4872-bbd5-5be6baedf80e&pf_rd_r=2DG2M7K5VYQ25NSN8N3P&psc=1&refRID=2DG2M7K5VYQ25NSN8N3P
I have been working with Power BI for the last 2 or so years since it was released. So most of what I have learned has been either directly from microsoft or figured out on my own. I would Echo Data_Cruncher's statement below. In order to match your vision of what you want to display with the reality of your actual data, you should get familiar with DAX.
Good DAX books I have read:
Learn to write DAX from Matt Allington (good book, lots of basic concepts)
https://www.amazon.com/Learn-Write-DAX-practical-learning/dp/1615470417
Power Pivot Power BI by Rob Collie (funny book with more advance concepts)
https://www.amazon.com/Power-Pivot-BI-Excel-2010-2016-ebook/dp/B019BNG4YW/ref=mt_kindle?_encoding=UTF8&me=
Also, since I figured if I was trying to learn others would want to know what I have developed. So I have built a website with short tutorials on how to use and manipulate data in Power BI. You can access it by going to www.powerbi.tips.
As a final thought you should also check out he Power BI youtube channel. Start at the beginning at Video 0-1 and work your way through the tutorials. It starts with some over views and then quickly gets into how to build dashboards.
https://www.youtube.com/playlist?list=PL1N57mwBHtN0JFoKSR0n-tBkUJHeMP2cP
Think Stats by Allen B. Downey is a nice little book that teaches you some concepts of probability. The book assumes that you already know at least the basic concepts of Python, though.
Not really. Check it out on Amazon if you want a preview.
https://www.amazon.co.uk/dp/B07Q3T381Q
It's definately more advanced but I'm enjoying this one:
http://www.amazon.com/Data-Visualization-D3-js-Cookbook-Nick/dp/178216216X
I think you need to start with the SQL standard and then with product specific documentation
SQL and Relational Theory
http://www.amazon.com/SQL-Relational-Theory-Write-Accurate/dp/1449316409
Then if you have the base you can use a good RDBMS : Firebird or Postgresql would do the job , they implement the SQL standard
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Hi, There are so many resources out there I don't know where to start! I would work through some kind of beginner python book (recommendation below). Then maybe try Andrew Ng's Machine Learning Coursera course to get a taste of Machine Learning. Once you have completed both of those I would reassess what you would like to focus on. I will include some other books I would recommend below.
Beginner Python - https://www.amazon.co.uk/Python-Crash-Course-Hands-Project-Based/dp/1593276036/ref=sr_1_3?keywords=python+books&qid=1565035502&s=books&sr=1-3
Machine Learning Coursera - https://www.coursera.org/learn/machine-learning
Python Machine Learning - https://www.amazon.co.uk/Hands-Machine-Learning-Scikit-Learn-TensorFlow/dp/1491962291/ref=sr_1_7?crid=2QF98N9Q9GCJ9&keywords=hands+on+data+science&qid=1565035593&s=books&sprefix=hands+on+data+sc%2Cstripbooks%2C183&sr=1-7
https://www.amazon.co.uk/Data-Science-Scratch-Joel-Grus/dp/1492041130/ref=sr_1_1?crid=PJEJNNUBNQ8N&keywords=data+science+from+scratch&qid=1565035617&s=books&sprefix=data+science+from+s%2Cstripbooks%2C140&sr=1-1
Statistics (intro) - https://www.amazon.co.uk/Naked-Statistics-Stripping-Dread-Data/dp/039334777X/ref=sr_1_1?keywords=naked+statistics&qid=1565035650&s=books&sr=1-1
More stats (I haven't read this but gets recommended) - https://www.amazon.co.uk/Think-Stats-Allen-B-Downey/dp/1491907339/ref=sr_1_1?keywords=think+stats&qid=1565035674&s=books&sr=1-1
Data Structures with C++ Using STL (2nd Edition) https://www.amazon.com/dp/0130858501/ref=cm_sw_r_cp_apa_i_f1SrDb61CPQ12
If you are buying a textbook (I used this for my intro class), you get a trial version you can download onto your computer for 3 months IIRC
Advanced Data Structures and Handbook of Data Structures and Applications are both well regarded.
http://www.amazon.com/Structures-Algorithms-JavaScript-Michael-McMillan/dp/1449364934/ref=sr_1_1?ie=UTF8&qid=1411131886&sr=8-1&keywords=Data+Structures+and+Algorithms+with+JavaScript
Sorry for the late reply on this one.
Data structures & algorithms is not something you see taught very often in JS although some resources do exist.
Data Structures & Algorithms with Javascript has some good information but is often criticized for having code errors and some misinformation in the book.
While it's certainly possible to learn these things in JS there are many more solid resources for learning them in Python/Ruby/Java than there are other languages.
Please check out my book
https://www.amazon.com/PRACTITIONERS-introductory-science-governance-Reporting-ebook-dp-B07L8BTBQ4/dp/B07L8BTBQ4/ref=mt_kindle?_encoding=UTF8&me=&qid=
This was the book I used.
It's decent, I just wish I used it more.
Here is an informative ebook perfect for BI beginners, The Ultimate Guide to Cleaning Data with Excel & Google Sheets. Or get it free at www.inzata.com
Nothing helps accelerate and improve a decision-making process like clean data. Updated & accurate data supports analytics and business intelligence, which in turn provides organizations with the proper information for better decision-making and execution.
I deliver DIAD training all over the US. I’m also a Power BI MVP. My fellow mentors are on the road all the time, helping others on their data journey. Business intelligence is so much more than reporting and if all you are doing is moving a spreadsheet to a webpage, you are missing the value.
The DIAD has a very specific purpose to introduce people to Power BI and show off the features. In my opinion, it doesn’t replace the need for training or for our Managed Community of Practice services.
Let me outline the journey and why trying to get all of this via YouTube might not be the most efficient way to learn.
To use an analogy, the DIAD teaches you the parts of the boat. Our training classes teach you how to sail the boat. Our Managed Community of Practice service helps you to become a master sailor. Our Executive Seminars help your captains learn about the sea and to determine what benefits they get from “going to sea.” Our Conversation-Centric training helps you learn how to read the charts and determine your destination.
We released a book recently from our CCD classroom training materials, called “What Does Your Data Say?” It’s designed to help people think about what questions to answer.
https://www.amazon.com/What-Does-Your-Data-Conversation-Centric-ebook/dp/B07VFRMXSL
We’ve partnered with ManyWorlds.com to help companies go farther and turn data into learning and then into action. Learning faster than others is the only true competitive advantage. Their book describing the Data to Learning to Action process is here:
https://www.amazon.com/Optimizing-Data-Learning-Action-Performance-ebook/dp/B07CBMKMM5
Just knowing where to click is the beginning, not the journey. As you can see, there’s a lot of stuff to learn to be truly effective.
I’ll be conducting a DIAD in Dallas, TX on Sept 30. If you are interested in attending, shoot me a line via our contact form at https://marqueeinsights.com I’d love to meet more of the folks on this sub.
I’ll be discussing some of the “how to sail” aspects in the DIAD and we can do a AMA dinner afterward.
Hope this helps.
have a look at this one.
https://www.amazon.com/SQL-Relational-Theory-Write-Accurate/dp/1491941170/ref=sr_1_1?s=books&ie=UTF8&qid=1481011655&sr=1-1&keywords=sql+and+relational+theory