SQL, Code, Coffee, Etc.

01/02/2018
by Marlon Ribunal
Comments Off on My Tech Reading List to Start the Year

My Tech Reading List to Start the Year

My bold learning goals call for adequate preparation and proportionate action. Before plunging into the challenge, I need to get myself into a focused learning mode quickly. The most effective way for me to do that is by reading. If you are like me, every time that you want to learn something, the first thing that you would do is look for written materials on whatever topic that you want to learn.

My medium preference is still the physical book. There are many benefits to reading printed materials such as brain stimulation and memory improvement. Reading online materials like blogs and articles is a big part of my daily routine. But when I need to sit down and focus on certain things that I want to learn deeply, I’d pull a physical book from my bookshelf and just put in the needed concentration and time to dissect and slice and dice every bit of information that I need to process into every available neural pathway of my brain.

Here is the first batch of technical books that I am reading to start the new year:

Star Schema: The Complete Reference by Christopher Adamson – You’d say, “Hey, Marlon, in the Era of Big Data and Hadoop, Dimensional Modeling is Dead! The traditional data warehouse has long been replaced by data lakes!” Ok, let me leave you that to debate among yourselves. What this Star Schema book teaches are the design principles that will not fall into obsolescence and will transcend beyond technology. What our business processes demand of us, data professionals, is that we not only deliver the data structure that will support the evaluation of these business processes but also the measures and their context with which the data are evaluated.

The Data Warehouse ETL Toolkit by Ralph Kimball & Joe Caserta – “Again, Marlon, I have a couple of words for you, “Hadoop it! ETL is likewise Dead!” Like the Star Schema book, this ETL Toolkit teaches the fundamental principles and techniques of extraction, transformation, and loading of data. Technologies surrounding how we extract, transform, and load data may have changed but the principles remain the same. This book will take you back to the basics, and regardless of technology platform, the principles you’ll learn here will equip you with the necessary skills to adapt to the ever-changing technology landscape.

Agile Data Warehouse Design: Collaborative Dimensional Modeling, From Whiteboard to Star Schema by Lawrence Corr – “Marlon, stop it! Data Warehouse is Dead!” Again, because of the principles that this book advocate, I have it on my list. If you’re looking for agile principles that you need to be guided by in your data projects, this is a great book to have. Dimensional modeling as a philosophy is alive and kicking. This book will make you learn the right questions to ask about your data stories: the who, what, when, where, how many, and why and how. This is also a good introduction to the concept of Business Event Analysis & Modeling (BEAM) if you’ve never heard about the concept before.

Storytelling with Data: A Data Visualization Guide for Business Professionals by Cole Nussbaumer Knaflic – Your data projects will be meaningless if they are not capable of telling their stories. With the era of Big Data revolution, we are inundated with more data and information than we can possibly handle at a time. This book teaches us that “Data Visualization sits at the intersection of science and art.” More important than the data themselves are the meanings and stories they convey. As data professionals, we just don’t deliver data solutions. We also need to deliver the effective stories behind those data. This book teaches us the right principles on how to effectively do just that.

Pro SQL Server Internals: Understand What Happens Under the Hood and How It Affects You by Dmitri Korotkevitch and High-Performance SQL Server: Bringing Consistent Response Time to Mission-Critical Applications by Benjamin Nevarez – Big part of my day job is to ensure that our client applications are running on optimal performance. These two books are great resources for making your SQL Server run faster. They provide sound principles for database maintenance and performance tuning.

I highly recommend these books. If you’re looking for books to grab on these topics, pick one or all of them. I’d like to hear about your tech reading list. Share them in the comment below or, if you have a post about your tech reading list, provide the link to the comment below. Happy New Year and Happy Learning!

12/26/2017
by Marlon Ribunal
2 Comments

My Learning Goals for 2018

A couple of weeks ago, the SQL Server community had their last T-SQL Tuesday of the year – 97th since 2009 – hosted by Mala (b|t). T-SQL Tuesday, a brainchild of Adam Machanic (b|t), is a monthly blog party in which participant tech bloggers write about any given topic. The topic for December is about learning goals for 2018.

I guess this post is quite late to the party but it’s good to have a baseline for what I want to learn for the new year, and so, this post is quite appropriate. Mala has given three questions that serve as guidelines for the format of the post:

What do you want to learn?
How and when do you want to learn?
How do you plan to improve on what you learned?

And, I’m going to use those questions to structure my learning goals.

What Do I Want to Learn?

Quick answer: Many things. I am declaring 2018 as my Career Year. So, everything I do is anchored to that theme. For 2016-2017, my mantra was Kaizen – Continuous Improvement. I want that to still be a part of what I do in 2018 – but bolder. My mantra for 2018, therefore, is Daitan’na (大胆な ): audacious, daring, bold. Daring with a hint of Kaizen, if you will.

I want to learn the following:

Big Data
Power BI
R Language

Yes, bold. Big Data itself is already a, well, big elephant. One bite at a time would not do it. Big Data is too big a topic to only learn it in a span of a year. But I am not shooting for mastery yet. The goal is to gain the practical skills that would translate into elements of a work experience – meaning, that I would survive if I was suddenly thrown into a Big Data dungeon.

Power BI is a natural next-step if you’ve worked with SSRS. There was a time that Tableau is a craze. Power BI can capture that market. I want to equip myself with the necessary skills that would measure proficiency. Therefore I need to build upon my Power BI skills.

T-SQL alone would not do it anymore. I need to learn a more powerful language for analysis. The R Language has been an interest to me ever since and I want to dig deeper into it.

When and How Do I Learn?

I work a full-time job. For many people who work in the tech industry, they know that a full-time job doesn’t just mean 9-5. It could mean 12 or more hours a day. You’ll never have a 40-hour week. Time is unpredictable in the tech industry. So, When, is a question that is hard to answer.

Learning itself is a philosophy that I have long embraced. I will find the time to learn even if it would mean sacrificing some of my sleeping time. Yes, that’s bold. Sleep is a commodity that even the Bourgeoisie can’t afford anymore. I’ll set a minimum of 1 hour for learning every day (this is on top of my minimum of 30 minutes of reading miscellaneous topics). That’s the minimum, meaning even if I don’t have time to study, I must find at least an hour for that purpose.

How do I learn is the easier question. I have three major places of learning: Pluralsight (courtesy of the Friends of Redgate Program), UDemy, and Microsoft Professional Program + edX. Of course, blogs, webcast, and even tech videos on YouTube and other media will help. In-Person events like the SQL Saturday are a great resource for the things that I want to learn as well but I am not sure if I have the time this year for such activity. The focus is to learn. It’s not a question of how or where do I learn but of what do I learn. And, there is an abundance of materials out there that I can use to my advantage.

How Can I Improve on What I Learned?

Learning for the sake of learning is an empty goal. The purpose of my learning goals is to scale my tech skills. It wouldn’t make sense to spend all of your precious time for nothing. Obviously, these goals are set on the personal level – learning is an aspect of my career that I have committed to. But of course, that doesn’t end there. I want to maintain certain baseline or level of skills that are readily applicable in the real world. I may not land a Big Data job or position in my current company or outside right away but I want to maintain a working-level experience at my disposal.

One avenue that I can probably utilize for sharing what I’ve learned is my blog. Well, tech blogging is one of the aspects that I want to improve on this year. I believe that my blog is an indispensable part of my career. So, this year, I also want to set aside some time for writing. And, of course, participating in forums should also be on the list.

Like I said, these learning goals are rather bold. But, if I want to focus on my career this year, it is just fitting that I have a bold mentality.

Daitan’na. Kaizen. Daring with a hint of Kaizen.

10/03/2017
by Marlon Ribunal
1 Comment

Book Review: High Performance SQL Server

As SQL Server professionals, we sometimes encounter some issues that we haven’t seen before or have seen already but forgot how we fixed them. There are few things that we usually do in these situations: Diagnose using sp_whoisactive or sp_Blitz, or any other tools that we have at our disposal, try to remember what we did to troubleshoot the issues, fire up our Wait Stats queries, check DMVs or maybe Extended Events, etc.

If none of these work, then we do what normal data pros usually do in desperate times: Google stuff or maybe post a question or two on Twitter using the hashtag #sqlhelp. But the problem is that the information that we need is all over the interwebs. There is just too much information but little time to look at each one of them.

If you are like me, you still find technical books to be relevant these days. And I mean the real, physical books. Great technical books offer high-value content that is readily available in one place (that is if you picked the right book for your purpose). Plus, if you’re looking to unplug, reading books is a good way to pry yourself away from the screen. For example, High-Performance SQL Server: The Go Faster Book by Benjamin Nevarez (B|T). I recently added this book to my SQL Server shelf.

Some of you know that I started a new job this year with a software company that caters to the retail industry (our clients are big brand retailers). Part of my day-to-day job is troubleshooting performance issues on SQL Server. So aside from reading technical blogs, I read technical books to improve my skills.

Let’s go back to Ben’s book. With only 200 pages, this book is not overwhelming to read. Yes, it’s short and it doesn’t have all the things about SQL Server but, I think, it has all the important things that I need to know. And, yes, it covers up to SQL Server 2016. It has 9 Chapters:

How SQL Server Works
Analyzing Wait Statistics
The Query Store
SQL Server Configuration
TempDB Troubleshooting and Configuration
SQL Server In-Memory Technologies
Performance Troubleshooting
Indexing
SQL Server Storage

The chapters that I found important (of course, this is relevant to who is reading the book) are 2, 5, 7, and 8.

Chapter 2 deals with Wait Stats. We love Wait Stats. If you are like me, you probably have SQL Server Wait Statistics: Tell Me Where It Hurts query from Paul Randal (B|T) in your arsenal. I haven’t perfected the Wait Statistics methodology of performance tuning yet and this is why I like this chapter. This chapter “explains how the task execution process fits into waits and queues performance methodology”. I know what processes are waiting but why they are waiting is the most important question to answer. This chapter discusses waiter list, runnable queues, task execution process, Extended Events, Latches and Spinlocks, Blocking and many other things about analyzing wait statistics.

Chapter 5 is about TempDB. One of the common issues that I encounter in my job is issues with TempDB running out of space although there is enough physical disk space for the TempDB files. When an application is doing tons of concurrent tasks that depend heavily on TempDB, you may want to be proactive about the health of you TempDB. Well, according to Brent Ozar (B |T), TempDB is the public toilet of SQL Server, so we better keep it clean. The information from this chapter will help you maintain the TempDB and keep it sanitary. Topics discussed are fixing latch contention, data file pages, Trace Flag 1117 & 1118, tempdb events, TempDB spills, monitoring TempDB disk space, etc.

Chapter 7 covers the overall performance troubleshooting. The topics discussed are performance counters, comparing batches and transactions, log growth, other DMVs not discussed in previous chapters, SQL Trace & Extended Events, Data Collector, what’s new in SQL 2016, etc.

Chapter 8 is about Indexes. This chapter explains how SQL Server uses indexes. It also offers tips on where to use indexes, how to work with indexes and how to use the execution plans, missing indexes feature, Database Engine Tuning Advisor & Index Tuning Wizard, etc. One does not simply over-study indexes.

Ben Nevarez is one of the people I respect and look up to in the SQL Server Community because of what they do in helping other SQL Server professionals grow in their career and personal life. But this is not the only reason why I like this book. The topic selections and how they were delivered in a minimal number of pages ensure that I get the information that I most need to know about performance tuning and not get overwhelmed learning about them.

This book is a good complementary material to Pro SQL Server Internals: Understand What Happens Under The Hood and How it Affects You by Dmitri Korotkevitch (B|T) from the same publisher as Ben’s, which I also have.