PASS Speaker Idol: Part of the Goal of Being a Better Speaker

MicrophoneAndStandIf one wants to get better at public speaking, there is no better way of doing that than to practice. Personally I think the best experience are where you are giving a talk to an audience, as that seems to improve my performance better than speaking to a mirror. I also read a lot of blogs regarding public speaking hoping to learn some tips. One of the things I know not to do, but I do anyway is add in those nothing works like “um” or “ah”. I know that I shouldn’t. I also know I shouldn’t procrastinate, but I find myself doing that sometimes as well. Sometimes you have to figure out ways to make yourself do things, like making a deadline so you can hit it or putting yourself in a situation where you are asking people to criticize your speaking skills. If the goal is to get better, I think you have to move yourself out of the comfort zone you may be occupying in order to make that happen.

Speaking as a Competitive Sport

For those of you who haven’t heard of PASS Speaker Idol, which is understandable since it has only been around for a year, it is a competition where 12 people compete by giving a five minute technical speech on a topic of their choice in front of an audience and a panel of judges. There are four rounds of competition, and 3 people will advance to the finals. The winner will get to speak at PASS Summit next year on a topic of their choice. Here are all the competitors, and the competition times. If you are at PASS Summit hopefully you can attend some of the sessions.

Wednesday (3:15pm – 4:30pm)

  • Todd Kleinhans
  • William Durkin
  • Ginger Grant
  • Ed Watson

Thursday (4:45pm – 6:00pm)

  • Rob Volk
  • Amy Herold
  • Bill Wolf
  • Wes Springob

Friday (2:00pm – 3:15pm)

  • Luciano Caixeta Moreira
  • Ronald Dameron
  • Theresa Iserman
  • David Maxwell

You will notice I am going on the first day. I’ve decided to give a talk on SSIS, and figured out how to talk for only five minutes.   I’ve been practicing, run through my demo, and took pictures of the demo in case it doesn’t work that day. After reading everything I could find on what happened last year, I’m feeling pretty good about my chances. Many thanks to Rob Volk t | b on all of the great information he put out about last year’s competition. A big thanks also to Denny Cherry t | b for not only starting the Speaker Idol contest but doing it again this year.

Winning Good Information

Regardless how the competition turns out, I will win information from those people who watch me speak how I can be a better speaker. Hopefully they won’t catch me saying “um” but I plan on learning how to apply some of the other things I learn to improve my talks the next time. If you are interested in where I am speaking next time, please take a look at the Engagements page on my blog where I list everywhere I have or will be speaking. One of the places I will be speaking is at the PASS Business Analytics Conference in May. I am thrilled to be able to talk about Implementing Successful Data Analytics Management Practices for two hours. After this week, I’m sure that presentation, and others will be even better than they would be. If you want to know how Speaker Idol turns out, please subscribe to my blog where I will be letting you know how it all turned out.


Yours Always

Ginger Grant

Data aficionado et SQL Raconteur



Internet Promotion: A Way to Make Falling Trees Heard

TreeFallsInTheWoodsIf a tree falls in a forest, and no one hears it, did it make a sound?

I can’t remember when I first heard this axiom, but it was sometimes when I was in elementary school. At the time I thought it was the silliest thing I had ever heard. After all, a tree falls regardless of my opinion or recognition. The tree is going to do what it is going to do and my interaction with it is meaningless. The sentence was one of those things, which is best described by Lewis Black as something which “…causes your brain to come to a screeching halt“. It made no sense to me, until later.

Why tell the world?

One of the reasons for this blog is pretty much the same as everyone else’s blog, namely, I wanted to write down what I know. So I got a high-speed internet connection (such as those available through optimum internet plans), created a blog, and started writing. There are a number of reasons for writing, to ensure I remember things, to find a link to something that works, to give back to those who have helped me by helping others or the desire to share something over the internet. The reason for informing the world varies. Displaying what your interest or expertise is can lead to opportunities where people ask you to do things where you have demonstrated your knowledge about a topic. As a member of a speaker selection committee, I know being able to find out about a speaker’s expertise made me recommend them or not.

Falling Trees Making a Sound

If someone gives a lot of talk and no one knows it, will they be asked to speak again? If you work with a real expert at a certain task and no one knows it, will this person be able to command a very high rate of pay at a future job? If your employer does something for you, such as sending you to a technical conference and you tell the world, are they more likely to send you to another in the future? While I am sure the answers to these questions can be universally answered by the consultant mantra “It depends“, for what it’s worth, perhaps letting the interwebs know will increase your chances of being asked or increase your value. If you are also one of those people who hate self-promotion, a blog may seem rather braggadocios. It’s also one of the few ways you have of telling people what you do.

The World is the Forest

It’s a big world out there. At some point, someone is going to ask you what you do. Sure you can practice an elevator speech. But when someone is sitting around surfing the internet and trying to find out about you, isn’t it best that you be the one who lets them know what you’ve done and what you know? Now, I don’t know if having a blog has helped me do anything I have done or not, but I continue to post. The world is a forest, and when I chop down a tree this is where I will make a sound.

Yours Always

Ginger Grant

Data aficionado et SQL Raconteur

Creating a Successful BI Project starts with Data Modeling

Recently I was helping someone debug an Analysis Services Multidimensional project, and didn’t come up with much to help the performance. Why? The underlying data model was completely unwieldy and the fix, which no one wanted to do, was to redo it completely. Having worked recently with a number of business analysts to migrate there Excel spreadsheets to Power BI to support the growing trend to Self-Service Business Analysis, has made me think a lot about what makes a project a success.  Self-Service BI has been hyped as the way that analysis can better do their job and not involve technical resources.  While I support the move to the Analysts being more involved in with the data to make good decisions using the data, these kind of projects still need experienced data professions help them make a the project a success. There isn’t a tool which can fix a project with a bad data model. The problems the analyst have are not so much with learning the tool, as Power BI was designed to be easy to use. The problem is with data modeling.

Reporting Views; Modeling for the Moment

A lot of business reporting is developed by using the following process, which you may find where you work. The database team can’t keep up with the report requests, so they create a number of views and provide business analysis with some tool, be it Report Builder, Excel or Access to gather the data to do reports. This method provides the ability for analysts who don’t know much about data modeling to create reports based on the information is provided. This process works for a while. As long as the data people need to do their jobs is provided, reports are created and the Database team doesn’t have to be involved. This whole methodology starts blowing up over time. Why? The reporting time starts to increase.

The Reporting Time Explosion

Once I was working at a company where the person in charge of doing the performance reporting went on an extended medical leave, and trained someone else on what was required to get the data and create the reports. She gathered data from this system and that system, added in some information on a spread sheet, ran some macros did some queries, updated some Excel spreadsheets and after that the reports were generated. This process required three hours every day to do this complicated series of task and a full week for monthly reporting. It took all of about two days for her replacement to be overwhelmed, and the task of doing the reports came to me. After a week, I had gathered all of the data together for the daily reporting and automated it, which took the daily reporting process from three hours a day to seconds of computer time. It took a couple of stored procedures, some SSRS reports and a new process for storing the data not in an Excel Spreadsheet, but in the application where it was supposed to be entered. By the end of the second week, the monthly reporting was completed as well. A task which took the majority the time person spent her day, was automated to button clicks in less than two weeks. Why? The task of gathering the data was given to someone who understood databases and data modeling. That’s the knowledge that is needed to set up a successful BI Project.

Business Knowledge needs to be combined with Technical Knowledge

To be an expert at something takes time and focus. There are only so many hours in a day, and if you are focused on spending those hours on creating technical solutions, you are bound to get really good at applying technical knowledge gained to solving problems. Likewise, if you spend all of your day looking at the data trying to solve business problems and answer questions about how the decisions made impact the data, you are going to get really good at analyzing business data. Tools help provide the ability to answer questions, which can be answered because the data model supports the type of analysis needed. To figure that out, someone who knows about data modeling needs to be involved to ensure the Self Service business intelligence project has a good foundational data model.  If that’s not there, it doesn’t matter what the tool is, the project won’t be successful.


Yours Always

Ginger Grant

Data aficionado et SQL Raconteur

Upcoming and Recent Events

24HOPPassSpeakingThe PASS organization is a professional organization which sponsors a number of different technical events in the technical community. Recently, I have been honored to be selected to speak at not one but two events hosted by PASS, a professional organization which provides a lot of great resources to improve knowledge of all things SQL Server and related technologies to the world. The PASS Business Intelligence Chapter provides training on all things related to Business Intelligence via the web. I was selected to talk at the last meeting in May. Thank you to all of the people who were able to attend my talk on Top 10 SSIS Tuning Tricks live. If you had to work, no problem all of the talks hosted by the PASS Business Intelligence Virtual Chapter Recordings are available on The recording of my Top 10 SSIS Tuning Tricks session is available here.

24 Hours of PASS

Periodically PASS provides a 24 Hour Training session on SQL Related topics to provide training live to every time zone in the world. As this event is watched by people around the world, it is a real honor to be selected for this event. This time the speakers were selected from people who had not yet spoken at the PASS Summit Convention, as the theme was Growing Our Community. The theme is just another way the PASS organization is working to improve people’s skills. Not only do they provide the opportunity to learn all things data, but also provide professional development through growing the speaking skills by providing many avenues to practice these skills.

Data Analytics with Azure Machine Learning

My abstract on Improving Data Analytics with Azure Machine Learning was selected by the 24 Hours of PASS. As readers of my blog are aware, I have been working on Azure Machine Learning [ML] this year and look forward to discussing how to integrate Azure ML into current environments. Data analytics with ML are yet another way to derive meaning from data being collected and stored. I find the application of data analytic fascinating, and hope to show you why if you are able to attend. There are a number of wonderful talks scheduled at this event, so I encourage you to check out the schedule at attend as many as you can. To be sure I’ll be signing up for a number of sessions as well.

Yours Always

Ginger Grant

Data aficionado et SQL Raconteur

What Does Analytics Mean?

A lot of words get used in technology and after a little while, no one bothers to mention what the word means. That’s too bad when the definition of a word gets changed, but that’s not the case with analytics. I found out that analytics is not a new word. It was coined in the 16th century to describe trigonometry, which makes me even more surprised WordPress’ spell checker always puts a red line under it as a misspelled or unknown word. I had someone tell me recently that they really weren’t sure what it was supposed to mean.

Wikipedia says “Analytics is the discovery and communication of meaningful patterns in data“. That’s what as data professional doing when we provide data in a manner which answers questions, such as providing KPIs, machine learning algorithms, or visualization. It’s not enough to be the keepers of the data library, data should also be used to provide meaning. Keeping that in mind, businesses all over the world tend to look for Adverity ( or any similar company that has a skilled and experienced team of data analysts. Such service providers usually extract meaningful insights from available data and assist in the formulation of marketing strategies. Here’s another reason to work on analytics, the dollars the trade press is predicting will be spent on business analytics by 2018.

Steps to Providing Analytics

When describing the process for providing analytics, I am sure many people will recognize parts of the process as they are engaged in them now. The first step is to understand the data. Understanding the data does not only mean having knowledge of the structure of the data, as that obviously will be necessary to select it, but also needing to know how the business uses the data. Which fields contain the data they actually use? The second step is to preparing the data, including determining what data to include. Do you have all of the data you need to do the analysis? If the answer to that question is no, the analytic process will stop. You may have to exclude some data if it is incomplete or of dubious quality.

Once one has the needed data, it’s time to start the third step, data modeling. Modeling is where you categorize and make various decisions regarding the data. For example, if you are wearing a blue shirt and tan pants and you are looking at the laptops and you happen to be in Best Buy, you have found an employee. Determining if your model is evaluated in the next step. Generally speaking the analysis will include items where you know the outcome. For example, if you are trying to predict when your website volume will increase, you want to look at the historical events that made that happen. Marketing people do this to determine if the ad campaigns were successful, for example.

The Dynamic Analytical Process

After the model is created and sucessfully tested and evaluated, it’s time to deploy it and monitor the outcomes. One thing to remember about complex analytical models is they will probably change. One example of this is an analytical model many people are familiar with, the FICO score. FICO scores were created to predict credit risk. They have been tweaked quite a lot as the latest real estate crash showed that the fact a high FICO score showing someone paid credit cards on time was a lousy predictor of whether or not that same person would default on a mortgage. Netflix changes the movies they recommend when new movies come out. Things change all the time, so working on analytics means the work is never “done”. All the better for those of us who enjoy data analytics.


Yours Always

Ginger Grant

Data aficionado et SQL Raconteur




Speaking for myself, sometimes I have a hard time getting motivated. I know that I need to get a bunch of work done, and I find myself mesmerized by the internet as pet pictures or the news or twitter momentarily provide really compelling reasons not to work on the list of things that I have to get done. Eventually, I pull my head out, and start getting things accomplished. I seek out articles which have motivational tips too. One of the best tips I read went something like the inhabitants of Planet Kardashian will exist whether or not you are aware of their foibles. (They have planets now? Star Trek fortold a reality show?) What I took from the tip is; what’s going on other places will continue to go on whether you know about it or not, so you can find out about it after your work is done. Some days that works well, others, more of a goal. I write to do lists, place sticky notes around where I can’t help but see them and engage in most of the other tricks I’ve read to motivate myself. Sometimes it is not enough to push myself, I need an outside force.

External Incentive

People can provide a big external incentive. For an example of this, check out how hard sometimes people try to impress people they will never see again at stop lights. I know that I have been guilty of similar behavior, just not Green lightat stoplights. Being a part of an online community helps in finding motivation, as there are other people trying to do the same thing that you are. Motivation can come from anywhere, from a blog or even twitter. I found motivation in both places. After reading Ed Leighton-Dick’s post, I found an external motivator. His blog also showed me how powerful a post can be. Thanks to twitter, a lot of people saw his post and a number of people in the SQL Server Community have posted links and wrote their own blogs in support of his efforts. As I am sure Psy can attest, one can never know how much people are going to respond to what you put out on the internet, so kudos to Ed to being the Psy of the SQL Server Community. A number of people are now finding themselves motivated to bring their thoughts out of their head and onto the keyboard. Sharing of knowledge will help us all get smarter and better at our jobs. If you happen to be on twitter and see an interesting blog post with the hashtag #SQLNewBlogger, thank Ed as he helped make it happen.


Yours Always

Ginger Grant

Data aficionado et SQL Raconteur