Tag Archives: professionalism

The best things from 2017 and what I am looking forward to in 2018

When I am talking to people about the year 2017, and what was important, I would repeat over and over: everything I was striving for during my 30+ years of professional career had happened. All wishes have come true. Which would inevitably lead to the question: well, Hettie, what are you going to next then?

And there are plenty and plenty of things I want to do, but first I wanted to reflect on 2017 one more time. I’ve already listed multiple times all our technical accomplishments, all the wonderful things I was able to implement in a real production environment.  But when I look back at what was the best, it is definitely working with our new tech team. As I am reiterating over and over again, “the database is a service”, and whatever we are doing inside the database, can only make any impact, if our results can be utilized by “somebody” – by our end users.

And most of the time our end users are  application developers.  I can’t imagine any serious database development without continuous interaction with the rest of the development team. For years my “golden standard” for the teamwork has been my work for New York Department of Education, where I had a full support of the tech leadership, which helped me to defend my approaches and produce the results I am still happy about.

But what has being going on in the past several months is even better. The way we discuss the user stories. The way we make decisions on what should go into the application, and what – into the database. The way we debug. The way we discuss, what is critical, and what’s not. The willingness of each of the team members “to go extra mile”, to adjust in order to make others job easier. Basically, whatever I could imagine for the teamwork being perfect, is there. 🙂

Being in this industry for 34 years, I know that nothing lasts forever:). I know that every tea,, every organization evolve, and that nothing is granted forever. But I also learned to be thankful for what’s going on right now, and enjoy the moment.

Looking forward to 2018 – I hope that our team will continue to be the most amazing team ever. I am looking forward for the stress -test of our new applications with high data volumes. After all, I was designing the data storage and data access to be super-scalable, and I hope that it will work this way.

I am looking  forward to use the performance data we’ll obtain to improve our bitemporal library, and I already have some ideas of what I exactly I want to do. Actually, I have new technical ideas on almost everything I’ve developed through the last year. I still didn’t get notifications on whether any of the papers I’ve submitted for the next year conferences were accepted,  but I know that both are very good papers :), so even if none will get accepted… I will try for another conference!

 

 

 

 

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The Data science education panel on ICDE 2017

In order to keep up with my own promises to tell more about what was happening on ICDE 2017 I am going to write about the panel on data science education. The panel was called “Data Science Education: We’re Missing the Boat, Again”, and I’d say it was probably the most interesting panel I’ve ever attended! By the time the panel was about to start, there was a huge crowd, and people were encouraged to take a dozen of remaining seats in the first and second rows (do I need to mention that I was at the front five minutes before the panel started?)

The topic of the panel described in my own words was the following. The Data science is a buzz word, students want to be taught “data science”, and there is a common believe that data science is about machine learning and statistical modeling while in reality 80% of time of the data scientists is spent on data pre-processing, cleansing, etc.

The panelists were given the questions which I am copying below.

If data scientists are spending 80% of their time grappling with data, what are they doing wrong? What are we doing wrong? What can we teach them to reduce this cost?
• What should a practicing data scientist learn about sys- tems engineering? What’s the difference between a data engineer and a data scientist?
• Scale is at the heart of what we do, and it’s a daily source of friction for data scientists. How can we teach funda- mental principles of scalability (randomized algorithms, for example) in the context of data systems?
• Perhaps data scientists are just consumers of our technol- ogy — how much do they really need to know about how things work? Empirically, it appears to be more than we think. There is a black art to making our systems sing and dance at scale, even though we like to pretend everything happens automatically. How can we stop pretending and start teaching the black art in a principled way?
• How can we address emerging issues in reproducibility, provenance, curation in a principled yet practical way as a core part of data engineering and data systems? Consider that the ML community has a vibrant workshop on fairness, accountability, and transparency. These topics are at least as relevant from a database perspective as they are from an ML perspective, maybe more so. Can we incorporate these issues into what we teach?
• How much math do we need to teach in our database- oriented data science courses? How can we expose the underlying rigor while remaining practical for people seeking professional degrees?

Bill Howe from UW was a moderator and the first panelist to give his talk.

The second one was Jeff Ullman, and thereby I have nothing more to say:)

Actually, i really liked the fact that he mentioned, that the math courses, linear algebra and calculus should be included into the Database curriculum.  I was always saying that nobody without Calc  BC should be allowed anywhere near any database.

The next panelist was Laura Haas, and again – what else I need to say, except of I’ve enjoyed each and every moment of her presentation?

One thing from her presentation which I find really important is that the Data science is not a part of the Computer Science, and not a part of Database management.  As Laura put it, “we provide the tools”, but not like “we” should teach the DS as a part of CS.

Next panelist was Mike Franklin from UC, and I hope this picture is clear enough for you to see a funny example of DS he is showing.

And the last one was very controversial Tim Kraska from Brown, who started with “he is going to disagree with all the rest of panelists” – and he did.

To be honest, it’s very difficult to write about this panel, because each of you can google all these great people, but you would need to see a video recording of this panel to really fell how interesting, and how much fun it was.

After the panel I talked to several conference participants, who like me are from industry and asked them what are they looking for when hiring recent grads. And literally everybody said the same thing that I was thinking about: they said they hire smart people with solid basic education, people who can solve problems, “and we will teach them all the rest”. Which I couldn’t agree more!

Paradoxically, the students think it’s cool to have something about “Data science” in their curriculum, they often think it will make them more marketable, but real future employers do not care that much!

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Chicago PUG updates

I am not sure how any of those who attended last week’d Meetup are actually reading this blog, but if you are one of those people who came to the Braviant office last week – thank you! And I hope you’ve enjoyed it! I certainly did, I think this event was a great success. Both speakers where just outstanding, and the audience was really engaged.

Here are some pictures:

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ACM Hour of Code Dec 5-11

I am re-posting the ACM newsletter about thee upcoming Hour of code – please consider organizing something in your community!

 

Organize an Hour of Code in Your Community During Computer Science Education Week, December 5-11

Over the past three years, the Hour of Code has introduced over 100 million students in more than 180 countries to computer science. ACM (a partner of Code.org, a coalition of organizations dedicated to expanding participation in computer science) invites you to host an Hour of Code in your community and give students an opportunity to gain the skills needed for creating technology that’s changing the world.

The Hour of Code is a global movement designed to generate excitement in young people. Games, tutorials, and other events are organized by local volunteers from schools, research institutions, and other groups during Computer Science Education Week, December 5-11.

Anyone, anywhere can organize an Hour of Code event, and anyone from ages 4 to 104 can try the one-hour tutorials, which are available in 40 languages. Learn more about how to teach an Hour of Code. Visit the Get Involved page for additional ideas for promoting your event.

Please post activities you are hosting/participating in, pass along this information, and encourage others to post their activities. Tweet about it at #HourOfCode.

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How I learned to love tests: both using and writing ones – part 1

My fellow database developers, let’s be honest: we do not like writing tests. We are not application developers. We do not understand the test-driven development: at the end of the day, how we can figure out what should be the outcome of our functions and stored procedures, when we do not know what data they will be working with?!  When our managers tell us, we should generate the test data, we think its’ the most ridiculous thing in the world, because if we create some data, obviously the results of the testing will be favorable!

I understand, that not necessarily each and single database developer goes to that extreme, but… pretty close. And I will be the first to admit being guilty with the similar attitude. I only believed in testing on a “copy of the real data”, sort of A/B testing, which is important, but not the only thing to be tested.

Especially these days, when the data structure is not “almost always static”, when the changes the application DB are not a rare catastrophe, but a part of normal life of the application. At a minimum you want to have tests which show you that if you change”something” in the database structure, other “something” won’t break. We need those tests. But… it is so boring to write them! It slows our development process sooooo much! Especially, you know, when you have this big project to complete, and each and every half an hour matters!

At least that’s what I was thinking for the past two months working hard to bring our new Data Warehouse live. And promising to myself, I will write the tests… later :).

But my former co-worker, my forever-mentor, current consultant for my company – Chad – have written his test for “his”part  – which is a part of our system, which is responsible for “taking” to the third-party databases. So… on the night of massive changes on the said third-party database, which were not properly communicated in advance, when some parts of my processes started to fail… and when I fixed the data structures to match the new ones… the tests started to fail!

I was not happy :). Not happy at all. I was thinking – why?  Why I have to sit and fix these tests at 11-30 PM?! But guess what. It took me only 45 minutes to fix each and single test, which was touched by the change, and to validate the new data structures. And I was done before the midnight. And guess, how long it took other people to have their parts of the system updated and running with no issues? Almost the whole night, and almost the whole next day! You might laugh at the next statement, but here is it anyway: at that moment I felt very much protected by these tests.

And that’s what the tests are for, aren’t they?!

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About my new job, or – “you get what you’ve asked for”

Now, that I am already 3 weeks into my new job – it’s finally time to write about it. To be exact, there is absolutely no time to write, since I am so busy. But that’s what all my friends are asking about: what’s my new job, and why I made this move. Especially, because is was so fast, so sudden, with no announcement – and thereby for so many of my friends it came like a lightening on a sunny day.

Many people are asking me why I decided to leave, especially because I liked my previous job so much. I was thinking, should I write about this or not, and decided against it. After all, we all know: people change. Companies change. It’s not always uni-dimensional.  Is it good or bad, for example, that we are getting older? Good in some aspects, bad in the other, but it any case, this is an unavoidable change.

Companies change as well. And you might like or not like the changes – it does not matter, the changes are unavoidable. And you have to decide, whether you are going with that change or not, whether it is still your company or not… In this case, we went our separate paths.

One thing which came to me as a surprise – when I started to think what should be my next step, and where I want to be – I’ve realized how much I’ve changed after these five years at Enova. One thing I will never deny – working at Enova made me a very different person. Before that each time I was starting to look for new job I was thinking about stability. I was definitely interested in the creative and challenging work environment, but I wanted job security more than anything else. Also, I was avoiding any type of managing. Since my very early work experience when I had to manage a small team who would develop a system based on my methodology, I was afraid that if I manage, I won’t have time to code.

Now all of this changed. I’ve realized I want more responsibilities. I want to take a risk. I want to see a direct impact of what I do on how my company is performing. And I am not afraid of risk.

I’ve also realized that I it’s not enough for me anymore to just know “what’s the right way” and “how things should be done”. Now it’s even more important for me to lead people, to convince them that the way I want things to be done is indeed the best way.

More to follow:)

 

 

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About the work I’ve done for New York Department of Education

Since people are keeping asking me about this, and since I myself often mention my work for the NYC DoE as one of the most successful projects in my professional life, I thought it would be a good idea to tell in more details about it, what it was all about, and why this project is so important for me.

In December 2003 I was a consultant working for the Spherion Consulting Group. My assignment at this time was a new HR/Payroll system in the City of Chicago Mayor’s Office. I’ve being working on this project for quite a while by that time. One of our the Spherion directors, Ed, who worked there in the beginning of my engagement left to lead another Spherion project in New York. A couple of times he would email me asking whether I have any ideas on how to optimize some queries…

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