After a brief hiatus, we are back on the air to continue the conversation and let me tell you–we have a great conversation lined up for this episode. The discussion around what will happen to the relational database, and by extension us as administrators continues to get quite a bit of traction. Even within SQL Server, we are starting to see more features that don’t fit the traditional relational mode and a podcast listener inquired about getting our thoughts. As I thought about a guest for this episode, I didn’t want to get someone tied to a product. They, like me, would be biased and I wanted to get someone a bit removed from the situation.
Our guest today is Andrew Snodgrass, the research vice president at Directions and we chat about the future of the relational database and what the future of the data environment we manage might look like. I hope you will find his insights valuable as an outsider. While we don’t get into the specifics of what databases are mostly like to be around, Andrew does give us administrator some ideas on what technologies we should start exploring.
What are your thoughts around the future of the relational database? Join the conversation and let us know!
“So these things have come out as a natural result of trying to solve a problem that we weren’t able to actually do with SQL Server.”
“I think what’s going to happen is SQL Server is going to be there for traditional structured applications and database.”
“The great thing is that we can operationalize an R script in SQL Server.”
“If you’re SQL Server and you want to look at big data… you’re going to learn Hadoop.”
Listen to Learn
01:41 Thoughts about database evolution and transactional system
02:05 Ideas about big data and database tools and services
05:40 Single platform for data: is it a fair approach?
12:00 JSON data, storage cost and compute cost
12:48 Effect on the Data Team
14:15 R script on SQL Server
14:46 Role of the Express version increasing in organizations
16:44 Azure services, data lake analytics, U-SQL on organizations
19:05 Technical skills that are robust in line with big data and data warehousing
21:33 Segway about Power BI
22:28 Azure vs Containers
27:13 Andrew’s advice for executives investing in their data platform
30:57 SSIS, SSAS, Power BI
35:56 SQL Family questions
About Andrew Snodgrass
Andrew Snodgrass is the vice president of research for Directions, a organization that help guides IT executives on technologies, strategies, product roadmaps, and licensing policies. Andrew leads the research and analysis of emerging trends in enterprise applications (primarily ERP and collaboration tools) and database management technologies with a focus on Big Data, business intelligence solutions, cross-platform mobile application development, and cloud hosting services. Her is currently and adjunct professor for the Albers school of business and Economics at Seattle University.
*Untranscribed introductory portion*
Carlos: Andrew, welcome to the program.
Carlos: Yeah, we appreciate you coming and taking some time to be with us today. We have kind of an interesting topic. Ultimately, our audience, our SQL Server folks, and we think about SQL Server, you know, we think about transactional system. It’s been around for a while although it has definitely evolved a bit. But one of the common questions that we get is what about all these unstructured data and even in SQL Server now we are starting to see that influx sort of kind of with XML and now we’ve got JSON, 2017 is going to have graph databases, Python, R. All of a sudden we are starting to see this intersection of what we could traditionally think of unstructured and structured data commingling in the same environment that has a lot of people of questioning; and not to mention the rise of other databases, right? It’s 2017 and Microsoft comes out with a new database technology and they are not the only ones. There are databases almost sprout out as often as applications all trying to solve a particular problem. And so ultimately our conversation today is going to revolve around this evolution if you will and kind of where the transactional system is going to end up. So I guess maybe take us through some of your thoughts there and kind of what you’re seeing and maybe what some of your customers are asking you about the same idea?
Andrew: Sure, along that line I think some of the rise of the M structure, the big data, semi structured, all these stuff have come around naturally and I think that the introduction of database tools and other services and capabilities have come about because as traditional structured, traditional relational database guys keep trying to force fit unstructured stuff into structured databases. And so these things have come out as a natural result of trying to solve a problem that we weren’t able to actually do with SQL Server. And so I don’t know that it’s necessarily that we’re seeing any kind of decline in traditional databases or in the relational industry that we’ve always been dealing with. I think those types of workloads continue to exist. I think they are still going to continue to exist and you still got financial systems, you still got procurement systems, and these things lend themselves well to a traditional, relational structured database model. But they don’t do everything. One of the things that I’d always look at was how do we handle situations where you need some kind of lightweight database management system. And SQL Server despite some attempts to give us lightweight database management didn’t always do a good job of it and so when JSON came about, XML you could say a little bit, but really when JSON came about and the idea of saying let’s go mobile. Let’s push data out to self describing. These seem like natural solutions and now that we’re seeing SQL Server come back and say, “Well, we’re going to try to make so that you can tap those sources.” I don’t know that I would necessarily think that SQL Server is trying to be everything although Microsoft might like to portray it that way. I think that SQL Server is trying to tap everything. And so it’s one of these things where I’ve got my traditional product list, my customer list, all my transactions that are in a nice, structured environment. We are working an application that people know and trust and love but I need to be able to get into other areas. I need to grab data from other areas and push data out to other solutions. So they are putting these tools into our SQL Server environments so that we can interact with those things intelligently and more seamlessly so we don’t have to push to an ETL tool or we don’t have to do some kind of extraction and then modify the data to push it out somewhere else and then bring it back. We can kind of put all these things into one environment and control it there.
Carlos: We’ve definitely drunk the KoolAid. I’m Microsoft kind of through and through if
(00:05:00) you will. Is that a fair strategy as I go and try and talk with businesses? One of the things that I like about this idea is that at least it gives me a common tool set from someone who’s been in SQL Server now for 15 years. That I don’t have to go out and learn all these other platforms, right? Now, obviously there are some differences, R or Python, so there is a learning curve but at least from I know the data in SQL Server there are some administrative things that I don’t have to relearn. Things like that and I think it will be easier. But it gives me the ability on a single platform to have all of that data. I mean, is that a fair idea or a fair approach?
Andrew: I think a fair assessment on it is I think that from an additional enterprise standpoint, I think it’s very attractive and I like it personally as well, large organizations, medium organizations, anybody that has applications that they’ve developed over the years where they’ve invested. This isn’t just an investment in skills and application creation and the rest of that but they actually have servers and they have licenses and all kinds of other stuffs that go along with that and the idea of saying, “If I can take advantage of what I already have and expand on it instead of trying to recreate it. That sounds very attractive. Here is a great analogy on it. There was somewhat type of when we went from client-server to web-based apps. There was this need to recreate all these applications so they work in a browser and it would have been nice if we could have kept our applications to simply have more kind of browser. And that’s kind of what we’re getting at here is we have all of our data sources, all of our capabilities, but we want to extend it. And that doesn’t mean you need to learn how to write web apps and it doesn’t mean you need to learn JSON and convert data. It doesn’t mean that if you want to go to Hadoop you’re going to have to learn Polybase and understand how to do a scale out compute environment and being able to tap those resources and manage that data. You might need to learn some MapReduce at the same time. But this is learning additional things and not replacing what you already have. And that’s I think part of the attraction of beefing up SQL Server to do more than it was before.
Steve: And I guess the way I’ve seen this happen a few times that I have talked with different people is that they’re using SQL Server, they’ve been using SQL Server in their shop for years and then they realized. “Ok, now we want to do unstructured data.” Big data as they often times end up calling it. And then they decide, “Ok, well we’re going to go with Cassandra or DocumentDB or CouchDB or DynamoDB.” Or one of those that is totally separate from anything that is SQL Server. I find that sort of the story goes with those oftentimes is that it’s kind of a decision. Are we kind of keep doing SQL or are we going to go with this other database or are we going to do a merge there or sort of using both sides of it. IT sounds like what you’re describing here is taking advantage of what’s being added into SQL Server so that we don’t have to go and look at those other technologies. Is that where you’re going?
Andrew: No. Actually, Steve, I don’t think that’s kind of the case. I think the merge is what’s going to happen ultimately. It’s kind of like buying a stereo system that’s an 011. You basically get a very generic set of components. If you really want the best you buy separate components. And I think what’s going to happen is SQL Server is going to be there for traditional structured applications and database and stuff but people are still going to be looking at Cassandra, cloudera, Hadoop, any of these for a true multiprocessing, parallel processing capability that they really don’t want to spend the money to try to make SQL Server do. The idea of that is if you go to a bid data solution you have a distributed computing environment with a lot of servers out there. Each with some local storage so that the computing the query happens locally on the data and you use parallel processing to do a lot queries across a lot of unstructured data at once to return the said information. If you try to do SQL Server to do a
(00:10:00) scale out and that same type of configuration your licensing cost alone is going to kill you. It doesn’t make any sense to say that you’re going to have 50 or a thousand servers each running a SQL Server Standard/Enterprise edition license. Oh my god, I can’t imagine the amount of cost that you’re going to have there. So what you’re actually looking at is you got a SQL Server environment that’s very powerful that has some really good SQL Server capabilities on it that uses Polybase to go out and tap that unstructured data that’s actually in a proper Cassandra, Hadoop deployment. If you really need to get in big data you’re going to have to look at a proper big data solution to host the data and run the compute. But you don’t have to run those stand alone. You don’t have to just do a MapReduce to get a data set that then you have to go through Integration Services or some other ETL in order to get in what your structured data. You will be able to do that directly from SQL Server so that you can query your structured information, your product list, your customer list and you can do sentiment analysis against a bunch of unstructured data out in Cassandra and bring those together in real time. That’s where I think the merging and the intelligence is going to be.
Carlos: Interesting. I think kind of with that a common point is like IoT, right? So you’re collecting, so all these sensors have all these information. SQL Server probably may not make the most sense for the repository for all of that information, right? But you have these sensors, you know, caches that on the web which you can then pull in to a Hadoop cluster or whatever else and then start to do that aggregation or some of that analytics on it and then pull in kind of the summary information and that maybe what you store in SQL Server and then of course then there is the reporting on top of all of that.
Andrew: Right, and that follows, Carlos, in the same line with the idea of JSON. It’s great that you can some native JSON stuff within SQL and you can push data out and pull data in. But from a storage cost and compute cost do you really want to store JSON data in blob columns within the SQL database? You are going to run some cost and performance issues that you might not want to deal with so I don’t think that’s necessarily the road with the JSON side either. I think store it where it make sense, where it is optimized and where it belongs. But I want to do stuff with that data and I want to do it in real time and that’s where bringing it into SQL Server and attaching it to business data make sense.
Carlos: So then let’s talk a little bit about the effect, are the data team just going to get bigger? I mean so we have like cache and some of this other caching layer that the programmers are already kind of doing. So now we start adding Hadoop and we’ve actually done an episode on Polybase. Now Polybase is still kind of an emerging technology. They kind of came up with the v1 but those worlds are still kind of very different so does that mean that I’m now going to have a SQL Server person, I’m going to have a Hadoop person, I’m going to have a Cassandra person or are you seeing organizations say, “Ok, guys. Now, it’s time to go learn Hadoop and you’re going to be responsible for both.”
Andrew: In some, and it depends on the size of the company. The really intelligent ones are investing in data architecture. It doesn’t matter just of saying we want big data you know everybody says that. How do you do that and how do you do it without spending too much.
Carlos: So the plumbing, the connections have become very very important. How’s that data is going to move and flow.
Andrew: Right, and so and the same thing is true now with machine learning. It’s great to say that we have R and Python in 2017 but what are you running this against? And what type of performance that you’re going to take on your servers with it. The greatest thing there isn’t suddenly we are able to do R scripts within SQL Server. The great thing is that we can operationalize an R script in SQL Server. And it’s that I’m going to R Studio. I’m going to build my script and I’m going to test it out in my data. I want to make sure everything is the right way and then I’m going to put this into a stored procedure and make it part of my application so that it performs the R script on the data, the right data, at the right time and then gives my users something useful.
Carlos: Exactly. I think now, so having said that do you see the role of the Express version increasing in organizations? I feel like adding some of that functionality
(00:15:00) to Express was a direct result of the rise of open source and particularly MySQL. And so to that idea now that I have the capabilities, and when we start creating these models maybe we don’t need 10 years worth of data. I need a month’s worth, a quarter’s worth. And then I can push that off unto an Express version let my data scientist or analyst or to whoever run all the items they want and then once they’ve decided, “Oh, I think this is where we want to go.” Then again kind of that integration, that’s in SQL Server already I could just move that into my production environment and have a more seamless experience.
Andrew: That’s a really interesting question on that. Most of our customers tend to be larger enterprises and so they have their MSDN Visual Studio subscriptions and even the data scientist they are putting MSDN Enterprise edition on or Standard and running it from there. I don’t know any answer for that. I think you probably could.
Carlos: Sure, the limitations that you’re going to run into. You know, 10GB or whatever. But again it’s that I can move that off my environment with the flexibility I get the tools so I guess I’m kind of interested to see how that plays off or plays out. Obviously, if you are Fortune 5,000 Company maybe that doesn’t makes sense but for these smaller organizations they have a couple of people trying to work on this. It will be interesting to see what happens I think.
Andrew: You know, on that line opening the door on that one for some of the may have customers both large and small we are seeing the use of Azure services spinning up capability there, moving data out, testing it out and then scaling down is a way of getting around local deployments and testing. Like Azure SQL Data Warehouse, all of a sudden you’ve got somebody who has 10 or 15 years or 20 years with a historical equipment data or performance data and they push this up to an Azure service and then run one of the analytics services against it. You know, they are doing some machine learning and some bigger analytics that they would never attempt on premises.
Carlos: Sure, because once they’re done they could just toss that out or spin it down.
Andrew: You know, and along those lines you’ve got Azure Data Lake analytics which was supposed to be originally just for going against the Data Lake storing environment with a bunch of unstructured data and all of a sudden they said, “Well, you know, we could tap into SQL database. We could tap into blob storage. We could tap into data warehouse.” And Data Lake analytics is all based on U-SQL and so we’ve got a really nice environment here for people that are comfortable with traditional SQL Server query capabilities to go out and run some really cool analytics and learn just a few new functionalities that are required for U-SQL and you got a scalable system out there to run these queries on that you don’t have to do on premises.
Carlos: Yeah, it’s very cool. I still think that some of that is like you mentioned for the larger organizations. I think as we start talking with people, I mean, there are those who are putting quite a bit of time to learn the U-SQL and take a look at Data Lakes. And I think obviously the bar is lowering but that’s still an investment right to take the time to learn some of those things and understand how they work. I guess like everything, all the technology continues to evolve and change.
Steve: Yup. It’s interesting because when we had our podcast talking about building your technical skills few weeks ago, one of the things we talked about was sort of the type of things that you can learn that stick around for a long time and the type of things that you can learn that are maybe a little bit riskier but they may go away or they may change rapidly. And it seems like some of the unstructured and big data and data warehousing pieces today are kind of within that riskier category because they are still sort of changing quite a bit. I mean are there any of these that you see that are kind of more robust to the point that or more mature might be the better word to the point that they are not changing quickly
(00:20:00) these days?
Andrew: Yeah, actually. Especially with the folks that are going to be listening that are SQL Server folks. You know, along that line if you take a look at Microsoft’s database landscape and say you’ve got structured, unstructured and semi and everything in between, the two that you would go into that are not SQL Server would be Hadoop and JSON. Hadoop is underpinning so much to the big data investment that Microsoft does into that if you want in SQL Server you’re probably comfortable to start learning Hadoop and understanding that environment. That was the whole concept behind Polybase was to touch Hadoop. If you actually look at the Polybase scale out concepts, this is a Hadoop cluster methodology for doing compute nodes. If you look at the Azure services you got Data Lake which is a Hadoop environment on the backend. You got Cosmos DB which is actually a Hive environment in the back end, and then you’ve got HP Insight which is multiple Hadoop type clusters that you can choose from there to do any kind of scale out environment you want based on the type of workload. Yeah, if you’re SQL Server and you want to look at big data and you want to say comfortable with Microsoft you’re going to learn Hadoop.
Carlos: Ok, interesting. There you go companeros. You’ve been warned. You heard here first.
Andrew: Yeah, and while you’re at it, learn some Power BI because Microsoft is investing in that.
Carlos: Oh yes, that is true. What it’s interesting I think that still kind of goes back to the plumbing. We’re actually starting to see traditional SQL Server people/folks trying to spin up Power BI environments and you’re like, “Hey, really cool reporting tool.” You know, the functionality is there, web browser and all that but then tickets are a little too big and they are like, “Hey, how to make this go faster?” And you’re like, “pull that out .csv file.”
Andrew: And then you do a Power BI premium where you have dedicated capacity or you end up doing a Power BI report server on premises.
Carlos: Yeah, that’s just coming out and it will be interesting to see that integration with Reporting Services that continues to evolve. I wanted to circle back quickly if we could because you mentioned Azure. We’ve actually talked a little bit about containers and containers particularly in the Linux world has been all the rage but it almost seems like maybe, I don’t know if competition is the right word, because ultimately the technology that they can give are different. Well, Azure versus containers. So if you’re a large organization and have an investment or haven’t made the move to Azure to that whole spin up for the way idea. I feel like that’s what containers are also trying to provide you. So is it an on premise Azure competition there when we talk about containers?
Andrew: Like yeah, that’s an interesting one. Maybe I’m too old struggling to find out a really good set of examples of doing containerization of apps and saying we’re going to put this out here especially when it is database related app. It seems like there is an off light you’re going to put in that container in order to make it work. But you know it’s interesting in Azure right. Microsoft’s whole move towards Linux anyway with SQL Server 2017 coming on Linux and the containers and all the rest of that. Azure has the Azure container services which has been out there for a little while, a year or a year and half, that allows you to spend up VMs and containerize things and then everything in it. But they’ve also just released a thing and it’s in preview right now called Azure Container Instances. And this is one where it’s a true platform as a service type. They provide complete control in the infrastructure so you don’t know the backend VMs. All you do is you’re seeing computing resources. I mean this many CPUs, and this so much RAM and here is my container image. Pow! Put it up there. Scale it as much as you want, run it as long as you want and then kill it. You don’t worry about the VMs or any of the backend stuff. You can throw SQL Server into this, and you don’t know if it’s Windows or Linux and doesn’t really matter because there is web access to it anyway. You get the URL and you just run it and you go for it. And so that’s another one where Microsoft is just trying to say we don’t really care on the
(00:25:00) platform. We know it’s the service you want and so here is how to go about doing the container and you don’t care what’s happening on the backend side of things.
Carlos: Now, I feel like the best example, and so we had Andrew on the program, different Andrew containing about container. The thinking was and I guess I’m inclined to believe it is that, at least from a database perspective. I can’t speak to the apps. You could do lots of different things with the apps but the best or the classic case for containers in the database is a development workshop. If you’re building like .com type of thing, right? If you’re a actively doing development that whole idea of, “Ok, once you’ve published or once you’ve pushed code. Ok now, let me take that snapshot, create a container, push that down back to all the developers.” So now I know they are developing against what is in production and it helps eliminates some of this migration issue.
Andrew: Yeah, that sounds very internal.
Carlos: I don’t think we’re quite, although I have heard a few people talking about it, I don’t think we’re quite saying that we’re going to throw containers at production databases just yet but.
Andrew: Yeah, you know, sometimes I hear so much about containers right now and it takes me back when we first heard about big data and then about artificial intelligence and it’s like, “Oh, I’ve got to get me some of that. I don’t know what I’m going to do with it but I got to get me some of that.”
Carlos: That’s right, so having said that what your ultimately with the directions, your organization, your consulting CIOs on technology choices. Now, obviously your mileage will vary right and it depends. It’s going to come into here but what’s your, I know we covered some of this pieces, and I guess you’ve already mentioned if you feel comfortable with SQL Server, you feel pretty safe gambling on Hadoop, not gambling but learning Hadoop. You know, taking the time to that could be your next foray. What else are you advising these executives in making investments in their data platform?
Andrew: So the things that we’re pushing or talking people about now is really along the lines of how do you take advantage of not only big data and machine learning capabilities…
Andrew: There you go they are implementing IoT and so that’s one of the things that we tell the folks is not necessarily to jump in because these guys aren’t going to do major investments or major overhauls. These are like organizations that have to plan out years in advance of what they are going to be spending their money and then get authorization for it and have to justify it. They’re getting a lot of CFOs and other CxOs that are reading too many magazines on airplanes that are coming back and saying, “Why aren’t we in big data? Why aren’t we doing artificial intelligence? What about IoT for our organization? How come we are not doing better analytics and all these stuff?” And so we’re trying to show them what Microsoft approaches to a SQL Server and data overall, and in fact we’re doing one here in another week on business analytics and business intelligence and how this are all working in the vision going forward and where the investments are happening and where should you spend your time now and where you should do it in the future? And so we think machine learning is actually far more mature than people like to think to this. Especially in a traditional business environment, there is a lot of stuff that is out there that the community has developed over the years either on R or Python. Now is the time. If you were ignoring it before saying we got to wait and see, now is the time to jump into it. The other area that we’re telling them to get into is taking a look
(00:30:00) now at better business intelligence and data sources on premises. This whole Power BI Report Server if you guys haven’t spend time in it we’re telling them to bring that in and take a look at it. One of the other one that is kind of surprising is any traditional ETL workloads that you have going on were you’ve been suing integration services for years. You know, ETL is changing, the idea that SQL Server’s database engine has the ability to go out and tap these resources in real time and do transformations. You might not be doing ETL the way you did for the last 10 years. Integration services, I don’t see getting a whole lot of investment. I see a lot more going into analysis services. We’re going to do real time queries and being stuff together and transform it there not in Integration Services. And so I think that’s going to be kind of a change for organization. You know, and that’s going to be one if you’ve invested in SSIS you’re not going to go out and swap it next month or next year. This is going to be like a multiyear thing. New stuff we bring in, we’re going to actually bring in directly. We are not going to run it through an ETL.
Carlos: Well, now see you’ll forgive me I guess maybe that my connections aren’t quite there. How am I getting the data? When I think of SSIS, I am thinking about it is that glue that takes me from my transactional system, into my cube, or it’s doing some transformation there for me. There are additional components now. I mean, we’ve talked about Polybase, so SSAS, the analysis services, now has these connectors to actually go out and grab this information in an ample time.
Andrew: Oh yeah. 2017 baby! Here we go, so Analysis Services in 2017 supports the M language. So all of the sudden all of the stuff you we’re doing in Power Query and Excel and you’re bringing stuff in and grabbing different sources, and maybe going out and getting a file list instead of just another data source that’s all coming in 2017 Analysis Services. So the big reason for that isn’t necessarily to make analysis more functional which was kind of nice outcome from it but they wanted to bring Power BI, and Power BI is all based in Power Query. And so in order to support that with Analysis Services in the new Power BI report service thing which is basically Reporting Services plus they had to bring in the Power Query engine capabilities.
Carlos: Ok, so now there is another dot connected because I know at least the initial version of Power BI Desktop, so the new version that you can download and install locally that only supports connections to SSAS. And I guess it makes more sense now if SSAS has a bit more functionality in it for you to take advantage of some of these other data sources because I think initially when I looked at that I thought, “Oh, that’s all going to be all cube data. I don’t want to always do that.”
Andrew: Yeah exactly, and it’s not. So what is Power BI report server when you bring it down and you install it basically we work on that reporting services plus because it’s just really the same thing. There are a few other things. You’re on a modern life cycle for updates which I don’t particularly like but that’s reality. But you can host your PBIX files and so you’ve got that capability. But the PBIX files that’s the only one that’s limited right now, the rest of the RDL stuff and KPIs and all the roster are full capability. So the PBIX files that you have there can only go through an analysis services cube which actually winds up being your gateway which then you have to think of in that scenario analysis services being like SSIS. It’s the glue that goes out and grabs everything and brings it in, right? Now, that’s the first three to Power BI report server hosting so you’ll see that expanding. They are going to all kinds of data sources for PBIOX files so I don’t expect that to be limited for more than a few months.
Carlos: Ok, very good. Andrew, thank you so much for visiting with us, great conversation. I wish we could go on for a bit longer but I know that we need to wrap it up here. I guess last thoughts. Steve, do you have any last questions.
Steve: No. I think that there is just a lot going in this space and keeping on top of it is going to be interesting I think. Like we are talking with Power BI so Microsoft is investing so much in Power BI these days that everything it touches is sure to expand down the road in the near future. So I think that’s a pretty safe bet. I
(00:35:00) think there is a lot of interesting things to come here in the near future.
Andrew: Have you guys ever wanted to talk about that one in a separate one. Power BI is one of the other cover, not for this broadcast obviously but in the future.
Carlos: Yes, of course we’d love to. Again, particularly for this conversation we wanted to have somebody who was obviously familiar kind of covering that beat if you will but didn’t work for Microsoft.
Andrew: They are not even a customer of ours.
Carlos: To see just how that continues to play out. I think we touched on it a bit but we as database administrators we have our homework cut out for us. I think it will be fun to see how that continues to evolve as time goes on. Shall we go ahead and do SQL Family?
Steve: Yeah, let’s do that, so Andrew how did you first get started using SQL Server?
Andrew: Up until 2008 I was really kind of a Sybase kind of guy. I know it takes me back a while. We had a need for standalone database engines and Sybase was one of the early ones that allowed you to have a decent relational database environment that you can have on a separate machine. We have a bunch of travelers so they needed that and I did not want to go into Access or FoxPro which is where we originally started. So there’s Sybase and then as things progress we saw the direction for SQL Server and that became our standard and we moved over in 2008 and never looked back.
Steve: Ok, interesting.
Carlos: There you go. Now, as you’ve been covering SQL Server since then and then working with it. If you could change one thing about SQL Server what would it be?
Andrew: Yeah, you don’t like this. I changed Management Studio actually.
Carlos: Oh boy! Here we go. You know, because they have broken that out. They have their own development cycles now. Let’s see. What don’t you like about SQL Management Studio?
Andrew: Well, I like a lot that’s in it. I think the thing that would benefit them is as if they would make it easier for new entrance. One of the things that I find that is most difficult with new developers and new database people we bring in isn’t learning SQL or learning database structures. They’re getting all kinds of education on that. But setting it up, accessing it, using it, you know, some wizards something in there for the new guys to be able to get in and use it would be nice.
Carlos: Sure, kind of updating that almost to like a web type interface which is a little more intuitive. We’ve have all those buttons everywhere and you’re like what kind of I’m looking at.
Andrew: Yeah, and they got some stuff that’s nice but few years back we would seek new people and say, “If you really want to see how to build a query on this? Let’s do this in Access. See this nice wizard, we draw all these tables together.” Oh look at that that great query. You know, the query works on but into Management Studio and running it as a query there, “Look it works.” Why can’t they do that there?
Steve: Very good point. And I think, I mean personally I love what you can do with Management Studio but I have definitely seen the challenge when you have someone who is first time ever using it. They sort of get dumped in and don’t know where to go. There is this huge hierarchy in the preview in the left side that you can expand. How do I get to other query? Can be a little the bit daunting in the beginning?
Andrew: Oh yeah, the wizards for setting up jobs was nice. Being able to go through and take a look at especially some of the new views and performance capabilities. These are all great stuff but I got new people that we would like to get engrained in this just to make their lives a little easier so they get addicted as well.
Steve: Alright, so what is the best piece of career advice that you have received?
Andrew: Early on someone told me, “Don’t get worked up about office politics.” I said, “Look, focus on doing a good job and the people you really want to work for will notice that and promote you and those who don’t care about the good work you do.”
Carlos: Good things will come to those who wait.
Andrew: Oh yeah, and if they don’t then you’re in the wrong place.
Carlos: Sure, yeah, and then think of all the time that you don’t have to spend worrying and talking about, “Oh, what are they going to do with.” You know, I don’t like this person.
Andrew: Exactly, yeah. Just don’t worry about it. Just go to your job.
Carlos: Very good! I like it.
Steve: You know, that’s one of the things that I like about on the consulting side is
(00:40:00) you’re there to do the job and not to be in the politics. I like being on that side of it.
Carlos: Andrew, our last question for you today. If could have one superhero power what would it be and why do you want it?
Andrew: I know he gets ridiculed all the time especially on big bang but I really like Aqua Man. And his ability to breathe under water so that I could basically do scuba without any kind of limits. That would kind of eminent. Lots of people is cool too but this ability to breath underwater that’s my thing.
Steve: Hey, if you figure that out let me know. I’ll go with you.
Andrew: Yeah, but not around here. It’s too cold. We’re going to go south.
Carlos: I said that would be the last question but just one follow up. Where is your favorite place to scuba dive then?
Andrew: That’s going to be the Caribbean and basically anywhere, 7 mile off coast of Mexico, any of it. Just go down about 70 to 100 feet and forget the world exists.
Carlos: And you’re there. Wow! Andrew thanks so much for talking with us today. We really appreciate it.
Andrew: Oh, you bet guys, that’s a lot of fun.