SDS 087: Business Intelligence – the role of Data Visualization

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Welcome to the SuperDataScience podcast. My name is Kirill Eremenko, data science coach and lifestyle entrepreneur. And each week we bring you inspiring people and ideas to help you build your successful career in data science. Thanks for being here today and now let’s make the complex simple.

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Welcome to the SuperDataScience podcast, super excited to have you back here, and today we’ve got an interesting guest, Deepak Prasad. Deepak is a Tableau and Qlik expert, and he works for a company called ASG Group, where he’s a consultant, and he helps other companies to implement business intelligence in their business. And what business intelligence basically entails is developing business intelligence dashboards and tools which can be helpful for executives, managers, and just generally other people in the business to see their data and understand how the business is progressing in various areas, whether it be finance or HR or perhaps operations, and so on.

So we’ll be talking a lot about business operations, and Deepak will give you some of his insights about Tableau, Qlik, and Power BI, and we’ll touch on a couple of other tools as well. And of course, he’ll give you some tips on his best practices in business intelligence, so stay tuned for that. And, finally, Deepak will share parts of his journey and how he structured his career in this space, and how it brought him to where he is now. And he’ll give you some of his best tips on how to have a fulfilling career as well.

So I can’t wait for you to check this out, and without further ado, I bring to you Deepak Prasad.

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Hello ladies and gentlemen, welcome back to the SuperDataScience podcast. Super excited to have you here, and today we’ve got an inspiring guest, Deepak Prasad, on the show. Deepak, welcome. How are you going?

Deepak: Fantastic and really energetic to talk on this podcast.

Kirill: That’s good. Where are you calling in from?

Deepak: I am signing in from Sydney.

Kirill: Sydney. Ok, so it was really cool how we were talking before. You mentioned that you would never live in Melbourne because what? Why wouldn’t you live in Melbourne?

Deepak: Basically, I come from a tropical climate. So anything below 20 is a bit of a pain for me and very tough to accommodate, so I don’t want to take risks in that aspect at least.

Kirill: Yeah, totally get it. Totally get it. And I really want to share with everybody the chat that we had with Deepak just before the show started. Deepak, you have a baby boy, right? 2 years old?

Deepak: Yeah, his name is Aryan.

Kirill: What is his name?

Deepak: Aryan – A-R-Y-A-N.

Kirill: Aryan.

Deepak: Yeah, exactly.

Kirill: Wow, that’s so fantastic. Congratulations. It’s always exciting to hear when people start families. And you were like — Deepak said to me, “Kirill, there’s one thing that I’d like to one day find out.” What did you say, Deepak?

Deepak: I really wanted you to get married and I wanted to see you again after marriage, whether you’re able to tie up with this podcast and regularly do productive stuff or not. So I just wanted to put you under an experiment that’s called marriage.

Kirill: Well, hopefully it won’t be an experiment. It will be, like, one day for good. But you want to see how my productivity will drop after marriage, how it will change?

Deepak: No, I really want to see whether it’s going to drop or it’s going to increase. It’s either way.

Kirill: Yeah, okay. I found that funny. And we both agreed that it’s a matter of priorities. Once you’re married, there’s just other things that you care about in life. You know, right now, for instance, I love travelling. I love doing sports and cool stuff and just seeing what life has to offer. But once you’re married, it doesn’t mean that you stop, or you become boring, or you’re less productive, or whatever. It just means that there’s other things. Like, you might spend less time on creating products or courses or something like that, but you spend more time with your kids and family, and I think that’s a very, very noble and important and loving and fulfilling thing to do. How do you feel about that?

Deepak: Very true. Just imagine me after a tiring day at work returning home, seeing my wife and kid playing and having fun, and my kid jumps on me and says he missed me and stuff. That keeps me going. That whole day, whatever tiredness I had will just vanish as soon as I see my kid laughing. So things like that will keep you going. Although you say you cannot do certain things and you cannot plan and you cannot act as per your plan, but things like happiness, seeing happiness from your kid and your wife keeps you going.

Kirill: Yeah, I can totally imagine. I feel the same about my family and my friends. Yeah, I can totally imagine that. You definitely need those parts in your life. Otherwise, if you’re just working all the time, you’re never going to be happy. You might be successful, but you’re never going to be fulfilled. I think this is even more important than work.

In fact, I’m actually in the Czech Republic right now, and I have a friend here, and we just had this conversation today. Even though he’s not super successful in his career and he hasn’t made millions of dollars or billions, he’s super happy because he’s travelled the world, he’s done what he’s wanted, he’s got a lovely girlfriend, he’s in love and he’s just living a very fulfilled life. It was very inspiring to see.

Deepak: True, true. You’ll get into the game, man. I wish I could learn from you.

Kirill: Thanks, man. So, Deepak, tell us a bit about yourself. I’m looking at your LinkedIn and it says you’re a Tableau and Qlik intrapreneur. A lot of people have heard the word ‘entrepreneur.’ What does ‘intrapreneur’ mean?

Deepak: Intrapreneur, as the word says, is like promoting some products and tools across various organizations. So, when it comes to technology, you will become an expert, and once you become an expert, you understand its pros and cons. And once you understand it, you get to expose it to the people, you get to expose it to the right persons. So that’s my day in and day out work. I go to people, talk about their problems and I tell them that this is what will work out after listening to them. If I straight away go and sell my product just because I have it, that won’t work.

Kirill: No, it makes total sense. So you’re kind of spreading the data analytics and data visualization culture within your organization, is that right?

Deepak: Yeah, exactly. Basically letting the people know the power of visualization.

Kirill: Okay, that’s really cool. And how is that going? Are you finding a lot of resistance, or are people generally quite open to learning about these things that you’re sharing?

Deepak: When we talk about visualization tools, and when we explain how it works and how it can help, although it’s not the first thing, people will come and conclude the conversation with “How much does it cost?” That would be the first question or the last question. Everyone would finish it. So I always make sure that the old technology and old processes, what we listen — and we should not be suggesting some “old process plus new technology”, as quoted by the HP CEO, I believe. So it should not be the case that old process plus new technology is equal to expensive old process.

So I make it as a statement in my everyday work. I should not suggest something which is just a new technology alone, I should improvise the process and the behaviour of people of any organization and then I should show them an insight. If you just throw a new technology at people, it will not work out. You should understand their data culture. You should ask them more questions, and you should ask them what they’re currently doing and you should really consider them with a current process and the technology you’re trying to bring in, is that the value proposition that’s going to be good or not. That’s the equation you have to arrive.

Kirill: Okay, gotcha. I’m just trying to rethink is. Help me out here. So, you are a consultant, and you go into other organizations and then you look at the processes and you decide that “You guys will benefit from Tableau,” or “You guys would benefit from Qlik,” and then your goal is for these organizations to adopt these products. Is that correct?

Deepak: I would say 70% correct. The reason is I wouldn’t just talk about Qlik and Tableau. Since I’ve been in visualization for five long years, I know Qlik, Tableau, Power BI and many other tools. We also evaluate other visualization tools in the market. For example, I’m keeping an eye on tools like ThoughtSpot, which is really a disruptive innovation, as I call it. It is definitely going to turn the industry upside down one day. So, some tools like this, you have to keep evaluating and understand the pros and cons.

So when you said Qlik and Tableau, I would say no, those are not my only verticals. Because I have seen the pinnacle of Qlik and Tableau, so I call myself a Tableau and Qlik intrapreneur, but if I feel that Tableau and Qlik will not fit an organization considering their current process, I would say that “Qlik and Tableau will not fit. Try something else,” which means I can suggest these things and these are the services I can provide you.” So that’s how the dealing should be.

Kirill: Okay, gotcha. I’m just trying to compare that with what I did at Deloitte. It’s a bit different because there, we used Tableau, or some other visualization software at Deloitte, within the organization, in order to then solve some challenges or solve a case for our client and then deliver the results. We didn’t actually go in and say, “You need Tableau.” We did the work inside and then we just delivered the results. It might have changed since then, or maybe I just worked on those types of projects, but that’s my experience. But for you, it’s a bit different. You not only deliver the project, you actually want to help the organization change their processes so that they can further down the track keep doing this on their own.

Deepak: Yeah, that’s true. The other thing when it comes to business intelligence, as you know, it’s also called a Decision Support System, so if something is supporting your decision, it has to come along with your culture, behaviour and other stuff. So, for me, data visualization is not just a technology. It blends people well together, then only you can win. So anything you produce and no one is there to view your product, whatever it may be, rocket science for you, but if the user utilization is 2%, what’s the point in coming up with a rocket science which no one uses? So when there is a demand, you should push it and you should create a demand. The behaviour of the people has to be initiated, elevated in the right way such as that they adapt to the new technology and they improvise the process and everything.

Kirill: Okay, sounds like quite an involved process, you would spend quite a bit of time. On average, how long does it take for you to complete one of these projects?

Deepak: When it comes to project, I wouldn’t call it as a project. I would rather put it as a “solution”. So you talk to persons, you understand what they do day in and day out, and then you understand what problem they are facing. Once you get to know their problems, then you get to know what are all the possible solutions you can come up with. There might be a scenario where a solution can just be implementing a product like Qlik or Tableau, or you might be saying that the way you ingest the data and massage the data itself is wrong, so we will give you a resilient database and we will give you a fantastic data mark which consolidates the data from your whole organization and brings it to a single place and then we will plug in a visualization tool like Power BI, Qlik or Tableau, whatever. So it will be an end-to-end solution. Along with the existing process, we will try this.

Then we will have a discussion with them stating, “Okay, this is all possible and this is not possible because of a budget constraint,” or whatever the constraint may be. So we have to talk like this and we have to do a proper gap analysis and then come up with one approach which brings a smile on both our faces.

Kirill: (Laughs) That’s a good way of putting it — one approach. So you just bring smiles to people’s faces. I think that’s the best job. It’s like Santa Claus, you’re like Santa Claus of data science.

Deepak: Yeah, that’s what we are here for. If you just give what they ask for, smile will not come. If you give them something more than what they ask for, that’s when the smile comes, and you see a happy customer, and you’ll also see many returning customers. When you give something, you should not just give what they ask. You should give an impact, that’s what I call it. Impact is what is very important, rather than just “Give a solution.”

Kirill: That’s true. And what part of your job is education? Obviously, you need to educate your clients, or your client’s employees, about how to use this product and how to get the most benefit out of it and get the correct insights, not the incorrect ones. So what part would you say is education? What role does education play in your career?

Deepak: Education is very important when it comes to business intelligence and data visualization. The reason is, as I mentioned before, you have come up with some product and if there is none to use it, no matter what your product does, it goes for a toss. So, when you do something, people have to be perfectly educated about what you did and how they can use it. So when it comes to — I’m a strong believer that when you design a dashboard, or when you come up with a product, that product should be following a certain methodology.

For me, I consider all the users as a king. For example, let’s talk about a king’s life. If a king wakes up from his bed, before his feet touch the floor, there will be sandals kept there. When he walks down to his bathroom, automatically all the soaps, towels and everything, whatever is going to work today will be ready and lying there. Just tell me one thing: Would the king even know who has kept and when they are kept and why they’re kept. He doesn’t have to worry about these things. He just has to get into the bathroom, and he will take his towel.

According to me, the user interface and user experience has to be like this. For the user, it has to be very natural. You shouldn’t even realize that these things are all very well-planned and kept here by someone and that’s when we have to use it like the soap. It has to be very natural for the people. That’s why I call it cognitive. So, the natural way of digesting things. You have to design your products such that it is very natural for people to use. If you keep your search bar somewhere in the bottom down, definitely people are not going to find that at all. The search bar, by default, it has to be in the right top or somewhere that people focus by default.

Kirill: Yeah, I totally understand. So where they’re used to seeing the search bar — on most websites the search bar is at the top and so on. And at this point we’re slowly venturing into product design. Before we continue with that, can you explain a little bit for us? For people who are not really familiar with business intelligence, what is a product in business intelligence? What are these things that you deliver to your end users? What do they look like? How could you quickly describe them to us so that we can have an image in our heads what a business intelligence product is?

Deepak: So, as I mentioned earlier in the podcast, business intelligence according to me is a decision support system. When you claim that you’re a hero and you don’t have proper data for it, you are just a person with an opinion. I strongly believe in that. For your organization, when you get into a diagnostic mode and see how your business is performing, and get insights and plan your future, you need data. So once you have your data, you need a presentation layer up above what I would call a ‘business intelligence layer’ where you can ask questions to your data and interact with your data and come up with your findings to construct your future.

So that is the layer I’m talking about, that is the layer which is called business intelligence, which is very important for each and every organization. So if you just have data lying around and if your data keeps on growing and if you don’t ask proper questions in the right time to your data, just imagine about your organizations. It would be just flat. It would be just following whatever has been followed, and it would just keep on doing that. There would not be any optimizations. There would not be any study of what happened, what is happening and what is going to happen. To answer about all these W questions – what, when, where, why – you need data. So when you have data to ask this question in a seamless way, you need a business intelligence layer.

Kirill: Gotcha. So, in a way, a business intelligence product brings together data of your organization and presents it in an easy-to-read matter. For instance, in Tableau, that would be like a Tableau dashboard, in Qlik, it would be Qlik dashboard or Power BI dashboard… It’s mostly dashboards, the way I imagine it, and everybody’s seen these. There’s a pie chart, there’s a bar chart, there’s an area chart at the bottom. And from that, just by looking at it, you can tell, “Okay, we’ve sold this many products. Revenue is up, this is down,” or whatever. Or it could be a segmentation dashboard for a different department. Is that about correct in terms of a visual image of what a business intelligence product looks like?

Deepak: True, very true. When you said, “From various departments in a single dashboard,” that talks about it. So, when you have different departments and different data laying around in various departments and it is not segregated, then you will not get insight. When all your data is segregated from various departments and you put it on a dashboard and you understand the associative relation between each of your departments, then comes the insight. So that insight to you can be provided by business intelligence layer is what I’m saying.

Kirill: It totally makes sense. That’s pretty cool. What we mentioned, that in different departments you have different data and different goals. So maybe the finance department wants to know information on the sales and the revenues and expenses and so on, whereas the operations department in a big company that has a call centre, the operations department wants to have a dashboard on how many calls are they getting, how many calls did they get this week, how many calls did they answer, how many calls they didn’t answer, how many calls were escalated, how many e-mails they got, they only get information on that, so completely different purposes. Do you have a favourite? What is your favourite type of department to work with? Or tell us maybe about the differences of working with finance, operations or other departments and the different type of dashboards that you’ve created throughout your career?

Deepak: For me, HR is really, really interesting data, always, because I’ve done a lot of things in HR analytics. When it comes to HR, the way of you seeing the data would be completely different. What you just described, sales, operations. It’s all about numbers, right? But when it comes to HR, it’s about the people. Salary would come from a different department or whatever department they’re tagged to. And the company has its own KPI of deriving how people are performing, how productivity is there.

So, when it comes to KPI in HR – KPI is the key performance indicator – what I try to say is, when it comes to HR, it is not about the KPI alone. It’s about people. You have to take people into the measure. There are many other parameters that should come into play when it comes to HR department. That’s the reason I like HR data a lot more. Whatever the dimensions you see the data, every time you will find some interesting insight. And those insights differ from various organizations. Organization A might not be having the same insight in the same situation as for organization B, depending upon their HR wireframe and so on. That’s interesting data, I would say.

Kirill: Okay. That’s really cool. And with your experience in dashboards, you obviously know some best practices and how to create these business intelligence products. Can you share some insights with us, some tips that you can give to our listeners about what are some tips on creating these business intelligence products so that they are indeed, as you said, useful to the people? So maybe how much information there is, how many maximum charts there should be on a dashboard, or what colours to use or anything from your experience that you think is important, some important guidelines to follow when creating BI products?

Deepak: Yeah. So, when designing a dashboard, when it comes to best practices, you have to keep certain things in mind. The first thing, and very important thing, is increasing the data-ink ratio. So when it comes to a dashboard, it is very clear that we are going to put some insights for your data. Other than data, nothing else should speak in your dashboard. That’s one primary important thing that I had to highlight. Let’s say that you come up with a very good insight in a bar chart and your title is 16 font size. Just tell me whether people would look for insights in your bar chart or in your title?

Kirill: In the title because it’s so big.

Deepak: Yeah, definitely. It’s so big. So, you have to be really concentrating in your dashboard where you want the people’s focus to be and you have to be carefully drafting it. And let’s say that you have five or six charts in the same dashboards and you really feel that you need all the five or six charts. Situations in this place would definitely ask you — if I am sitting beside you, I would ask you to revisit again. If six charts are there, which would be the first one people would be looking at and whether — when correlating all the six charts in the same dashboard, you should be making sure people should not derive some wrong insight that you don’t want them to. And when you come up with six charts in the same dashboard, it’s about landscape as well, how your real estate is going to be maintained and whether people will be able to focus.

As I told you earlier, the data-ink ratio should be increasing and the space between each and every object, not just charts – let’s say title, let’s talk about headers and footers, let’s talk about logo placement – each and every object in your dashboard should have at least a .5 centimetre to 1 centimetre gap between each object. I think Tableau 10.4, the latest version of Tableau, is quite concentrating on this stuff which is quite exciting. I’m very eager to try that as well. So they’re going to come up with a concept called ‘spacing between objects.’ If you set 0.75 centimetres as to spacing, all the objects will be evenly distributed and will have a white space around that.

Things like that would let the user clearly differentiate various objects and concentrate. And your logo placement and colours you choose, that’s very important. When it comes to visualization, colours are very important. Also, I know that you have a separate course in Udemy for colours alone.

Kirill: Yeah, yeah. I personally learned so much from creating that course. I didn’t realize how colours are important. I mean, I realized that they’re important, but I didn’t realize how exciting this theory of colours is. Yeah, you’re right, it’s really cool.

Deepak: Yeah. And when it comes to colours, you have to make sure colour blind safe. And when you are very sure that you have a brand and you wanted to generate a colour palette from the brand logo, you have certain tools in website like Coolors – coolors.co – that’s a very good website for you. If you just upload your picture, it will give you a colour palette to follow so that your colour palette, whatever you are following in the dashboard, would almost go with your company standards.

Kirill: Yeah, and there’s a couple of other tools. There’s a Coolor at Adobe – color.adobe.com – the same thing where you can upload your image. Yeah, Adobe Coolor, maybe that’s the same one we’re talking about. But you can find a couple of those tools online, they’re very useful, I agree. Sorry, you were going to say the next thing?

Deepak: Yeah, things like this would be — you have to leverage many things when you come up with a dashboard. Not only data tells the story. Things like colours, how you maintain the real estate of the dashboard, and titles, how good is your title. I can tell you that just from your title, people get 30 to 40% of what is there in the dashboard. You have to very carefully choose your title. If you are talking about sales and if you return something like ‘Profit Margin’ as your title, people are going to look for something called ‘Profityou’re your dashboard and there will not be any value for profit and they’re definitely not going to like it.

And the final one would be the data quality. The data quality has to be checked not only once or twice, at least thrice, because when you put in the dashboard, it is like you’re certifying that this is the dashboard and this is where you have to derive insights from. And just think about the scenario where you have sourced the data from the wrong place and people are making decisions out of that dashboard. So you have to be very sure of what data you’re using. That’s very important as well.

Kirill: That’s really cool. Let’s sum it up, these insights. We have the data-ink ratio, which is actually a cool term. Data-ink ratio should be increased, should be quite high, meaning that it shouldn’t have less stuff that doesn’t convey insights that are auxiliary or they’re just there for visual help. You should make sure the space between objects is sufficient so that it all looks good, it doesn’t look like it’s cluttering each other. Colours are very important, and we have some tools such as — you just sent me Coolors, so coolors.co or you’ve got colors.adobe.com. It can help you derive the colours and make sure it’s colour blind safe. Then we’ve got the title, so we have to have a good title and data quality.

I like how you put it, that data quality has to be checked at least three times. You are basically certifying that it’s all correct and this is where you derive data. I have an interesting question for you. A lot of times I hear from data scientists about pie charts, that pie charts are evil and they should not be used. What’s your opinion of pie charts because I’ve seen them used quite a lot in BI?

Deepak: There’s also a very good blogger, I’m sure you know him, his name is Andy Kriebel.

Kirill: Yes, yes. It’s so funny, he’s coming on the podcast very soon.

Deepak: Yeah. So, his tagline is “Friends don’t let friends use pie charts.” (Laughs) That’s important. Pie chart has its own way of expressing the information. In my experience, I would use pie charts in only one instance, which is individual to whole comparison. Let’s say you wanted to compare what are all the mobile providers. For example, let’s take Apple, Samsung, LG, Nokia and so on, and let’s say you want to see what is Apple’s share and others. Let’s say that Apple will be 35% and rest of all will fall into 65%. That is called individual to whole comparison. For those alone, I would use a pie chart. Other than that, if you have more than three dimensions, I would not suggest a pie chart. Other than individual to whole, I would not suggest a pie chart anywhere else.

Kirill: Okay. That’s really cool. I will bring this up with Andy Kriebel, talk about it more with him. This is an interesting point. Thanks for sharing that. And what’s your favourite type of chart?

Deepak: When it comes to charts that are simple, I like the bar chart. But when it comes to complicated stuff, when you want to see the distribution, I like box plot more.

Kirill: Okay. Why do you like box plot so much?

Deepak: Box plot tells you a different story. Every time you click on a box plot chart, it tells you a different story.

Kirill: Okay. By the way, these visualizations, this is the next thing I want to talk about. These visualizations aren’t just visualizations. They’re called dashboards for a reason, because they’re interactive. You create them in a way that people can click, so when they click on something, the rest of the dashboard adjusts and talks about that specific part. For instance, if you have a bar chart for different age categories, or different age groups of your users or age groups of your customers, and then the user of the dashboard click on everybody on the bar that’s 25-35, then the rest of the dashboard will focus in on everybody who is 25-35.

Tell us a bit more about interactivity. How important is it for these dashboards to be interactive, and have you noticed any changes in the behaviour of users of these dashboards over the recent years? Because it’s becoming more and more easier to create dashboards which are interactive, I think people are getting more used to them now.

Deepak: When we talk about interactivity, if you ask me, interactivity is nothing but asking questions. When we talk about asking questions, we wanted a technology or a product to remember what we asked before the second question. For example, I asked three questions and we wanted the third question to be answered after considering the first two questions I asked. This is the power, right? So, when you ask one question—for example, if I ask the Siri app — I’m talking about the Siri voice command platform in Apple — if I ask Siri what is the weather in Sydney, it tells me what is the weather. And the second question is, should I bring an umbrella today. So it should consider the weather, which is my first question, and it should answer the second one also.

So, the correlation is what I’m talking about. This is what I consider is very important when it comes to Qlik and Tableau. Also, a very favourite question – I don’t know whether you would ask it – but I would put it in the podcast: Everyone always asks me which is better, Qlik or Tableau.

Kirill: Oh, yeah, that’s a good one. So what’s better?

Deepak: That is one question that everyone asks me whether it is in the interview or whoever I meet and talk about the visualization tools. According to me, Qlik has its own power and Tableau has its own power. For Tableau, its power comes from the drag and drop interface, very intuitive, people can come up with a dashboard in just two to three minutes and things like that. When it comes to Qlik—

Kirill: When you’re comparing Tableau versus Qlik, is it QlikView or Qlik Sense?

Deepak: I would compare — if it is going to be a head-to-head comparison, I would take Qlik Sense because it follows the same methodology as well: drag and drop, easy, intuitive. When it comes to Qlik, the power lies behind what I call a ‘subscripting layer’ where you can blend the data, where you can play with the data, multiple layers of ETL.

For example, you have [indecipherable], you wanted to make it as a mail, and you have a particular number you want to add it up with another number and do some mathematical expression layer by layer, Qlik is very good at doing it. Tableau to an extent, yes, but not like Qlik. Qlik, when it comes to dashboard building and publishing and getting it to the user, it follows its own pathway, Tableau follows its own pathway. But the power of Qlik lies in associative experience.

The associative experience, if you ask me to talk, I will talk for days and hours. It’s a very beautifully patented one that’s patented by Qlik. That’s the one thing that will pull a big crowd into Qlik. Tableau pulls the crowd because of its intuitiveness and drag and drop interface.

Kirill: Which one would you say is easier to learn for somebody listening to this podcast who wants to start?

Deepak: That depends. For someone who is listening to the podcast, I would say—I have a hard and fast rule. If your data lake is very good, if you feel that your data doesn’t need any massaging at all, it is already done and if you feel your data is very good, go for Tableau. If your data needs multiple levels of cleaning, massaging, and you don’t have a data warehouse at all, you don’t have a massaging layer in your enterprise at all, Qlik comes to rescue you. So you directly connect to an interface, you clean, massage and save everything in QlikView data format and then you consume it to the presentation layer. That’s the way.

Kirill: Cool, gotcha. And you mentioned as well, you work with Power BI. What do you think of Power BI? I ask this question because I’ve noticed them—it’s a Microsoft product, for those who don’t know, and it’s free as opposed to Qlik and Tableau, it has the same goals of what it can do—but what I’ve noticed is that it has been developing and growing with huge leaps every single month for the past year or so. They’ve been releasing updates every month. And it stands to show, a proof of their growth is how the Gartner’s Magic Quadrant has positioned them a year ago.

Gartner’s Magic Quadrant is for all products and they have one for BI products, it comes out in February, and last year they were somewhere in the middle among everybody else, but now they’re in the lead alongside Tableau in that Magic Quadrant. So what are your thoughts and views of Power BI?

Deepak: For me, Power BI stands great because every two weeks they give proper updates. And the second thing is the integration point of view. People want flexibility now. If you say, “This is the way my product works,” and you don’t get more flexibility, then people basically don’t like your product. Just think about Power BI. It can integrate to any Microsoft products seamlessly. And imagine embedding your dashboard in your SharePoint. Take any organization. 60%- 70% of our organization is all Microsoft-based. I have SharePoint in my organization; I have Excel, Microsoft Word, PowerPoint laying everywhere.

So whenever you talk about BI tools to people, the first question, the first good question they ask is, “Can I export it to Excel? Can I export it to PPT?” because that’s what is going to be shown to all the board members and CXO level executives. So, when it comes to this, Power BI understand these things and they export functionality and connecting to all its database SQL, SSIS, SSRS layers, and DAX cubes. It clearly understood what it wants. And also, for anyone who knows Excel, catching up with Power BI is very easy. Just imagine the number of people who use Excel in this world. And if you say that will be a very less learning curve if you know Excel, then who wouldn’t learn Power BI?

That’s the point. It’s about grabbing your share perfectly. Microsoft did that perfectly, I would say. It clearly understood who all can be its end user and what other words can attract people like ‘Excel users’ and ‘Microsoft-based organizations.’ They can use these words to easily pull people inside. They’ve clearly concentrated in those areas like exporting functionalities and connecting seamlessly into Microsoft and being on cloud, which is a buzzword now everywhere. If you say, “You can go on cloud in just five days with our product,” then definitely you get one step ahead than any other product.

Kirill: Yeah, totally. That’s a pretty solid overview. It will be interesting to see how all these three compete and other products compete over the next couple of years. It’s kind of like a horse race. Every year you check who’s in the front, who’s in the lead, who has got what new. Yeah, exciting times.

Deepak: Yeah, did you see that? Yesterday, or I think day before yesterday, Tableau acquired a company called ClearGraph.

Kirill: No, I didn’t see that. That’s interesting.

Deepak: Yeah. ClearGraph is a company—say you just type ‘Sales by country’ and hit enter, it will give you a ‘Sales by country’ bar chart just by your search.

Kirill: Nice. That’s really cool.

Deepak: They’re doing a lot of things in natural language, NLP and text processing. So, the ClearGraph acquisition definitely shows that all the BI tools’ next mission would be understanding whatever people type, like Google. So, the Google-like experience is going to be the next big thing in the data visualization world.

Kirill: That’s really cool. Then the only think you have to watch is the correctness of it, right? It’s like is it actually giving you what you want or something random.

Deepak: Yeah.

Kirill: And what I also like about Tableau is that they have a very strong user community. There’s lots of bloggers who write about Tableau, there’s lots of people on the forums, so if you have any questions you get them answered very quickly. I don’t think that’s the case for QlikView and Power BI, not yet anyway. What do you think of that?

Deepak: True, very true. The community and the way they market their product and the conferences that are being held every year and the way they promote the conference, I think they have very good team structure. One team promotes a community, one team answers all the queries of people, and the learning community is almost free. You can learn from zero to hundred, everything for free when it comes to Tableau.

I accept some mastery tricks that you provide in your Udemy course, I would say. Other than that, if you want to just understand the basics and just keep going until even intermediate/advanced, everything is properly covered in their course curriculum for the very basic users. But to go to an advanced level, you need guidance from people who achieved that already.

Kirill: Yeah, I totally agree with you. I’m not going to argue with that. I think you can totally get everything for free in the Tableau courses and online on YouTube. The only kind of difference and what my courses bring is the element of a journey and the elements of more applied case studies that you go through and you practice and so on. It’s kind of a different approach to education, but yeah, I totally appreciate and it’s really cool that Tableau provides this education and that people can pick it up pretty quickly. Good thing.

I’m cautious of time, we’ve talked a lot about these different tools and business intelligence. It’s so great to get some of your insights. I’ve already learned a lot personally. And I would also like to talk about your personal journey as well. From your LinkedIn I can see that you only recently joined ASG Group. How are enjoying it at the company? Do you enjoy the company culture?

Deepak: Yeah, the company culture is really enthusiastic, energetic, and more than that. I heard one important statement from my boss which is listening to people, listening to our customers. So, when you listen to people, instead of just talking to them, listening is the one important capability that every BI consultant should have, which was a good learning for me when I started this job. When you put yourself in that perspective, when you listen to people instead of just pushing whatever you have in your mind, you will just open up to give more suggestions.

Instead of giving an idea of what a business intelligence layer does, you will give them an idea that “Your data warehouse itself has a problem. Do you mind if I take a look?” Things like that. So if you ask those questions, then people open up. “Okay, do you want to do some consulting on data warehouse and give us some insights to what’s wrong with our data warehouse?” and then let’s go to the next layer, which is business intelligence. That’s when it has to start.

So I strongly feel that instead of just selling your single product, it has to be an adaptation of their very own data culture. Instead of you just selling, you have to adopt their data culture and provide an end-to-end data solution. That’s what ASG is all about and that’s all the services we provide to our customers. And that’s why people keep returning to ASG. If you just trace back any people who have worked with ASG, they would come back again just because of this quality.

Kirill: That’s fantastic. And I really like what you mentioned about listening. I think that’s very important. You can save a lot of time and efforts if you just listen carefully to personal requirement, and not necessarily just in consulting. Even if you’re within an organization trying to help somebody, if you listen to them carefully and not make assumptions about what they want and what their problems actually are, if you hear them out you can really save a lot of time by focusing on the right things.

I’m looking at your LinkedIn again. Throughout your career, you’ve gone through a huge transformation, a huge growth. You started as an Assistant System Engineer back in India and then you had some big roles like Consultant, Associate Manager, BI Specialist and Senior Technical Consultant for several years at a time. You obviously have a vision for your career. You’ve been, as I can see, deliberately selecting these opportunities and growing and growing. Now you’re in Sydney, Australia, working for ASG Group and it sounds like you’re having lots of fun. What would you say have been the most important qualities for you that helped you build this career for yourself?

 

Deepak: What I feel is, from my academics, when I study a topic, I will not turn my pages until I’m very clear about the topic. That put me apart from the crowd. During my college or school days, if you see my answer paper and other answer papers in my class, people would have answered for 100 mark and score 98 or 99 or even 60 or 50, and if you take my answer paper, I would have only answered for 60 mark and I would get all 60. That is one characteristic which has always put me outside, as an outlier from the total crowd.

So, the way I study is, until I understand a certain topic completely, I will not move further. Let it be about BI or a data warehouse or any other topic, if I’m reading about the topic and if I’m stuck in the second line and if I’m not understanding the word from the second line, I’ll just Google about it, read about it, get myself clear, and then I will start reading the third line. I will not cross the second line until I’m very clear. That’s one good quality I have, which is attention to detail.

The way I achieve mastery in any skills I take—for example, I started my career, as I told you, with Unix, then Oracle, then Informatica, then Cognos, then MicroStrategy, then QlikView, then Tableau. So what I feel is an important quality is your basics, no matter what, always have to be very strong. Your advanced quality in certain tools or products can be wavering, but your basics of any product should be very strong. If your basics are very strong, for you to reach mastery level is always a cakewalk. But if your basic itself is not strong, although by mistake or by luck you reach mastery level, it’s very highly likely that you might fall down on any day. So I strongly feel if one’s basics are figured out clearly, then you are very good to go.

Kirill: Fantastic. That’s really cool. On that first one, just to recap, first one was a very unique quality. I don’t think I’ve encountered this in person like this, where you will just focus on that one thing that you’re currently working on and you will make sure you know it really well and then you only move forward, and the second one was basics have to be very strong.

On that first one, I wanted to ask you, have you ever encountered a situation where you just weren’t able to move forward, where you came into a roadblock and it was just impossible to either learn that thing or get that thing done or whatever you were focused on, there was something preventing you from doing it? Has that ever happened and what did you do in that case?

Deepak: Luckily, I’ve not come across this situation. The reason being is we are wealthy enough as a world, we are wealthy enough that we have excellent resources available and tools like Google, where you just type and it gives you whatever we have. We are not here to invent something new. Everything is there available on the Internet. For me, at least, I think if I would have been born before the 1940s, I would have come across this.

Kirill: Yeah, gotcha. Good point. With Google, you can pretty much find an answer to anything. Okay, that’s been really cool. You know, we’re slowly coming to the end of the podcast and I wanted to ask you, from what you’ve seen in the space of business intelligence and from the work you’ve done, where do you think this whole field of data science is going and what should our listeners look into to prepare for the future?

Deepak: When it comes to the future, the future doesn’t want people who just have a balance of technology. The future needs people who understand the technology, who understand the process, who understand people and deliver something which balances everything together. We wanted someone who can listen to the problems and deliver solutions, custom-tailored solutions according to the need, not the same one-size-fits-all. It’s old theory now. Everyone needs a different stitch and everyone wants it in their own way and you have to make sure you have got the right skills to provide that.

Kirill: Gotcha. People, process, technology – those are three important things. Can you elaborate on that a little bit more?

Deepak: When you want to sell or project some idea about yourself or any future-proof product you want to come up with, just imagine your product with certain end users. Any product that has been built or going to be built without keeping some end users in mind, the product will definitely not succeed. And same with the process.

For example, I’m going to come up with a product called a newspaper. Let’s say that the whole world doesn’t have something called newspaper for now. If I say that I’m going to come up with a newspaper now, how many people would really read a newspaper when all the information they want is available across the Internet for free? Although you charge 1 cent, do you think people would buy that? No. So when you come up with a product, or when you come up with a solution, or any platform or a service or anything, you have to be very sure of who are going to be your end users and who are you going to serve and what is the current problem they are coming across and how are you going to solve it? So these three things are all I’m talking about: people, process and technology. It has to be perfectly balanced.

Kirill: Fantastic. Thank you so much, Deepak. That’s really good insight. We’re going to end on that note. Thank you so much for coming on the show. A quick question: Where can our listeners find you, connect with you or get in touch so they can follow your career further?

Deepak: They can find me at LinkedIn. They can also reach me as a consultant through ASG.

Kirill: Gotcha. ASG in Sydney and LinkedIn.

Deepak: Yeah, LinkedIn. Just search for Deepak Prasad.

Kirill: We’ll definitely share that. And I have one last question for you. What is a book that you can recommend to our listeners that can help them become better data scientists?

Deepak: If you want to become a data scientist, first you have to have a really good hold of your data. When you don’t have a good hold of your data, no matter what algorithms you know or what skills you get for data science, it will go for a toss. So for data analysis purposes, I strongly recommend a book “Head First Data Analysis” by O’Reilly. And the second book I suggest is a book called “Data Smart.” That is for data analysis as well.

For visualization, I strongly feel there is a very good book that I will read again and again and again that is called “The Truthful Art” and “The Functional Art.” There can’t be any better book than this according to me. And I bought a good book recently which is called “The Big Book of Dashboards” which is quite interesting as well.

And for data science—for me, when it comes to data science, you have to have a good hold of many algorithms and real use case studies. That will basically come from the “Data Smart” book itself, but there are many other data science books called “Doing Data Science” from O’Reilly and that’s a good place to start. And then once you have decided you’re going into data science, “Doing Data Science” is a better start, and then once you’ve chosen which technology you’re going to take, whether it’s going to be R or Python, according to that, you have to choose your books.

Kirill: Wow. That’s a whole library there, guys. “Head First Data Analysis,” “Doing Data Science,” “Data Smart,” “The Truthful Art,” and “The Big Book of Dashboards.” I actually heard of that last one, “The Big Book of Dashboards.” I haven’t read it yet, but somebody on the podcast mentioned it so it must be pretty good. I’m sure you’re going to enjoy that one. Once again, thanks a lot, Deepak, for coming on the show. I really appreciate you coming in and sharing all these insights. It was very interesting to talk about business intelligence and different types of tools and approaches, so thanks so much.

Deepak: Thank you, Kirill. Thanks a lot for this opportunity. And more than me talking, I learned a lot from you as well.

Kirill: Thanks, man. All right, take care.

Deepak: Thanks. Take care. Bye.

Kirill: So there you have it. That was Deepak Prasad from ASG Group. I really hope you enjoyed today’s episode and that you picked up some interesting ideas from here, whether it be about business intelligence or about your career. And personally, my favourite part was when we discussed the three pillars that you need to take into account when deploying business intelligence tools. That is people, process and technology. And personally, I actually think that it’s not just relevant to business intelligence, but in many areas of business, you need to think about these three things, about people and process and technology and how they all work together, how people use the technology to execute the processes that they should be executing, how the processes are tailored to the people to maximize the power of technology, or how the technology is selected to help the people execute the processes. So there’s lots of ways that these three interact and depending on the current business situation, it’s important to look at them from different perspectives through different lenses.

So there you go. You can get the show notes for this episode at www.www.superdatascience.com/87, and of course, there you will find all of the resources mentioned in today’s show, including a URL to Deepak’s LinkedIn where you can hit him up and connect with him and see how his career progresses further. And I look forward to seeing you here next time. Until then, happy analyzing.